NVDA is coming down to the EMA20 for a test. Another 1/8th of my last cash position is being devoted. For now, will hold some cash to see how the test goes. January 10 is far enough off to suffer the loss of time value on a stock that I view as having lots of long-term fundamentals to keep it from meandering too low. Still, I'd like to keep some cash back in case this test goes south, producing a better trading opportunity at a lower price.
So, for the record, 25% of my virtual cow-carving portfolio is in UVAAC. This second purchase would be made for $1.95. Math to follow soon.
Update, right over the EMA20. 5% more @ $1.70.
Thursday, September 17, 2009
Wednesday, September 16, 2009
Talk About Leeroy
NVDA just got whacked. Likely due to report that their new chip came back from first silicon with a 2% yield. This can spell all sorts of bad news, but in reality it won't. The engineers will investigate the chips for causes of process flaws. Somewhere on some wafer enough clues will be there to figure out what's wrong with the silicon.
What you worry about when it comes to chip stocks is when the design or process is fundamentally flawed. NVDA's a fabless chipper, meaning they outsource the foundry work. Foundries usually are just a step behind Intel's production technologies, which typically funds most of AMAT. What I'm getting at is that NVDA's not looking a failure to get a new exotic process working, but instead the simple glitch in what was supposed to be a proven process with a new chip design.
Anyway, this is a Leeroy event. I had no idea the chips would come back bad. I did think the stock would be vulnerable to any upset and have to retreat to the ema20. Well, time to take what's been beautifully laid out on the table.
For the next paper trade, I'm going to select a Jan 10 call @ $15. Hello UVAAC for $2.15. Trading in 12.5% of whatever cash resulted from the previous paper trades. (I promise to get the numbers worked out within a week) This is another example of a little option trading excercise.
What you worry about when it comes to chip stocks is when the design or process is fundamentally flawed. NVDA's a fabless chipper, meaning they outsource the foundry work. Foundries usually are just a step behind Intel's production technologies, which typically funds most of AMAT. What I'm getting at is that NVDA's not looking a failure to get a new exotic process working, but instead the simple glitch in what was supposed to be a proven process with a new chip design.
Anyway, this is a Leeroy event. I had no idea the chips would come back bad. I did think the stock would be vulnerable to any upset and have to retreat to the ema20. Well, time to take what's been beautifully laid out on the table.
For the next paper trade, I'm going to select a Jan 10 call @ $15. Hello UVAAC for $2.15. Trading in 12.5% of whatever cash resulted from the previous paper trades. (I promise to get the numbers worked out within a week) This is another example of a little option trading excercise.
Friday, September 11, 2009
UVACN Update
Selling the UVACN for $3.55 per contract. Looking to re-enter and eying some other activity on the Dow.
In the face of any uncertainty, it's always best to run when it comes to options.
In the face of any uncertainty, it's always best to run when it comes to options.
Thursday, August 27, 2009
The Onion of Truth
Ugh...the trends moves on. Looks like there won't be an opportunity for a pullback buy. NVDA's basically at such a sharp ascending triangle that there's very little room for the trend ping-pong to continue. It can't break $14. It can't drop below the EMA20. I'm about to use 12.5% of my "money" to pick up some more UVACN (Mar 10 NVDA Calls).
Recall that when I made the trade, I had a lot of reasons for making the trade that would seem moot if my call was right. For instance, if the EMA20 is a trading signal, why does the MA50, which will be below the EMA20, even matter?
The answer is that no trade is 100% certain, but trades with lots of layers of certainty tend to take care of the trader. If you're not right about this contention point, maybe there's a larger contention point brewing that will build momentum if the first pattern fails. And so on and so forth.
On the other hand, NVDA just needs to stably break $14 to go into a little bit of a pop. It just needs to break $14. Not today, not four weeks from now. When it happens, the stock will have a tendancy to "fill the gap." The gap ends at $17, at which point UVACN will have $3 of intrinsic value and at least some time value left.
So here goes. The total is 12.5% of my cash on some options that were trading at $2.10 at the beginning of this post. The other 12.5% will probably follow shortly, but you'll get an update on it. I'll do the math regarding how many contracts I actually would have sought to obtain later.
Stay tuned.
Recall that when I made the trade, I had a lot of reasons for making the trade that would seem moot if my call was right. For instance, if the EMA20 is a trading signal, why does the MA50, which will be below the EMA20, even matter?
The answer is that no trade is 100% certain, but trades with lots of layers of certainty tend to take care of the trader. If you're not right about this contention point, maybe there's a larger contention point brewing that will build momentum if the first pattern fails. And so on and so forth.
On the other hand, NVDA just needs to stably break $14 to go into a little bit of a pop. It just needs to break $14. Not today, not four weeks from now. When it happens, the stock will have a tendancy to "fill the gap." The gap ends at $17, at which point UVACN will have $3 of intrinsic value and at least some time value left.
So here goes. The total is 12.5% of my cash on some options that were trading at $2.10 at the beginning of this post. The other 12.5% will probably follow shortly, but you'll get an update on it. I'll do the math regarding how many contracts I actually would have sought to obtain later.
Stay tuned.
Monday, August 24, 2009
"That Guy Stole My Market Manipulation Software!"
Today's Leeroy is more refreshing in ways. Sergey Aleynikov, former Goldman Sachs employee was arrested on suspicion of stealing software used for millisecond trading.
I'll keep watching, but I suspect that the derivitives bubble was a lot more well known than a lot of people want to admit. If I dig back far enough into my own posts on a trading forum a few years ago, theres a post regarding the slow down in home sales likely cascading into increased mortgage defaults. At the time it was rather clear to see the lack of real health in the housing market. After a few years of near zero interest rates, home lenders had litterally sprouted like kudzu, and people were buying into the market because the market was strong.
Be it known, home buyers are not nearly as smart as equity market investors. They will not recognize that what goes up can also come down. I had never seen a real-estate bubble, and it really didn't factor into my projections that the housing bubble and derivitives bubble could actually fuel an equity bubble taking the Dow to 14k. Thus here we are with tons of defaulted mortgages and a Dow 9k. I remember a commercial with a computer generated bull and bear. The bear gave his stereotypically gloomy estimates. They actually came true.
Update: After thinking about this a little more, I see the potential for something larger. The prosecuter looks at the code and finds evidence of techniques that are clearly designed to manipulate trading feedback. The code is used to press charges against Aleynikov and subpoena more code from Sachs. The code that is obtained from Sachs leads to charges and more subpoenas against Sachs. In a plea bargain, Aleynikov testifies against Sachs as the lead witness. Aleynikov took the code knowing that Sachs would have to chase him out of the alley and into the open.
By chasing him, Sachs might end up costing themselves more than having let him go. The interesting part is if Sachs thinks that protecting their code was more valuable than anything they will lose by chasing Aleynikov. Depending on how this unfolds, it could draw enough scrutiny onto big trading firms and hedge funds to get serious investigation into the practices as a whole, and given how unpopular the bailout was, congress will be ready to throw a lot of ink at the SEC and markets in general. Right now Wall Street is the Afghanistan of 2001.
At a bail hearing three days later, a federal prosecutor asked that Mr. Aleynikov be held without bond because the code could be used to “unfairly manipulate” stock prices. ~ New York TimesAs opposed to arresting Goldman Sachs for probably using the software to make billions of dollars? I sincerely hope that someone makes the connection between the theft and who it was stolen from. We might be seeing a test case so to speak since this is likley the first time any prosecutor has had their hands on such software.
Until the late 1990s, big investors bought and sold large blocks of shares through securities firms like Morgan Stanley. But in the last decade, the profits from making big trades have vanished, so investment banks have become reluctant to take such risks. ~ New York TimesRecall what I wrote in an earlier post regarding the large spike in volume after 2000 and the formation of a down megatrend for most of this decade:
Computer trading started in the 80's and was driven simply by the emergence of the technology. What could have lead to the need for so much more trading activity? Let's say you're a major fund manager and you realize that the megatrend has meat in it and that investing long isn't going to pay well. What do you do? Play volume, derivatives, arbitrage, and market smoke and mirrors to take advantage of every move that occurs in the relative market stagnation.Looks like I'm not the only one who suspects that the down megatrend was widely recognized by a lot of large trading firms, driving a huge spike in adoption of electronic trading systems for price manipulation and market-making at ludicrous speed.
Notice that the volume was about a billion shares per day and was fairly consistent over the last decade. Notice how it started directly coincident with the tech crunch. No, this isn't a conspiracy theory. Don't read into this line of thought too much, but I will go ahead and suggest that there was a recognized need for large trading establishments and hedge funds to generate profit from trading in the relative shortage of investable stocks.
What makes this line of thinking consistent is that the trading activity didn't continue to grow, suggesting that market fees and other limitations put a hard cap on how much profit could be squeezed out of this type of trading. Or perhaps there is an overlay of two conflicting trends. Either way, the volume spike and subsequent stagnation starting in 2000 is a little curious and I'll get back to this before the end of summer. ~ from Falling Off the Blade
I'll keep watching, but I suspect that the derivitives bubble was a lot more well known than a lot of people want to admit. If I dig back far enough into my own posts on a trading forum a few years ago, theres a post regarding the slow down in home sales likely cascading into increased mortgage defaults. At the time it was rather clear to see the lack of real health in the housing market. After a few years of near zero interest rates, home lenders had litterally sprouted like kudzu, and people were buying into the market because the market was strong.
Be it known, home buyers are not nearly as smart as equity market investors. They will not recognize that what goes up can also come down. I had never seen a real-estate bubble, and it really didn't factor into my projections that the housing bubble and derivitives bubble could actually fuel an equity bubble taking the Dow to 14k. Thus here we are with tons of defaulted mortgages and a Dow 9k. I remember a commercial with a computer generated bull and bear. The bear gave his stereotypically gloomy estimates. They actually came true.
Update: After thinking about this a little more, I see the potential for something larger. The prosecuter looks at the code and finds evidence of techniques that are clearly designed to manipulate trading feedback. The code is used to press charges against Aleynikov and subpoena more code from Sachs. The code that is obtained from Sachs leads to charges and more subpoenas against Sachs. In a plea bargain, Aleynikov testifies against Sachs as the lead witness. Aleynikov took the code knowing that Sachs would have to chase him out of the alley and into the open.
By chasing him, Sachs might end up costing themselves more than having let him go. The interesting part is if Sachs thinks that protecting their code was more valuable than anything they will lose by chasing Aleynikov. Depending on how this unfolds, it could draw enough scrutiny onto big trading firms and hedge funds to get serious investigation into the practices as a whole, and given how unpopular the bailout was, congress will be ready to throw a lot of ink at the SEC and markets in general. Right now Wall Street is the Afghanistan of 2001.
Friday, August 21, 2009
UVACN.X
.X is the ticker suffix on yahoo for derivatives. UVACN is the March 2010 call for NVDA with a strike price of $14. Going to play a blog game on paper. Recall that I consider 50% cash to be sufficiently diversified. This is probably only true if you want to trade options. The biggest advantage of cash diversification is that you don't have to watch it at all. It's safe and keeps you from experiencing catastrophic losses, which is the point of diversification.
If you're not into options, just take this opportunity to watch me try to make the best of what's ahead. This will be the first trade that I'll make to build up a small pile of case studies in various types of trading regimes.
I've been waiting on NVDA to perform a gap fill for some time. The reason is that I'm long NVDA. In other words, I beleive that inevitably the value will hit $14, and when it does, there will be a gap fill. Leeroy has continued to relinquish market fears about larger economic recession. The right numbers with the right amount of sunshine keep trickling in.
Ideally I would wait for support, but we're reaching a critical level of contention. The gap is at $14 and 20day EMA support is over $13. Without some type of market pullback, we're going to hit the gap, and that's a sensitive trading region -- too sensitive to wait for the support.
Ideally you always buy options when the stock is trading down because the option orders are very finicky and whenever you trade them with the grain they tend to run away. Trade them against the grain and they will sell you all you want. To make a bar room analogy out of it, you're headed towards one side of the room when most people are moving away in search of greener tables.
However, it's still possible to trade a larve volume of options very quickly. Buy all at once, so that your crashing through existing orders before they can move, and buy into the market depth. I have seen numerous occasions where 2k or 3k contracts for large cap stocks are just twiddling around $0.05 across the spread. That's equivalent to 200k or 300k shares under contract.
In this theoretical trade, because I want to go ahead and open a position before the gap starts to fill, I will hypothetically trade 1k contracts at $2.15, which is a little over the current ask price. This would cost about $215k In reality I would try to work with 25% of my capital, which is 50% of the money I'm willing to commit. This is to hold a little bit of cash in case we do get a pullback. So I'm assuming a working capital of $860k. These numbers are just to keep the calculations simple.
Now, here's what I see in my crystal trading ball at this point:
Here goes 1k UVACN.X @ $2.15
After following up with another 25% of my paper capital, I will continue to monitor and look for the right time to sell, at which time I will be accepting the bid price on these options. Right now that's at $2.00, so just by making the trade, I've lost a little bit of ground. This what options are. You have to be able to trade with a very high degree of certainty. The moment you commit to a trade, you've already stepped backwards across the spread. After that, the time value will continue to decay until the expiration date. You don't break even on options hardly ever. Even if your predictions about the stock market are mostly right, you can still lose money. At around the one-year interval, I'm not too concerned about the time premium I'll be losing, but if things drag out, it's usually best to pull your cash out once your predictions are getting stale.
Oh, and if I were actually doing this, I would be using an IB account. Whatever you do, get real time quotes and market depth when you start getting this serious about trading. Delayed quotes will destroy you on options. Interactive Brokers has a decent UI, very serious minded trading fees, and access to lots of markets.
If you're not into options, just take this opportunity to watch me try to make the best of what's ahead. This will be the first trade that I'll make to build up a small pile of case studies in various types of trading regimes.
I've been waiting on NVDA to perform a gap fill for some time. The reason is that I'm long NVDA. In other words, I beleive that inevitably the value will hit $14, and when it does, there will be a gap fill. Leeroy has continued to relinquish market fears about larger economic recession. The right numbers with the right amount of sunshine keep trickling in.
Ideally I would wait for support, but we're reaching a critical level of contention. The gap is at $14 and 20day EMA support is over $13. Without some type of market pullback, we're going to hit the gap, and that's a sensitive trading region -- too sensitive to wait for the support.
Ideally you always buy options when the stock is trading down because the option orders are very finicky and whenever you trade them with the grain they tend to run away. Trade them against the grain and they will sell you all you want. To make a bar room analogy out of it, you're headed towards one side of the room when most people are moving away in search of greener tables.
However, it's still possible to trade a larve volume of options very quickly. Buy all at once, so that your crashing through existing orders before they can move, and buy into the market depth. I have seen numerous occasions where 2k or 3k contracts for large cap stocks are just twiddling around $0.05 across the spread. That's equivalent to 200k or 300k shares under contract.
In this theoretical trade, because I want to go ahead and open a position before the gap starts to fill, I will hypothetically trade 1k contracts at $2.15, which is a little over the current ask price. This would cost about $215k In reality I would try to work with 25% of my capital, which is 50% of the money I'm willing to commit. This is to hold a little bit of cash in case we do get a pullback. So I'm assuming a working capital of $860k. These numbers are just to keep the calculations simple.
Now, here's what I see in my crystal trading ball at this point:
- Over the EMA20 - check
- Over the MDA50 - check
- Below a gap - check
- Stock is long - check
- Market has no imminent contention points to resolve - check
- No pending (known) Leeroy events - check
- Stock is far away from plausible valuation limits - check
- No immediate additional product competition - check
- Potential to enter additional markets - check
Here goes 1k UVACN.X @ $2.15
After following up with another 25% of my paper capital, I will continue to monitor and look for the right time to sell, at which time I will be accepting the bid price on these options. Right now that's at $2.00, so just by making the trade, I've lost a little bit of ground. This what options are. You have to be able to trade with a very high degree of certainty. The moment you commit to a trade, you've already stepped backwards across the spread. After that, the time value will continue to decay until the expiration date. You don't break even on options hardly ever. Even if your predictions about the stock market are mostly right, you can still lose money. At around the one-year interval, I'm not too concerned about the time premium I'll be losing, but if things drag out, it's usually best to pull your cash out once your predictions are getting stale.
Oh, and if I were actually doing this, I would be using an IB account. Whatever you do, get real time quotes and market depth when you start getting this serious about trading. Delayed quotes will destroy you on options. Interactive Brokers has a decent UI, very serious minded trading fees, and access to lots of markets.
Tuesday, August 18, 2009
Dragon Bones
Faux-fact: Way back in the pre-Zhou dynasty in cHiNR (pronounced, "China") there was a practice of carving runic messages into turtle shells and heating them over a fire until they cracked from thermal stresses. Then an old man with one eye open much wider than the other and likewise off-center behavior would analyze the way that the shell fractured in order to determine the answer to whatever cryptic message was scrawled onto the shell. Then the emporer or whatever (China has not nearly as continuous history as Chinese historians, PRC, and other Sinophiles would have you believe) would make his interpretation of the old man's word and choose the path to righteous destiny!
These bones were burried for future generations to dig them up and hawk as a miracle ingredient in traditional Chinese medacine. And they were called:
Well, thousands of years later, and perhaps not yet too much brighter, here we are divining buy and sell signals from the stock market. There are websites hawking advice, possibly mafia gimmicks, and maybe tried and traitorous buy-and-hold tonic.
If you've been keeping up with my posts, you should have a decent feel by now for the concept of limited determinism. The rugby pile at the knife edge on the beach head in the bar room full of singles who want to be first, but don't want to be desperate. The chaotic cow that has absolute authority to vanquish the magician back into the realm of his game. The magician and Leeroy Jenkens battling it out unceasingly inside the circus tent that flows withing the chaotic probability zone.
What I'm really getting at is that there are places where the stock market's movements are absolutely limited by the price elasticity --- as well as places where bar room politics and magicians tricks and cameo appearences by Leeroy take over.
I have tried numerous times and many ways to figure out the correct analogy for how to make use of the serendiptitious patterns that emerge from the chaos whenever the stock market is trading well within the realm of price-elasticity, the places where limited determinism is more like conditional determinism, which is a paradox in itself.
The technical patterns, Leeroy effects, and magic shows are fun to watch. Inevitably there is a contention point, and that contention point will lead to the development of a new pattern, a new trend, a new wave to ride on. The capability of the wave to sustain itself is many times, by virtue of being well within the chaotic trading range, purely up to the surrounding chaos, which was itself decided in a nearly arbitrary fashion and wholly lacking of discernable sense to the average Vulcan.
In the end, the chaotic movements of the stock market are in so many ways just like the dragon bones. The charts almost even look like the cracks as they split through the dragon bones. How can this completely unreliable process provide any opportunities to make rational trading decisions at all? I give you my final answer:
The shape of each crack is arbitrary
The existence of cracks is absolute
What I mean by this is that you don't have to find meaning in the cracks, but never for a second think that just because there is no higher order that you can afford to ignore them.
And this is how the emporer rolls. Yes, the months and weeks leading up to a contention point should theoretically have no impact on the prices traders are willing to buy and sell shares at. At the contention point, the fact that the knife can fall either way would seem to suggest that there is no significance to the result. The cracks could have gone North and South or East and West and the old man still would have given his answer to the emporer just as if there was some greater meaning to it. The emporer's word is final. The follow-through of his beauracracy is like wise absolute. The follow through of the stock-market is no different.
When trading in the chaotic regions, try to spot the serendipity. Say not, "the stock will trade this way," but "if the stock trades this way, it would be likely to follow through this way." Then once the knife falls, if it falls in such a way that you think it has momentum and the blessing of the chaotic cow (it's well towards the middle of its price-elasticity curve) ride the storm until the next contention point. Better yet, if the pattern is stable, wait for the pattern's reinforcing signal, whether it's a linear uptrend or a moving daily average, and then make your move.
When dealing with a pattern that has room to run, it tends to do just that. That tendancy is strong enough to overcome the times that you will be wrong or a Leeroy event will pop up. No trade is ever 100% certain, but even with pitiful diversification (keeping a 50% cash position is diversification in my book), if the trades you're going after are the ones that you're 90% certain on, and you've tested and matured your ability to know when you can be right and when you can't, the mathematics will take over and you'll be sitting pretty at the end regardless of a few Leeroys throughout your trading career.
I'm almost absolutely certain that I'll get one of these tests soon enough a la NVDA. I'm waiting for it to fall back to its strength. When it gets there, I'll show a prediciton and we can watch it play out.
These bones were burried for future generations to dig them up and hawk as a miracle ingredient in traditional Chinese medacine. And they were called:
Dragon Bones!
Well, thousands of years later, and perhaps not yet too much brighter, here we are divining buy and sell signals from the stock market. There are websites hawking advice, possibly mafia gimmicks, and maybe tried and traitorous buy-and-hold tonic.
If you've been keeping up with my posts, you should have a decent feel by now for the concept of limited determinism. The rugby pile at the knife edge on the beach head in the bar room full of singles who want to be first, but don't want to be desperate. The chaotic cow that has absolute authority to vanquish the magician back into the realm of his game. The magician and Leeroy Jenkens battling it out unceasingly inside the circus tent that flows withing the chaotic probability zone.
What I'm really getting at is that there are places where the stock market's movements are absolutely limited by the price elasticity --- as well as places where bar room politics and magicians tricks and cameo appearences by Leeroy take over.
I have tried numerous times and many ways to figure out the correct analogy for how to make use of the serendiptitious patterns that emerge from the chaos whenever the stock market is trading well within the realm of price-elasticity, the places where limited determinism is more like conditional determinism, which is a paradox in itself.
The technical patterns, Leeroy effects, and magic shows are fun to watch. Inevitably there is a contention point, and that contention point will lead to the development of a new pattern, a new trend, a new wave to ride on. The capability of the wave to sustain itself is many times, by virtue of being well within the chaotic trading range, purely up to the surrounding chaos, which was itself decided in a nearly arbitrary fashion and wholly lacking of discernable sense to the average Vulcan.
In the end, the chaotic movements of the stock market are in so many ways just like the dragon bones. The charts almost even look like the cracks as they split through the dragon bones. How can this completely unreliable process provide any opportunities to make rational trading decisions at all? I give you my final answer:
The shape of each crack is arbitrary
The existence of cracks is absolute
What I mean by this is that you don't have to find meaning in the cracks, but never for a second think that just because there is no higher order that you can afford to ignore them.
And this is how the emporer rolls. Yes, the months and weeks leading up to a contention point should theoretically have no impact on the prices traders are willing to buy and sell shares at. At the contention point, the fact that the knife can fall either way would seem to suggest that there is no significance to the result. The cracks could have gone North and South or East and West and the old man still would have given his answer to the emporer just as if there was some greater meaning to it. The emporer's word is final. The follow-through of his beauracracy is like wise absolute. The follow through of the stock-market is no different.
When trading in the chaotic regions, try to spot the serendipity. Say not, "the stock will trade this way," but "if the stock trades this way, it would be likely to follow through this way." Then once the knife falls, if it falls in such a way that you think it has momentum and the blessing of the chaotic cow (it's well towards the middle of its price-elasticity curve) ride the storm until the next contention point. Better yet, if the pattern is stable, wait for the pattern's reinforcing signal, whether it's a linear uptrend or a moving daily average, and then make your move.
When dealing with a pattern that has room to run, it tends to do just that. That tendancy is strong enough to overcome the times that you will be wrong or a Leeroy event will pop up. No trade is ever 100% certain, but even with pitiful diversification (keeping a 50% cash position is diversification in my book), if the trades you're going after are the ones that you're 90% certain on, and you've tested and matured your ability to know when you can be right and when you can't, the mathematics will take over and you'll be sitting pretty at the end regardless of a few Leeroys throughout your trading career.
I'm almost absolutely certain that I'll get one of these tests soon enough a la NVDA. I'm waiting for it to fall back to its strength. When it gets there, I'll show a prediciton and we can watch it play out.
Thursday, July 30, 2009
Circus Tent in Outer Space
The last post introduced the concept of the magician, an aggregate representation of all types of induced feedback in the market. At this point, there are two distinct mechanisms of feedback in the market. The first arises from technical analysis. The second is born from the capability to steer technical patterns with subtle nudges at the right points of instability. Both have their limits, and that's the focus of the post today.
The magician (apologize for lack of an illustrative introduction) uses induced feedback. Induced feedback is feedback that has been triggered by creating the right input signal to cause the system to enter a particular state of self-propagation via simpler feedback mechanisms. Imagine a school bus full of children who are shifting their weight in order to rock the bus. By feeling the movement of the bus and using this to decide when and how much to shift their weight, the children are a simple feedback mechanism. They feed back one signal (the bus is rocking) to create another signal (rock more/less). Induced feedback was what happened when one kid got up, started rocking, and encouraged some of his friends. After the thing was rocking and it was widely perceived as fun, the storm was already in motion.
The magician in the stock market is no different. By utilizing the right stimulation to the right trading pattern, the magician has a butterfly on the end of his wand that creates a tornado. The cost of achieving these tornadoes is very low relative to the storms that are created, which continue to build through their own mechanisms in the absence of further capital input. The magician reaps the benefits. However, there are two limitations to the magicians capabilities:
What goes on inside the chaotic boundary regions can be likened to a circus. Complete with a ring leader, lots of people shouting, and no real method to the madness except whenever the chaotic meanderings take clear form and feedback drives them in one direction or the other. Outside the circus, whatever went on inside the circus is no longer important. The feedback mechanisms are dominated by external influences that cannot be affected outside the tent. Faced with the cold reality that the circus games can only last from one side of the tent to the other, the crowds and performers head back into the tent. The magician, having driven the show outside the tent himself, stays inside the ring and charges admission for all returning.
The clouds of chaos float just behind the curtains on the stage. The magician has his tricks. The audience gets to clap, but outside the stage the show is over, and our mystery superhero, the chaotic cow, keeps the show in check. Why do I cast the cow in a positive light? You can make money off the magician. You can make money off the cow. You can predict the movements of the cow. You can't predict the movements of the magician. The timing when stocks will move off the stage is much less certain than when they will get moved back on the stage. Follow the beef.
Illustrations on their way, but I want to keep moving through the material and doing a good illustration can take a good chunk of time.
The magician (apologize for lack of an illustrative introduction) uses induced feedback. Induced feedback is feedback that has been triggered by creating the right input signal to cause the system to enter a particular state of self-propagation via simpler feedback mechanisms. Imagine a school bus full of children who are shifting their weight in order to rock the bus. By feeling the movement of the bus and using this to decide when and how much to shift their weight, the children are a simple feedback mechanism. They feed back one signal (the bus is rocking) to create another signal (rock more/less). Induced feedback was what happened when one kid got up, started rocking, and encouraged some of his friends. After the thing was rocking and it was widely perceived as fun, the storm was already in motion.
The magician in the stock market is no different. By utilizing the right stimulation to the right trading pattern, the magician has a butterfly on the end of his wand that creates a tornado. The cost of achieving these tornadoes is very low relative to the storms that are created, which continue to build through their own mechanisms in the absence of further capital input. The magician reaps the benefits. However, there are two limitations to the magicians capabilities:
- In the absence of any susceptible patterns, the magician's actions are distorted in the haze, and it costs more to create a self-propagating pattern. The profit potential is less and the stability of the resulting signal can be affected.
- Mechanisms unrelated to feedback cycles cannot be controlled by induced feedback. Unrelated influences are noise to the magician, costing him more to manifest signal stability and causing the patterns he creates to dissipate rapidly.
What goes on inside the chaotic boundary regions can be likened to a circus. Complete with a ring leader, lots of people shouting, and no real method to the madness except whenever the chaotic meanderings take clear form and feedback drives them in one direction or the other. Outside the circus, whatever went on inside the circus is no longer important. The feedback mechanisms are dominated by external influences that cannot be affected outside the tent. Faced with the cold reality that the circus games can only last from one side of the tent to the other, the crowds and performers head back into the tent. The magician, having driven the show outside the tent himself, stays inside the ring and charges admission for all returning.
The clouds of chaos float just behind the curtains on the stage. The magician has his tricks. The audience gets to clap, but outside the stage the show is over, and our mystery superhero, the chaotic cow, keeps the show in check. Why do I cast the cow in a positive light? You can make money off the magician. You can make money off the cow. You can predict the movements of the cow. You can't predict the movements of the magician. The timing when stocks will move off the stage is much less certain than when they will get moved back on the stage. Follow the beef.
Illustrations on their way, but I want to keep moving through the material and doing a good illustration can take a good chunk of time.
Wednesday, July 29, 2009
The Magician
This post will explain probably the most influential mechanism of stock manipulation. Long before anyone would have written the control function for the stock market or created the necessary neural network or other algorithm(s) needed to calibrate the behavior of a sci-fi trading computer, it was recognized by many that the stock market is just as fickle as public opinion would be if we had hundreds of simultaneous presidential elections going on. We try, through appreciation of human accomplishments won through logical faculty, to make rational evaluations of trading opportunities, but inevitably our social mechanics and primal nature filter in. Just like pundits and anyone with anything to gain in the political world, there are always players spinning their wheels cloak-and-dagger style, behind the cape of uncertainty and faith in the general legitimacy of society, working hard to push the right buttons at the right time to get the herd moving in some direction they can capitalize on. Collectively, this influence can be represented as the arch-rival of the chaotic cow, the magician.
Let's start with a brief introduction to social behavior. Assume you want something and recognize that lots of other people want the same thing. A viable strategy is to identify whoever looks like a strong player and follow their lead. Apply the reasoning to a cave man scenario. While on the day's group hunt, you and your party are slowly creeping up on [insert large tasty dangerous animal]. Suddenly, one of you raises up and starts running at one of the creatures. The signal hadn't been given. The guy is breaking consensus. Do you
A) rush in with him?
B) hold back, tie him to a tree after he's scared the prey off, and try again one short?
What if the guy doesn't look like your above-average hunter? Is he probably out on a limb for his ability? Now, suppose the guy is well regarded as an expert at pre-emptive cave/kung-fu. Even though the leader might not have seen the opportunity, you generally expect that this guy does. In the first case, you probably don't follow. In the second, you probably do.
Back to financial markets, are there any arenas where the elite players and gamblers mix? The answer is yes. Instruments with elevated risk and reward exist in the form of derivatives, namely stock options and futures. Stock options essentially allow you to buy the profit potential, short or long, in exchange for risk. Stock options only have a certain window of time available within which that profit can be won. This has a price, known as the time premium. Futures operate much the same way. Increased risk, increased return. Because these instruments are very volatile and dangerous, it's usually expected that big plays in the derivatives markets are made by expert players showing their hands. The reasoning is that bad plays go south, so bad players go bankrupt or get out fast.
Now, lets say that the you're a major institution or large investor and you feel/determine that there is a little bit of a wound up spring in the market if a technical pattern builds at a certain point, and you want to capitalize on that movement. You could A) get lucky or B) shove the rugby pile with a large play. Since everyone is always watching the market, all plays are visible, and one of the places that gathers a lot of attention is derivatives. A frivolous move on the derivatives market will become very costly very quickly, but making a very aggressive play that shows up in the derivatives markets is easy. The market sizes are small and the reactionary trading habits are greatly amplified. The feedback happens so fast that you can ping the spread with a single order and suddenly watch the market readjust like hyenas in a flinch-fight. One order, and the whole thing starts rearranging.
Because frivolous plays are costly, it's expected that frivolous derivatives exchanges don't happen to a large degree. However, if you're a well capitalized trader with a large position in a stock, that frivolous trade becomes cheap, and then you send the whole pack of hyenas mad in one direction. Better yet, just like our pre-historic cave hunters, the regular traders will pick up on the unusually activity of the "experts" and follow suit. If the move was made at an appropriately susceptible position, then the flurry of activity will probably be enough to push the needle over, and lo and behold the market will go in that direction, with full technical support.
This is the power of the magician. In between the boundaries of chaos, the chaotic cow is powerless, disorganized, and fickle. The magician is calculated, precise, and utilizes the emerging patterns in disorganized chaos to create self-propagating movements through technicals. How often does this happen? Ask Jim Cramer. This link goes to an interview that also aired on John Stewart's infamous clash with the poor Cramer.
The next post (barring another market update) will focus on the limited influence of the magician. Possibly an illustrated guide to the struggle that brews between the cow and the magician. Get on my RSS to be sure and catch it.
Let's start with a brief introduction to social behavior. Assume you want something and recognize that lots of other people want the same thing. A viable strategy is to identify whoever looks like a strong player and follow their lead. Apply the reasoning to a cave man scenario. While on the day's group hunt, you and your party are slowly creeping up on [insert large tasty dangerous animal]. Suddenly, one of you raises up and starts running at one of the creatures. The signal hadn't been given. The guy is breaking consensus. Do you
A) rush in with him?
B) hold back, tie him to a tree after he's scared the prey off, and try again one short?
What if the guy doesn't look like your above-average hunter? Is he probably out on a limb for his ability? Now, suppose the guy is well regarded as an expert at pre-emptive cave/kung-fu. Even though the leader might not have seen the opportunity, you generally expect that this guy does. In the first case, you probably don't follow. In the second, you probably do.
Back to financial markets, are there any arenas where the elite players and gamblers mix? The answer is yes. Instruments with elevated risk and reward exist in the form of derivatives, namely stock options and futures. Stock options essentially allow you to buy the profit potential, short or long, in exchange for risk. Stock options only have a certain window of time available within which that profit can be won. This has a price, known as the time premium. Futures operate much the same way. Increased risk, increased return. Because these instruments are very volatile and dangerous, it's usually expected that big plays in the derivatives markets are made by expert players showing their hands. The reasoning is that bad plays go south, so bad players go bankrupt or get out fast.
Now, lets say that the you're a major institution or large investor and you feel/determine that there is a little bit of a wound up spring in the market if a technical pattern builds at a certain point, and you want to capitalize on that movement. You could A) get lucky or B) shove the rugby pile with a large play. Since everyone is always watching the market, all plays are visible, and one of the places that gathers a lot of attention is derivatives. A frivolous move on the derivatives market will become very costly very quickly, but making a very aggressive play that shows up in the derivatives markets is easy. The market sizes are small and the reactionary trading habits are greatly amplified. The feedback happens so fast that you can ping the spread with a single order and suddenly watch the market readjust like hyenas in a flinch-fight. One order, and the whole thing starts rearranging.
Because frivolous plays are costly, it's expected that frivolous derivatives exchanges don't happen to a large degree. However, if you're a well capitalized trader with a large position in a stock, that frivolous trade becomes cheap, and then you send the whole pack of hyenas mad in one direction. Better yet, just like our pre-historic cave hunters, the regular traders will pick up on the unusually activity of the "experts" and follow suit. If the move was made at an appropriately susceptible position, then the flurry of activity will probably be enough to push the needle over, and lo and behold the market will go in that direction, with full technical support.
This is the power of the magician. In between the boundaries of chaos, the chaotic cow is powerless, disorganized, and fickle. The magician is calculated, precise, and utilizes the emerging patterns in disorganized chaos to create self-propagating movements through technicals. How often does this happen? Ask Jim Cramer. This link goes to an interview that also aired on John Stewart's infamous clash with the poor Cramer.
The next post (barring another market update) will focus on the limited influence of the magician. Possibly an illustrated guide to the struggle that brews between the cow and the magician. Get on my RSS to be sure and catch it.
Monday, July 27, 2009
Falling Off the Blade
This post will focus on the recent technical contention point of the broader US market and the influences that have guided what will become the new trend. Several trends were involved, some of which will emerge as the new trends for the time being. If you interpret charts enough, you can usually always find a downtrend and an uptrend. When the two connect, it's a technical paradox, with signals going both ways. It's an unstable equalibrium. Sometimes it's like a tennis ball on a hill. Sometimes it's like a needle balanced on a knife, with the slightest input causing the system to diverge decisively towards one solution. This was one of those needle on a knife moments, and this post will discuss what to do with it.
In the abscence of new economic data, it's a battle between two self-sustaining patterns, exactly like two storms colliding. The more organized flow, usually the more established trend, will usually win. In this case, we have new economic data, lots of new economic data. In fact, there's so much economic data that the dominating mechanic is unmistakably fundamentals.
The needle on the knife was a well established downtrend going back a little less than a decade. The beginning was so long ago that I remember a professor of mine using the word "megatrend." The big picture consists of the rise of oil consuming India and China (US consumption is figuratively a tautology), the Iraq war, the tech crunch, and the general doom and gloom of terrorist hysteria. All of these factors put dampers on the US economy via various mechanisms. Let's take a moment to reflect. Every great once in a while I pull out bigcharts.com when I need...big charts.
Here you have it, the history of the universe for the last thirty years. Roaring 90's, y2k bubble pop, 2001, and finally the housing bubble-bust. Notice how the first two decades of this chart show a readily identifiable curve? Then in the 90's, suddenly things went ape. In 2001 we reconnected with a "curvy" interpretation of the previous trend. Right now we're connecting with a linear interpretation of the previous trend. This is all art of course, but remember that the mechanisms of simple trends are mostly psychological, meaning that as humans who share similar psychology, we're already perfect indicators of how we visually process charts. If you've ever taken a class in trig or calculus, you have every tool necessary to be a curve fitting artist.
The last feature to pay attention to in that chart is the almost unbroken downtrend starting in 2001. What broke it? The housing and derivatives trading bubble. Bubbles pop, and in short, since reality brought the trend back in line, there was a good chance that it was still a dominant economic mechanic.
Now let's break out the microscope and look at this recent contention point:
The big question for this recovery rally from the bottom was whether to consolidate again at the bottom, letting the down trend make another run, or to have a summer rally now that the sky isn't falling. We hit that 200day moving average and almost started to head back South, but then the economic data hit and most of it indicated that the sky is in fact still well overhead. This was the wind that blew the needle off the blade, and now it's falling towards the North.
The DJIA will undoubtedly make a run back to the 50day after earnings are over. Profit taking after the flow of news slows down. At that point, the trend will take over. I would look to build positions as the earnings sink in. Any downward movement here is a buying opportunity for the summer. Pick long stocks and play their technical trends using the 20-day exponential moving average or whatever trend indicator is being consistent for that stock (more on this later.)
Short plays are a bad idea in an up market. If you're not sure the company's bankruptcy is going to happen in the next three months, look at this upward movement as the potential building of a bubble. It's frustrating to try to play a stock short that's being propped up by market movements. The simple truth is that long plays will get help from the market, so any short play is trading upstream.
What does this mean for me? I'm letting go of AMD for the time being. Yes the earnings were terrible and foreshadow the chronic failure to execute that has plagued the company, but they have enough cash to go for at the very worst several quarters, so the clouds of chaos aren't yet there.
What am I doing instead? NVDA. There's a trading gap at $14 that represents a large technical leap. NVDA is a great company with a great future. I'm sure I'll write more on this before the end of the week to give you some perspective on how I make these calls, but in the end what I'm doing is taking advantage of a stock that has a wound up technical spring and market that's poised to set that spring loose.
In the abscence of new economic data, it's a battle between two self-sustaining patterns, exactly like two storms colliding. The more organized flow, usually the more established trend, will usually win. In this case, we have new economic data, lots of new economic data. In fact, there's so much economic data that the dominating mechanic is unmistakably fundamentals.
The needle on the knife was a well established downtrend going back a little less than a decade. The beginning was so long ago that I remember a professor of mine using the word "megatrend." The big picture consists of the rise of oil consuming India and China (US consumption is figuratively a tautology), the Iraq war, the tech crunch, and the general doom and gloom of terrorist hysteria. All of these factors put dampers on the US economy via various mechanisms. Let's take a moment to reflect. Every great once in a while I pull out bigcharts.com when I need...big charts.
Here you have it, the history of the universe for the last thirty years. Roaring 90's, y2k bubble pop, 2001, and finally the housing bubble-bust. Notice how the first two decades of this chart show a readily identifiable curve? Then in the 90's, suddenly things went ape. In 2001 we reconnected with a "curvy" interpretation of the previous trend. Right now we're connecting with a linear interpretation of the previous trend. This is all art of course, but remember that the mechanisms of simple trends are mostly psychological, meaning that as humans who share similar psychology, we're already perfect indicators of how we visually process charts. If you've ever taken a class in trig or calculus, you have every tool necessary to be a curve fitting artist.
The last feature to pay attention to in that chart is the almost unbroken downtrend starting in 2001. What broke it? The housing and derivatives trading bubble. Bubbles pop, and in short, since reality brought the trend back in line, there was a good chance that it was still a dominant economic mechanic.
Now let's break out the microscope and look at this recent contention point:
The big question for this recovery rally from the bottom was whether to consolidate again at the bottom, letting the down trend make another run, or to have a summer rally now that the sky isn't falling. We hit that 200day moving average and almost started to head back South, but then the economic data hit and most of it indicated that the sky is in fact still well overhead. This was the wind that blew the needle off the blade, and now it's falling towards the North.
What to Do With It?
The DJIA will undoubtedly make a run back to the 50day after earnings are over. Profit taking after the flow of news slows down. At that point, the trend will take over. I would look to build positions as the earnings sink in. Any downward movement here is a buying opportunity for the summer. Pick long stocks and play their technical trends using the 20-day exponential moving average or whatever trend indicator is being consistent for that stock (more on this later.)
Short plays are a bad idea in an up market. If you're not sure the company's bankruptcy is going to happen in the next three months, look at this upward movement as the potential building of a bubble. It's frustrating to try to play a stock short that's being propped up by market movements. The simple truth is that long plays will get help from the market, so any short play is trading upstream.
What does this mean for me? I'm letting go of AMD for the time being. Yes the earnings were terrible and foreshadow the chronic failure to execute that has plagued the company, but they have enough cash to go for at the very worst several quarters, so the clouds of chaos aren't yet there.
What am I doing instead? NVDA. There's a trading gap at $14 that represents a large technical leap. NVDA is a great company with a great future. I'm sure I'll write more on this before the end of the week to give you some perspective on how I make these calls, but in the end what I'm doing is taking advantage of a stock that has a wound up technical spring and market that's poised to set that spring loose.
Ponder This
What a coincidence that the technical contention occured right around the same time as earnings. What a conincidence that most stocks' charts that I'm watching showed this same type of contention at about the same time. What another coincidence that the down megatrend occured around a huge spike in trading volume.
Computer trading started in the 80's and was driven simply by the emergence of the technology. What could have lead to the need for so much more trading activity? Let's say you're a major fund manager and you realize that the megatrend has meat in it and that investing long isn't going to pay well. What do you do? Play volume, derivatives, arbitrage, and market smoke and mirrors to take advantage of every move that occurs in the relative market stagnation.
Notice that the volume was about a billion shares per day and was fairly consistent over the last decade. Notice how it started directly coincident with the tech crunch. No, this isn't a conspiracy theory. Don't read into this line of thought too much, but I will go ahead and suggest that there was a recognized need for large trading establishments and hedge funds to generate profit from trading in the relative shortage of investable stocks.
What makes this line of thinking consistent is that the trading activity didn't continue to grow, suggesting that market fees and other limitations put a hard cap on how much profit could be squeezed out of this type of trading. Or perhaps there is an overlay of two conflicting trends. Either way, the volume spike and subsequent stagnation starting in 2000 is a little curious and I'll get back to this before the end of summer.
Computer trading started in the 80's and was driven simply by the emergence of the technology. What could have lead to the need for so much more trading activity? Let's say you're a major fund manager and you realize that the megatrend has meat in it and that investing long isn't going to pay well. What do you do? Play volume, derivatives, arbitrage, and market smoke and mirrors to take advantage of every move that occurs in the relative market stagnation.
Notice that the volume was about a billion shares per day and was fairly consistent over the last decade. Notice how it started directly coincident with the tech crunch. No, this isn't a conspiracy theory. Don't read into this line of thought too much, but I will go ahead and suggest that there was a recognized need for large trading establishments and hedge funds to generate profit from trading in the relative shortage of investable stocks.
What makes this line of thinking consistent is that the trading activity didn't continue to grow, suggesting that market fees and other limitations put a hard cap on how much profit could be squeezed out of this type of trading. Or perhaps there is an overlay of two conflicting trends. Either way, the volume spike and subsequent stagnation starting in 2000 is a little curious and I'll get back to this before the end of summer.
Wednesday, July 15, 2009
Leeroy Alert
Today we have a good example of how a minor Leeroy event can threaten to completely change the stable pattern that was forming. Earnings season is very prone to Leeroy popping up, and this is why I prefer the quieter months of the year. Earnings is when excessive divergences from reality get reined in and loose ends in the minds of investors get tied up somewhat. As a whole we will correct our worst mistakes and decide where to go in the future. Well, that sounds very egalitarian, but let's focus on putting trading dollars to work.
The event I'm going to highlight is the Intel earnings report. I'm pretty sure that they beat. I'm not particularly concerned with the details. Yes, I know. Just leaving nice, solid information out on the clothes line to get bleached in the sun. But the truth is that I have my eye on a bigger ball. Within this cycle of earnings, the Dow and several individual stocks I'm watching will all be decided. What I mean is that we're on the cusp of the technical patterns diverging either north or south. A 5% move this week will probably turn into a 30% move in the next month. Check out what this little pop has done to the Dow's chart:
The Dow is unquestionably running into a well established downtrend and the only question is whether it's going to head south to consolidate the bottom or break out for a summer rally. There's always the possibility of stagnation, but doldrums neither lose or make money, so I'm typically focused on identifying the divergent behavior even if stagnation takes hold. In the previous article, it was looking pretty set in stone that traders would respond to that echo resonating in the 200-day moving average and take the market south. This one day of upbeat earnings has pushed north of the 200-day, and now we're left with a much more exciting picture. It could break either way. I say that not because the stock has simply crossed the line, but has done so on the back of plausible evidence that the economy is doing alright.
Back to AMD, we're seeing that the 20-day exponential moving average has been broken. I'm going to fast forward given what I know about AMD. The investors who follow AMD are the most rabid, underdog loving, cinderella buying lot on Earth. INTC just put out a positive earnings report. This usually bodes well for AMD stock. I'm going out on a limb to predict that without some contradicting earnings report from somewhere else in the sector, the AMD dead cat will bounce one last time. Although they're bleeding less on the income statement, note that this is only because the fab operation has been spun off. Just like the flash operation, AMD's partial stake of 44% in the fab will continue to dog them one way or another.
I'm keeping an eye on AMD and NVDA. Short AMD. Long NVDA. Depending on how they break, I'll be looking for one of them to develop into a nice profitable trade. I'm going to do a little bit of research into AMD's chips before the 20th, when AMD's earnings come out. It doesn't take a rocket scientist at this point to determine whether AMD can survive or not. Chips tend to be make or break products, with most of the money concentrated in the ability to earn the performance premium across you product line. Flagship chip prices are very telling as to how well a company is doing this. If AMD can't gain this premium, they will never return to enough profitability to have even a slight chance of paying down their massive debt and getting back in the black on the balance sheet.
The important thing to take home from this Leeroy upset is that stocks are very sensitive at the breaking point. Minor disturbances can take something that was stable and make it start diverging one way or the other. Focus on the medium-term outcomes that will result from the short term chaos. Once the pattern starts to stabalize, if it is founded in at the very least trader hope and confidence, it will usually go on to develop a solid upshot or breakdown depending on the circumstances.
The Leeroy watch has begun.
The event I'm going to highlight is the Intel earnings report. I'm pretty sure that they beat. I'm not particularly concerned with the details. Yes, I know. Just leaving nice, solid information out on the clothes line to get bleached in the sun. But the truth is that I have my eye on a bigger ball. Within this cycle of earnings, the Dow and several individual stocks I'm watching will all be decided. What I mean is that we're on the cusp of the technical patterns diverging either north or south. A 5% move this week will probably turn into a 30% move in the next month. Check out what this little pop has done to the Dow's chart:
The Dow is unquestionably running into a well established downtrend and the only question is whether it's going to head south to consolidate the bottom or break out for a summer rally. There's always the possibility of stagnation, but doldrums neither lose or make money, so I'm typically focused on identifying the divergent behavior even if stagnation takes hold. In the previous article, it was looking pretty set in stone that traders would respond to that echo resonating in the 200-day moving average and take the market south. This one day of upbeat earnings has pushed north of the 200-day, and now we're left with a much more exciting picture. It could break either way. I say that not because the stock has simply crossed the line, but has done so on the back of plausible evidence that the economy is doing alright.
Back to AMD, we're seeing that the 20-day exponential moving average has been broken. I'm going to fast forward given what I know about AMD. The investors who follow AMD are the most rabid, underdog loving, cinderella buying lot on Earth. INTC just put out a positive earnings report. This usually bodes well for AMD stock. I'm going out on a limb to predict that without some contradicting earnings report from somewhere else in the sector, the AMD dead cat will bounce one last time. Although they're bleeding less on the income statement, note that this is only because the fab operation has been spun off. Just like the flash operation, AMD's partial stake of 44% in the fab will continue to dog them one way or another.
I'm keeping an eye on AMD and NVDA. Short AMD. Long NVDA. Depending on how they break, I'll be looking for one of them to develop into a nice profitable trade. I'm going to do a little bit of research into AMD's chips before the 20th, when AMD's earnings come out. It doesn't take a rocket scientist at this point to determine whether AMD can survive or not. Chips tend to be make or break products, with most of the money concentrated in the ability to earn the performance premium across you product line. Flagship chip prices are very telling as to how well a company is doing this. If AMD can't gain this premium, they will never return to enough profitability to have even a slight chance of paying down their massive debt and getting back in the black on the balance sheet.
The important thing to take home from this Leeroy upset is that stocks are very sensitive at the breaking point. Minor disturbances can take something that was stable and make it start diverging one way or the other. Focus on the medium-term outcomes that will result from the short term chaos. Once the pattern starts to stabalize, if it is founded in at the very least trader hope and confidence, it will usually go on to develop a solid upshot or breakdown depending on the circumstances.
The Leeroy watch has begun.
Tuesday, July 7, 2009
Find Yourself a Hammock
I've been more stagnant than I want to be with regard to writing the blog, and I swore I didn't want to start making recommendations, but for one this is one of those situations I can't help but get excited about and second it's a good opportunity to start delving into -drumroll- applied theory.Basically what you're looking at is the bottom of the recent crash and the recovery stalling at the first major resistance test. I'm going to go on my experience and say we're looking at the first indications of some major summer doldrums during which the bottom will be solidified as the market continues to weigh the impact of recent events on back-half seasonal profitability as well as long-term profitability. If Dow 7000 roles around again, I'll be about as surprised as I am about seeing a hurricane on the Weather Channel.
The second exhibit is one of my favorite trading stocks in one of my most favorite situations: the pointless breakout in an unfavorable market. In short, since I'm short on the market, the fact that I'm short on AMD has insurance. It will take more than just a minor Leeroy event to derail this breakdown. AMD, during most of its ascent and breakout, demonstrated what you call "weak buying," where the stock is bleeding a lot of red even as it trades higher, indicating that there is a lot of selling into the springback off the bottom. Basically it's a dead cat bounce that created an opportunity to dump shares, and now the bouncing dead cat is headed back to the ground.
I'll continue to revisit these two examples as I move forward into the conclusions of my model. I'm feeling pretty certain at this point I want to go back and re-approach some of the material. I've had a decent time getting my head around the material in the context of writing the book, so a little reorganization seems more than appropriate.
Good luck trading.
Tuesday, June 2, 2009
Cold War
In the last post it was proposed how to model a computer trading system that would be capable of analyzing the behavior of all participants in the stock market, calibrating its own predictions, and making trades accordingly. Now we'll see the reasons why this method introduces yet more exotic behavior into the stock market, making it difficult to realize the profit that would otherwise be expected.
The first reason is simply the presence of intermittent trades with effectively random timing from the perspective of the software. The Leeroy Jenkins effect is most powerful against weak patterns. Stronger, more self-sustaining patterns will require a larger Leeroy event to upset.
Secondly, there are news events in the future that are effectively random. The initial impact will be beyond the design of such a system. Only after it receives new data that can measure the reaction amongst fundamental investors can the system recalibrate itself to meet the changing conditions.
Less importantly, the model written in the last post makes some assumptions. One is that traders continue using the same tools over and over again and that the popularity of indicators changes at a slow pace relative to trading regimes.
A very dangerous assumptions is that no other computer systems with unknown behavior and unknown influence on the stock price. In reality there are many such systems, and by getting a step ahead, all that happens is a new type of feedback in introduced. Since none of the computers know precisely what the others model is or what the trading implementation is, effectively all computer trading systems are tied up in a constant poker game. Dead reckoning and playing the cards right (from a programming perspective) might still be, on the whole, a reliable strategy, but the notion of predicting, much less controlling the stock market at the most granular levels to create wide-reaching patterns is far fetched.
Essentially, the picture of the stock market is shaping up to be a bit like a system of springs, weights, and dampers, with some of the springs trying to consciously understand the system, but because the knowledge of the system and interaction with it changes the spring, and thereby the system, this consciousness is always just out of reach. In short it's impossible to predict the chaotic dynamics of the market when characterization thereof influences participation, changing the system at its most fundamental level, trades and traders.
The first reason is simply the presence of intermittent trades with effectively random timing from the perspective of the software. The Leeroy Jenkins effect is most powerful against weak patterns. Stronger, more self-sustaining patterns will require a larger Leeroy event to upset.
Secondly, there are news events in the future that are effectively random. The initial impact will be beyond the design of such a system. Only after it receives new data that can measure the reaction amongst fundamental investors can the system recalibrate itself to meet the changing conditions.
Less importantly, the model written in the last post makes some assumptions. One is that traders continue using the same tools over and over again and that the popularity of indicators changes at a slow pace relative to trading regimes.
A very dangerous assumptions is that no other computer systems with unknown behavior and unknown influence on the stock price. In reality there are many such systems, and by getting a step ahead, all that happens is a new type of feedback in introduced. Since none of the computers know precisely what the others model is or what the trading implementation is, effectively all computer trading systems are tied up in a constant poker game. Dead reckoning and playing the cards right (from a programming perspective) might still be, on the whole, a reliable strategy, but the notion of predicting, much less controlling the stock market at the most granular levels to create wide-reaching patterns is far fetched.
Essentially, the picture of the stock market is shaping up to be a bit like a system of springs, weights, and dampers, with some of the springs trying to consciously understand the system, but because the knowledge of the system and interaction with it changes the spring, and thereby the system, this consciousness is always just out of reach. In short it's impossible to predict the chaotic dynamics of the market when characterization thereof influences participation, changing the system at its most fundamental level, trades and traders.
Wednesday, May 27, 2009
If I Were a Computer
If there was a several hundred billion dollar capital fund and you were charged with investing it, you would hire the smartest people you could get your hands on, provide them with a relatively insane budget, and give them huge incentives to perform. Even with a lot of bright people who can easily employ fundamental analysis and technical analysis to make a lot of money, the tendency will still be to try and get ahead of the game. After all, who gets paid to invest several hundred billion dollars with primitive tools used by any multi-billion dollar hedge fund manager? If you were paid to be one of these people, three tools would be made available to you with no expense spared: The best financial market data that can be purchased, every research report written, and a really big computer along with some programmers and engineers to help you run it.
The details of this post are rather daunting. You don't need to understand them down to the gory details in order to see the points of this exercise. Focus on the notions that are implied simply by alluding to the mathematics rather than the actual content of mentioned formulas.
What you're looking at is called a control diagram. Whenever there's a really big system with lots of feedback response that need to be modeled, engineers will draw up a control diagram and use it to write the equations of the system. Looking at that big column of blocks with the arrows going in a circle, does something seem familiar? (This illustration is from Covert Newspaper Interception.)
Here's a brief rundown of the diagram:
It gets better. The task of figuring out how influential technicals and fundamentals are is readily taken care of by the use of empirical constants k1, k2, k3...kn, and multiplying the indicator by this constant, or even a simple empirical formula, all while remaining well within the reach of the computational power of a simple desktop computer.
How is this possible? Well, let's imagine that a set of n traders with mi capital are watching a particular indicator of a particular stock, and that each individual trader is influenced in some arbitrary amount by that indicator. The weight for each individual trader is just some constant factor, like 0.10 for instance or maybe 0.40 if a trader really likes a certain indicator. The summation of all of these traders, weighted by their individual incomes and sensitivity to the indicator, is just a constant times that indicator. One simple number multiplied by one other number can, to a very large degree, represent the aggregate trading influence of the movements of a particular indicator.
In a nutshell, that last paragraph says that you can, to a sufficient degree of accuracy, simplify the stock market to be, instead of n traders with n wallets and n propensities to trade because of a particular indicator, just one big trader with a big wallet and a wallet-weighted average propensity (wallet-weighted average since the amount of money a trader has influences how much their propensity gets expressed in the aggregate).
If you do this for every single indicator imaginable, you can represent the entire feedback portion of the stock market as one gigantic, linear function. Solving for these k constants isn't easy just yet. And we still have to decide on how to empirically represent the fundamentals.
To start, let's assume that, by and large, you can hire a group of true-to-the name analysts who have access to enough of the information that their assessment of the value and future earnings of a stock are a reasonably accurate depiction of all traders who are following a stock. They don't have to be supremely accurate since the bulk of traders trade multiple stocks and don't have time to cover every one of those perfectly themselves. The idea is that you want to have some indication with sensitivity to changes in fundamentals that can be tweaked by a constant or simple function. Hiring traders or polling traders to get an idea of what other traders are doing is a perfectly valid course of action. Again, you're making a reasonable assumption that n traders with n models and n data sets can be approximated as one average trader who used a plausibly average data set and a plausibly average financial model. The accuracy of this approximation is again not that important. That your panel of analysts behaves for the most part just like real traders is all that's important.
Now, we could be heroes and plug and chug these constants all day until the model starts working, or we could just throw the thing into what's called an artificial neural network. It's just a neat type of software that is very good at signal analysis and recognizing patterns in data. It would simply tweak the constants until the model, at any given time in the past, predicted any other time after that with the highest accuracy. The result won't be perfect, but what will eventually get spat out on the other end is a set of these k constants that makes the model the most in line with the data. Not only that, using statistical analysis it would be possible to estimate the accuracy of future predictions, so the software could tell you the best times to pay attention to the result.
And it gets better still. By controlling feedback, a sufficiently large fund could create feedback cycles that would be stable enough to absorb the fund's own trades, and they have absolutely every reason in the world to do so. It's conceivably possible that maximizing the return on investment for such a fund might even involve calculating which feedback cycles to generate at which points in order to maximize the total amount of the fund's own trading activity that the market volatility could accommodate. Given the size of some overgrown funds, once more it can't be more obvious that they in fact have every reason in the world to do so.
This post has cleared the stage for the dark side of the stock market. Get ready to feel more skeptical of the market as a whole than your used to. At the same time, rest assured that you can be on a level playing field as long as you let the underlying implications work for you. The posts following this one will almost entirely be focused on this dark side and how to safely navigate it. Consider this the half-way point for this blog.
The details of this post are rather daunting. You don't need to understand them down to the gory details in order to see the points of this exercise. Focus on the notions that are implied simply by alluding to the mathematics rather than the actual content of mentioned formulas.
Now for some plot spoilers:
What you're looking at is called a control diagram. Whenever there's a really big system with lots of feedback response that need to be modeled, engineers will draw up a control diagram and use it to write the equations of the system. Looking at that big column of blocks with the arrows going in a circle, does something seem familiar? (This illustration is from Covert Newspaper Interception.)
Here's a brief rundown of the diagram:
- Emerging financial and economic data (basically any information, including insider information, that will affect the results of fundamental models.) flows in at the far left.
- This data gets processed by fundamental analysts, who are the vector for that data to start affecting the supply and demand for a stock.
- This result flows into the summing junction, which is exactly what it sounds like, just a way of indicating that the arrow coming out of the right side is the sum of everything going in.
- The summed signal goes back into all of the technical analysis branches, which produce new buy and sell signals.
- The result that pops out at the right is dependent on both the recycled data that's already present in the system and the new data that is introduced by fundamental traders.
It gets better. The task of figuring out how influential technicals and fundamentals are is readily taken care of by the use of empirical constants k1, k2, k3...kn, and multiplying the indicator by this constant, or even a simple empirical formula, all while remaining well within the reach of the computational power of a simple desktop computer.
How is this possible? Well, let's imagine that a set of n traders with mi capital are watching a particular indicator of a particular stock, and that each individual trader is influenced in some arbitrary amount by that indicator. The weight for each individual trader is just some constant factor, like 0.10 for instance or maybe 0.40 if a trader really likes a certain indicator. The summation of all of these traders, weighted by their individual incomes and sensitivity to the indicator, is just a constant times that indicator. One simple number multiplied by one other number can, to a very large degree, represent the aggregate trading influence of the movements of a particular indicator.
In a nutshell, that last paragraph says that you can, to a sufficient degree of accuracy, simplify the stock market to be, instead of n traders with n wallets and n propensities to trade because of a particular indicator, just one big trader with a big wallet and a wallet-weighted average propensity (wallet-weighted average since the amount of money a trader has influences how much their propensity gets expressed in the aggregate).If you do this for every single indicator imaginable, you can represent the entire feedback portion of the stock market as one gigantic, linear function. Solving for these k constants isn't easy just yet. And we still have to decide on how to empirically represent the fundamentals.
To start, let's assume that, by and large, you can hire a group of true-to-the name analysts who have access to enough of the information that their assessment of the value and future earnings of a stock are a reasonably accurate depiction of all traders who are following a stock. They don't have to be supremely accurate since the bulk of traders trade multiple stocks and don't have time to cover every one of those perfectly themselves. The idea is that you want to have some indication with sensitivity to changes in fundamentals that can be tweaked by a constant or simple function. Hiring traders or polling traders to get an idea of what other traders are doing is a perfectly valid course of action. Again, you're making a reasonable assumption that n traders with n models and n data sets can be approximated as one average trader who used a plausibly average data set and a plausibly average financial model. The accuracy of this approximation is again not that important. That your panel of analysts behaves for the most part just like real traders is all that's important.
Now, we could be heroes and plug and chug these constants all day until the model starts working, or we could just throw the thing into what's called an artificial neural network. It's just a neat type of software that is very good at signal analysis and recognizing patterns in data. It would simply tweak the constants until the model, at any given time in the past, predicted any other time after that with the highest accuracy. The result won't be perfect, but what will eventually get spat out on the other end is a set of these k constants that makes the model the most in line with the data. Not only that, using statistical analysis it would be possible to estimate the accuracy of future predictions, so the software could tell you the best times to pay attention to the result.
And it gets better still. By controlling feedback, a sufficiently large fund could create feedback cycles that would be stable enough to absorb the fund's own trades, and they have absolutely every reason in the world to do so. It's conceivably possible that maximizing the return on investment for such a fund might even involve calculating which feedback cycles to generate at which points in order to maximize the total amount of the fund's own trading activity that the market volatility could accommodate. Given the size of some overgrown funds, once more it can't be more obvious that they in fact have every reason in the world to do so.
This post has cleared the stage for the dark side of the stock market. Get ready to feel more skeptical of the market as a whole than your used to. At the same time, rest assured that you can be on a level playing field as long as you let the underlying implications work for you. The posts following this one will almost entirely be focused on this dark side and how to safely navigate it. Consider this the half-way point for this blog.
Tuesday, May 26, 2009
Changing Lanes
When navigating the chaos highway, what you quickly realize is that, while the middle of the road can't give you a clear sense of direction, the edges of the asphalt are usually so cut-and-dried that you find yourself neglecting to even imagine what it's like beyond the edge. This can never be made more clear than if you ride a motorcycle. Sure, you have ten feet of margin on either side, so in a way it's like you have all the freedom in the world, but that stops at the curb. If you ever have to get closer than you like, you feel it fast.
The boundaries of the stock market are not hard boundaries. Think of grassy medians. The stock tends to bounce around like a reckless motorcyclist as long as things are more than okay. Wanting to profit from the movements of this motorcyclist, we're tempted to try and hire physicists and mathematicians and work out the equations of motion etc etc. Yet because of the motorcyclists unpredictable whims and even bad driving decisions, this is for the most part guaranteed to be a dead end. The more precisely we try to describe the motorcyclist, the more vulnerable our predictions are to subtle inconsistencies.
But recall the cigarette analogy. We know that the largest divergences are the most rare. We know that the range of expected behavior roughly reflects changes in fundamentals and subsequent shifts in price-elasticity (supply-demand/price relationship). What if the motorcyclist is happily speeding along in the far right lane on a freeway that's taking a sharp left and dropping two lands due to construction. Chaos goes here. If "here" changes because the highway itself is turning too far away for the motorcyclist to do whatever he or she wants, then it's no longer about their whims. With a limited degree of certainty (they can ride in the median if they're crazy) they will follow the road.
The trading price is like a reckless motorcyclist. There's lots of profits and losses to be had in the chaotic meanderings through five lanes of traffic. The reliable profit comes when you see that the motorcyclist has nowhere else to turn. Keep your eye on the biker, but keep a better eye on the road. As a corporation's fundamentals change over time, the region where the stock will trade at also changes over time. The stock price is the most obvious piece of the picture. When you see that the fundamentals that have created the current trading regime are going to break down in some way, good or bad, you know almost without a doubt that the stock is about to be on the move.
The boundaries of the stock market are not hard boundaries. Think of grassy medians. The stock tends to bounce around like a reckless motorcyclist as long as things are more than okay. Wanting to profit from the movements of this motorcyclist, we're tempted to try and hire physicists and mathematicians and work out the equations of motion etc etc. Yet because of the motorcyclists unpredictable whims and even bad driving decisions, this is for the most part guaranteed to be a dead end. The more precisely we try to describe the motorcyclist, the more vulnerable our predictions are to subtle inconsistencies.
But recall the cigarette analogy. We know that the largest divergences are the most rare. We know that the range of expected behavior roughly reflects changes in fundamentals and subsequent shifts in price-elasticity (supply-demand/price relationship). What if the motorcyclist is happily speeding along in the far right lane on a freeway that's taking a sharp left and dropping two lands due to construction. Chaos goes here. If "here" changes because the highway itself is turning too far away for the motorcyclist to do whatever he or she wants, then it's no longer about their whims. With a limited degree of certainty (they can ride in the median if they're crazy) they will follow the road.
The trading price is like a reckless motorcyclist. There's lots of profits and losses to be had in the chaotic meanderings through five lanes of traffic. The reliable profit comes when you see that the motorcyclist has nowhere else to turn. Keep your eye on the biker, but keep a better eye on the road. As a corporation's fundamentals change over time, the region where the stock will trade at also changes over time. The stock price is the most obvious piece of the picture. When you see that the fundamentals that have created the current trading regime are going to break down in some way, good or bad, you know almost without a doubt that the stock is about to be on the move.
Monday, May 25, 2009
Brick by Brick
Probably the most frustrating situation from the perspective of fundamentals is when you find yourself having all of the pieces of the puzzle together and know almost beyond a shadow of a doubt that your prediction about the future value of the company is going to pan out, and yet the stock is slowly meandering towards the inevitable. The easier it is to draw your conclusion, the harder it is to figure out what's keeping investors from jumping all over it. To set this paradox aside, first recall that a stock's fundamentals change over time. The second thing to consider is that fundamental valuations are only driven by breaking news, emerging financial data, and insider information etc, all types of cold hard facts that are known to at least some investors. Check back to Covert Newspaper Interception for a refresh on the subject.
Now, within the large volume of information available that can be used to come up with fundamental evaluations, there are essentially two types of facts:
To look at this another way, every prediction has a time point associated with it. In between now and the time the prediction is targeting, the part of the prediction that is exposed to risk will start off at maximum risk. As time goes by, if nothing negates the prediction, it will become more and more certain. If the time of the prediction target is reached with no contradicting information, the prediction will have become like fact, within the accuracy limits of the initial prediction. People don't pay for risk unless they're playing the lottery. The value in information that is forward looking will be directly proportional to the risk fading out as the potential for large surprises dwindles because of the nearness of the prediction target.
The best example of this is earnings forecasts. A company issues an earnings forecast at the beginning of the quarter. Parts of the forecast will be fully effective on the day of the prediction. Other parts will be forward looking and will take time to fully pan out. As time goes by in the quarter and there are no earnings warnings or revisions, it's usually assumed that the company has hit their target forecast or only slightly performed outside the predicted range. Then earnings are reported. This information is immediately actionable and 100% accurate, excepting gross accounting errors. Hindsight is 20/20. Foresight becomes hindsight in the absence of new information.
Putting all of the information together, all of these facts and predictions will assemble over time. The concrete part of what is known and used to establish fundamental valuations takes shape over time. Only the concrete parts matter. Some of this information is concrete today. Some of it only becomes concrete over time. Brick by brick, the facts that you can bank on come together.
Now, within the large volume of information available that can be used to come up with fundamental evaluations, there are essentially two types of facts:
- Facts that are true right now. These are facts that are immediately actionable and give indications as to the present value of the corporation. Information of this nature has an immediate impact on the stock that is only limited by the reliability of the information.
- Facts that are true over time. These are facts that are forward looking. A lot of things can happen in between now and then, but barring the emergence of any conflicting data, the information will become more and more like the first type of fact as the time of the prediction draws near.
To look at this another way, every prediction has a time point associated with it. In between now and the time the prediction is targeting, the part of the prediction that is exposed to risk will start off at maximum risk. As time goes by, if nothing negates the prediction, it will become more and more certain. If the time of the prediction target is reached with no contradicting information, the prediction will have become like fact, within the accuracy limits of the initial prediction. People don't pay for risk unless they're playing the lottery. The value in information that is forward looking will be directly proportional to the risk fading out as the potential for large surprises dwindles because of the nearness of the prediction target.The best example of this is earnings forecasts. A company issues an earnings forecast at the beginning of the quarter. Parts of the forecast will be fully effective on the day of the prediction. Other parts will be forward looking and will take time to fully pan out. As time goes by in the quarter and there are no earnings warnings or revisions, it's usually assumed that the company has hit their target forecast or only slightly performed outside the predicted range. Then earnings are reported. This information is immediately actionable and 100% accurate, excepting gross accounting errors. Hindsight is 20/20. Foresight becomes hindsight in the absence of new information.
Putting all of the information together, all of these facts and predictions will assemble over time. The concrete part of what is known and used to establish fundamental valuations takes shape over time. Only the concrete parts matter. Some of this information is concrete today. Some of it only becomes concrete over time. Brick by brick, the facts that you can bank on come together.
Monday, May 18, 2009
Serendipitous Joyriding
ser·en·dip·i·ty - the faculty or phenomenon of finding valuable or agreeable things not sought for - Merriam Webster
When looking at the last article, especially if you've tried to delve into technical analysis before, you may have noticed a paradox that's rather hard to overcome. Different types of technical analysis can lead to conflicting conclusions. Different trading patterns can exist simultaneously, even nested patterns. Yet as a technical analyst you would nonetheless be faced with the need to reach a conclusion in the absence of definitive indications. Isn't that what the stock market is supposed to be about anyway? This article aims to change your mind.
Back to clouds and general inaccuracy of weather forecasting, there are some obvious similarities with the stock market. Hurricanes don't just disappear and stocks don't trade at prices that are not supported by supply and demand. The unlikely happens. The impossible doesn't. A hurricane is a very good example of where something chaotic, weather, gives birth to something that's more stable, self propagating as long as conditions remain favorable, and has readily identifiable order to it. Compared to relatively random puffs of clouds that can occur under a lot of conditions, a highly organized storm has both predictability and easily recognized patterns to its behavior. Yes, we still wonder whether they will land in Mexico or Louisiana sometimes, but compared to weather in general, a hurricane is something altogether different than the apparent randomness it resulted from.
Now, to borrow another example from fluid dynamics, take a good look at the photo on the right. Notice how the surrounding clouds seem to have nothing particularly important about them, while seemingly out of nowhere a double swirling pattern emerges and flows downwind. It's a Von-Karman vortex sheet. It was caused by an island that disrupted the cloud flow, which happened to be moving the right speed past an island of the correct size. All of that just happened. And yet the swirl pattern that emerged was periodic, highly organized but still so completely fragile that it slowly dissipates into the equally impressionable surrounding flow.
If chaos is apperent disorder from which it would seem nothing can become ordered, serendipity is the coalescence of many disordered influences that becomes itself not only ordered, but ordered in such a way that it becomes self-sustaining to an extent. As a technical analyst, this is many times what you see. At certain times it's as if there just is no clear pattern, and then out of nowhere the right influences start developing such that there is a clear pattern, and it goes on to re-express itself in the trading behavior as the rest of the traders recognize that the pattern has formed and seek to capitalize on it, reinforcing it.
In the last article, it was advised to think a bit like a single at a bar. Find a table, and then start talking. If you stand out in the middle of nowhere, you're never going to get anywhere. When you're trading, you have to realize that whether you're thinking that a stock is profitable or not, there's still no point in throwing all your money in right away. Don't fight the rugby pile at mid-field.
This article has a second piece of advice; don't find answers where there are none. It's a bit like trying to get inside a person's head while talking to them. You'll inevitably wind up chasing shadows; you'll show yourself in plane sight the first time you screw up. Stock market is no different. The first time you reach a conclusion about something that's really still too weak of a pattern to have the kind of significance required to become self-sustaining, you'll get caught with what's called a whipsaw, where an indicator indicates too early. In layman's terms, it's wrong.
When doing applying technical analysis or any kind of analysis for that matter, avoid the clouds. When you see a small eddie in a vast flow, let it go. When you see a couple of massive vortices that dominate the flow behavior and will continue to do so, jump on it. First of all, the smaller votices are not worth a lot because, even if they do continue to propogate, the end movement will be very small. Second of all, less organized phenomenon always get creamed and negated by more organized phenomenon. Why get fascinated by a quarter that's spinning on a table when a dump truck is about to unload a heap of cash somewhere else? Even if you find a needle in a haystack, it's still just a needle.
Just like these Von-Karman vortex sheets that span miles out over the ocean, what you should be most interested in is that effect that has sprung forth from a medley of all the right circumstances and is about to go on repeating itself several times even in the face of smaller eddies and disturbances along the way. They're huge. They're easy to identify. They develop slowly. They dominate. When you're looking at the weather of the market and the clouds seem to be just rolling forth without purpose, leave them alone. Wait for those moments of serindipity when you realize that all the right things have come together. At that moment, you'll be at the right place at the right time and be able to slowly buy your way into a position, and you won't find it that stressful. You'll have plenty of time to watch and see if the thing keeps developing and you won't have to overexpose yourself by trying to get the most out of a 2ft ladder.
When you do this, it's like your on chaos highway without a thing to lose just changing lanes at a whim and hugging the corners to feel the edge. There are sometimes cars all around and no clear direction, but sometimes that one driver slows down and that one space opens up in that other lane and you can punch it and move straight on through like there's no traffic at all. It's not magic anymore than finding a door in a wall. When it's there it's there. Serendipitous joyriding.
When looking at the last article, especially if you've tried to delve into technical analysis before, you may have noticed a paradox that's rather hard to overcome. Different types of technical analysis can lead to conflicting conclusions. Different trading patterns can exist simultaneously, even nested patterns. Yet as a technical analyst you would nonetheless be faced with the need to reach a conclusion in the absence of definitive indications. Isn't that what the stock market is supposed to be about anyway? This article aims to change your mind.
Back to clouds and general inaccuracy of weather forecasting, there are some obvious similarities with the stock market. Hurricanes don't just disappear and stocks don't trade at prices that are not supported by supply and demand. The unlikely happens. The impossible doesn't. A hurricane is a very good example of where something chaotic, weather, gives birth to something that's more stable, self propagating as long as conditions remain favorable, and has readily identifiable order to it. Compared to relatively random puffs of clouds that can occur under a lot of conditions, a highly organized storm has both predictability and easily recognized patterns to its behavior. Yes, we still wonder whether they will land in Mexico or Louisiana sometimes, but compared to weather in general, a hurricane is something altogether different than the apparent randomness it resulted from.
Now, to borrow another example from fluid dynamics, take a good look at the photo on the right. Notice how the surrounding clouds seem to have nothing particularly important about them, while seemingly out of nowhere a double swirling pattern emerges and flows downwind. It's a Von-Karman vortex sheet. It was caused by an island that disrupted the cloud flow, which happened to be moving the right speed past an island of the correct size. All of that just happened. And yet the swirl pattern that emerged was periodic, highly organized but still so completely fragile that it slowly dissipates into the equally impressionable surrounding flow.If chaos is apperent disorder from which it would seem nothing can become ordered, serendipity is the coalescence of many disordered influences that becomes itself not only ordered, but ordered in such a way that it becomes self-sustaining to an extent. As a technical analyst, this is many times what you see. At certain times it's as if there just is no clear pattern, and then out of nowhere the right influences start developing such that there is a clear pattern, and it goes on to re-express itself in the trading behavior as the rest of the traders recognize that the pattern has formed and seek to capitalize on it, reinforcing it.
In the last article, it was advised to think a bit like a single at a bar. Find a table, and then start talking. If you stand out in the middle of nowhere, you're never going to get anywhere. When you're trading, you have to realize that whether you're thinking that a stock is profitable or not, there's still no point in throwing all your money in right away. Don't fight the rugby pile at mid-field.
This article has a second piece of advice; don't find answers where there are none. It's a bit like trying to get inside a person's head while talking to them. You'll inevitably wind up chasing shadows; you'll show yourself in plane sight the first time you screw up. Stock market is no different. The first time you reach a conclusion about something that's really still too weak of a pattern to have the kind of significance required to become self-sustaining, you'll get caught with what's called a whipsaw, where an indicator indicates too early. In layman's terms, it's wrong.
When doing applying technical analysis or any kind of analysis for that matter, avoid the clouds. When you see a small eddie in a vast flow, let it go. When you see a couple of massive vortices that dominate the flow behavior and will continue to do so, jump on it. First of all, the smaller votices are not worth a lot because, even if they do continue to propogate, the end movement will be very small. Second of all, less organized phenomenon always get creamed and negated by more organized phenomenon. Why get fascinated by a quarter that's spinning on a table when a dump truck is about to unload a heap of cash somewhere else? Even if you find a needle in a haystack, it's still just a needle.
Just like these Von-Karman vortex sheets that span miles out over the ocean, what you should be most interested in is that effect that has sprung forth from a medley of all the right circumstances and is about to go on repeating itself several times even in the face of smaller eddies and disturbances along the way. They're huge. They're easy to identify. They develop slowly. They dominate. When you're looking at the weather of the market and the clouds seem to be just rolling forth without purpose, leave them alone. Wait for those moments of serindipity when you realize that all the right things have come together. At that moment, you'll be at the right place at the right time and be able to slowly buy your way into a position, and you won't find it that stressful. You'll have plenty of time to watch and see if the thing keeps developing and you won't have to overexpose yourself by trying to get the most out of a 2ft ladder.
When you do this, it's like your on chaos highway without a thing to lose just changing lanes at a whim and hugging the corners to feel the edge. There are sometimes cars all around and no clear direction, but sometimes that one driver slows down and that one space opens up in that other lane and you can punch it and move straight on through like there's no traffic at all. It's not magic anymore than finding a door in a wall. When it's there it's there. Serendipitous joyriding.
Saturday, May 2, 2009
Where's the Party At?
During the last post, you should have cemented the idea of limited chaotic trading by exploring the mechanisms that both cause it and contain it to finite ranges. This post will focus instead on what happens inside this finite range. While semi-hard limits are established by the edges of plausible fundamental valuation scenarios, fundamentals play less and less of a role when the stock is trading well within the plausible range. Look back to Covert Newspaper Interception for a refresh on the relationship between fundamentals and technical analysis.
This is a diagram of essentially what you should understand so far. There is a time dependent range of prices that a stock could plausibly trade at. These limits cannot be definitively described by any analytical solution, and even if they could, supply demand imbalances can cause them to be exceeded, although this is not favorable from the market's perspective and traders will quickly jump in to pick up any asset that is trading well away from its estimable value.
The limits can be changed by any number of influences, but usually large changes in a stock's trading regime will occur because of decisive changes to the corporations fundamental value drivers. Whenever this occurs, the chaotic meanderings of the stock within the range of plausible valuations will run into the semi-hard boundaries, where the demand becomes very responsive to further price changes and the stock can be expected to reliably recover.
Stocks always spend the least amount of time near the semi-hard boundaries. The reason for this is that the fundamentals are always dominant and exert ever increasing pressure at the edges, driving the stock back towards the chaotic region where fundamentals give no definite indication as to whether the asset is over or under-priced.
Area in between the boundaries is the current region of interest. The question of trading price is rather easily answered whenever the stock is near it's plausible fundamental boundary. It's rather obvious that somebody needs to either obtain or get rid of shares, and so traders are quick to show up at these points. Their activities guide the stock back into the chaotic region. The question is, now what?
Going back to the singles playing rugby in a bar analogy, ask yourself if you would stand out in the middle of nowhere or wait for a table to fill up somewhere with some interesting characters. Obviously you want to be where the action's at if you're going to make a move. Just like a trader wants to maximize profit potential for every trade, in a bar you might only briefly engage a single your interested while passing by in only to head over to their table later. The decisive interaction happens wherever interested parties coalesce for the mutual opportunity for exchange. Stock trades that happen at prices of little significance are low in volume and likely have little effect on the overall trading pattern. Cool exchanges while passing by on the staircase don't leave much opportunity for conversation. The rugby pile does not just happen out of thin air. Players wait for the right openings. No trades can happen without trading partners. Orders will be waiting in the wings until it's obvious that some trading is about to take place.
Looking at our current model, a chaotic trading pattern semi-bounded by price elasticity resulting from fundamental analysis, it's a bit like knowing what street the bar is on. Once inside, the question becomes, which table are we looking to find a seat at? Technical analysis is the only tool capable of answering this question. It serves such a vital role that even if the entire body of literature on technical analysis were just 1% of what it is, that relatively tiny amount of knowledge would be paramount for anyone who wanted to maximize their profit or move a large amount of shares.
At first glance, the most basic forms of technical analysis seem to be inspired more by superstition and market psychology than any meaningful mechanisms, but recall that we, as traders, are interested exactly in determining where a "good" price to make a play is at in the absence of decisive fundamentals. To put it bluntly an arbitrary but mutually agreed upon price is exactly what's desired. Therefore the fact that the methods seem arbitrary makes them even more important than any analytical indications.
Before going straight to the question of which price to trade at, let's look at the three basic situations for any stock to find itself in:
Price Support/Resistance levels: Look for regions of the chart where lots of trading activity has occurred. A volume overlay is available on free websites such as stock charts that lets you see this graphically:
Blow up the chart to get a clearer view. See the hold up that occurred at approximately 7900 - 8300? Shouldn't be all that significant, yet as the Dow recovered, lo and behold the bounce decelerated quickly as it re-entered this range.
Uptrends/Downtrends: Connect some recent peak-to-peak points or bottom-to-bottom points and linearly extrapolate the result. It's really that simple. Stock charts has their own article on this. This is the most straightforward pacing mechanism in the stock market. As long as the rugby pile keeps advancing somewhere, this is where the new players will show up to keep the momentum going. Trendlines are especialy influential in the shaping of intraday trading.
Moving Averages: Come in exponential and standard varieties. These are also really good pacing mechanisms for a stock on the move. They form the first line offense/defense for trendlines. The beauty is that they exist as indicators even in the absence of existing price points or a nearby trendline. Thus they work even in the third situation.
AMD goes into a dead-cat bounce with the rest of the market and where's the first good point for restistance? There weren't any good price plateau's on the way down, so the stock went on uninterupted until the 200-day moving average. Then the scrummage was on. The exponential 20-day in particular will remain very intact on a long trend and will breakdown almost immediatly whenever the main trend has run its course.
With these three tools, you have all the ability to pick arbitrary price points that you need in order to avoid trading out in the middle of nowhere. Got a falling knife? Look for an old price point. Not sure where to make an entry on a long-term uptrend that is getting tripped up? Look for a longer-term uptrend that has remained intact.
I don't really consider this a form of technical analysis, but picking round numbers isn't always a bad idea. If you want a buy order to go through for certain and are expecting the stock to hit at least $14.50, place the order for $14.48 and you'll avoid having your order get creamed by everyone else. These are numbers of arbitrary significance and if humans had twelve fingers maybe we would think $144 was a price milestone, but we have ten and so decimal values are the numbers to pay attention to. I know. It seems too trivial to be significant, but trust me if you ever watch level II quotes on the daily, you'll see relatively massive volume at round prices like $35 or $10. The rounder the better.
Yes, these numbers are arbitrary, but so is the arrangement of tables in a bar, and yet we still sit down at them instead of standing in the space between.
This is a diagram of essentially what you should understand so far. There is a time dependent range of prices that a stock could plausibly trade at. These limits cannot be definitively described by any analytical solution, and even if they could, supply demand imbalances can cause them to be exceeded, although this is not favorable from the market's perspective and traders will quickly jump in to pick up any asset that is trading well away from its estimable value.The limits can be changed by any number of influences, but usually large changes in a stock's trading regime will occur because of decisive changes to the corporations fundamental value drivers. Whenever this occurs, the chaotic meanderings of the stock within the range of plausible valuations will run into the semi-hard boundaries, where the demand becomes very responsive to further price changes and the stock can be expected to reliably recover.
Stocks always spend the least amount of time near the semi-hard boundaries. The reason for this is that the fundamentals are always dominant and exert ever increasing pressure at the edges, driving the stock back towards the chaotic region where fundamentals give no definite indication as to whether the asset is over or under-priced.
Area in between the boundaries is the current region of interest. The question of trading price is rather easily answered whenever the stock is near it's plausible fundamental boundary. It's rather obvious that somebody needs to either obtain or get rid of shares, and so traders are quick to show up at these points. Their activities guide the stock back into the chaotic region. The question is, now what?
Going back to the singles playing rugby in a bar analogy, ask yourself if you would stand out in the middle of nowhere or wait for a table to fill up somewhere with some interesting characters. Obviously you want to be where the action's at if you're going to make a move. Just like a trader wants to maximize profit potential for every trade, in a bar you might only briefly engage a single your interested while passing by in only to head over to their table later. The decisive interaction happens wherever interested parties coalesce for the mutual opportunity for exchange. Stock trades that happen at prices of little significance are low in volume and likely have little effect on the overall trading pattern. Cool exchanges while passing by on the staircase don't leave much opportunity for conversation. The rugby pile does not just happen out of thin air. Players wait for the right openings. No trades can happen without trading partners. Orders will be waiting in the wings until it's obvious that some trading is about to take place.
Looking at our current model, a chaotic trading pattern semi-bounded by price elasticity resulting from fundamental analysis, it's a bit like knowing what street the bar is on. Once inside, the question becomes, which table are we looking to find a seat at? Technical analysis is the only tool capable of answering this question. It serves such a vital role that even if the entire body of literature on technical analysis were just 1% of what it is, that relatively tiny amount of knowledge would be paramount for anyone who wanted to maximize their profit or move a large amount of shares.
At first glance, the most basic forms of technical analysis seem to be inspired more by superstition and market psychology than any meaningful mechanisms, but recall that we, as traders, are interested exactly in determining where a "good" price to make a play is at in the absence of decisive fundamentals. To put it bluntly an arbitrary but mutually agreed upon price is exactly what's desired. Therefore the fact that the methods seem arbitrary makes them even more important than any analytical indications.
Before going straight to the question of which price to trade at, let's look at the three basic situations for any stock to find itself in:
- Trading Flat - In this situation, the stock has a lot of recent information describing the price elasticity. Reactions to price are well understood and the contention points are straightforward. Non-flat trading will encounter resistance.
- Moving Into Well-Defined Trading Regime - The price is on the move, and there is a body of existing trade history providing good cues as to what prices can be expected relative to prior valuations.
- Moving Into Undefined Trading Regime - Stock is at a price that it has never traded at or hasn't traded at for a very long time. Indications of relative valuations are not current enough or non-existent and cannot provide reliable price points.
Price Support/Resistance levels: Look for regions of the chart where lots of trading activity has occurred. A volume overlay is available on free websites such as stock charts that lets you see this graphically:
Blow up the chart to get a clearer view. See the hold up that occurred at approximately 7900 - 8300? Shouldn't be all that significant, yet as the Dow recovered, lo and behold the bounce decelerated quickly as it re-entered this range.
Uptrends/Downtrends: Connect some recent peak-to-peak points or bottom-to-bottom points and linearly extrapolate the result. It's really that simple. Stock charts has their own article on this. This is the most straightforward pacing mechanism in the stock market. As long as the rugby pile keeps advancing somewhere, this is where the new players will show up to keep the momentum going. Trendlines are especialy influential in the shaping of intraday trading.
Moving Averages: Come in exponential and standard varieties. These are also really good pacing mechanisms for a stock on the move. They form the first line offense/defense for trendlines. The beauty is that they exist as indicators even in the absence of existing price points or a nearby trendline. Thus they work even in the third situation.
AMD goes into a dead-cat bounce with the rest of the market and where's the first good point for restistance? There weren't any good price plateau's on the way down, so the stock went on uninterupted until the 200-day moving average. Then the scrummage was on. The exponential 20-day in particular will remain very intact on a long trend and will breakdown almost immediatly whenever the main trend has run its course.
With these three tools, you have all the ability to pick arbitrary price points that you need in order to avoid trading out in the middle of nowhere. Got a falling knife? Look for an old price point. Not sure where to make an entry on a long-term uptrend that is getting tripped up? Look for a longer-term uptrend that has remained intact.
I don't really consider this a form of technical analysis, but picking round numbers isn't always a bad idea. If you want a buy order to go through for certain and are expecting the stock to hit at least $14.50, place the order for $14.48 and you'll avoid having your order get creamed by everyone else. These are numbers of arbitrary significance and if humans had twelve fingers maybe we would think $144 was a price milestone, but we have ten and so decimal values are the numbers to pay attention to. I know. It seems too trivial to be significant, but trust me if you ever watch level II quotes on the daily, you'll see relatively massive volume at round prices like $35 or $10. The rounder the better.
Yes, these numbers are arbitrary, but so is the arrangement of tables in a bar, and yet we still sit down at them instead of standing in the space between.
Wednesday, April 1, 2009
Origins of Chaos
In the last post the conceptual framework for seeing some bits of order in apparent disorder. This post will focus on the sources of disorder in the stock market. Many of the concepts will apply readily to financial markets of all types. What you should take home from this post is that there is no clear-cut way to determine the value of a stock, and even if there was, there are plenty of reasons why it can't be traded at that value consistently. However, a greater question is, can a stock trade at any price? This post will answer this question with a degree of certainty that seasoned traders and new traders alike may find surprising.
To start, let's imagine a market established solely to determine the value of shares while paying no attention to whether they can be bought or sold in volume at that price. Looking back at the relationship between fundamental analysis and technical analysis, since fundamental analysis is the only avenue for information to enter the market through trading while technical analysis is effectively blind without some fundamental analysis or an existing trading pattern, it's clear that fundamental analysis is the only technique that would be able to determine the value of shares in the absence of trading and market data. Therefore we need to look more closely at what fundamental analysis is and where it loses traction in order to find out why stocks seem to trade so erratically sometimes.
The goal of the fundamental analyst should be to determine the price of the stock based on equity per share and future earnings. Equity per share is just an acknowledgment that the corporation does indeed have assets, cash and non-cash, that if liquidated will be worth an approximate value per share, effectively establishing a certain amount of "hard" value to the share. That is, the share is representative to a certain extent of at least that amount of real assets.
The value of future earnings is much trickier. For one, the value one should pay for earnings that have yet to be booked isn't well agreed upon. Good measures are usually derived from other more stable investments such as CD's and bonds. The value of potential earnings can be benchmarked against relatively guaranteed earnings and using various approximations for risk, the price one is willing to pay for future earnings can be obtained.
However, analysts don't always agree about their earnings predictions, growth rates, and the equity in a corporation. Depending on their models, the data their using, how they interpret it, their instincts through experience and hunches, and even whether or not the investment bank they work for is trying to get a banking deal with the corporation, their earnings estimates and target prices will differ. Different analysts will apply different growth models and will make approximations using different methods. This alone is enough to tell us that the problem of establishing the price a stock should trade at is not straightforward.
Two issues are responsible for most of the difficulty in calculating future earnings, which is a big part of the value per share. The first is that earnings is the difference between revenue and expenses per share. If revenue and expenses are relatively large compared to their difference, then relatively minor fluctuations in either revenue or expenses can produce huge percentage differences in the earnings. This is a condition known as low-margin, and it just means that there is little separation between revenue and expenses. Wall street likes the sound of high-margin because it means that earnings are much less sensitive to minor fluctuations in revenue and costs.
The second challenge to accurately predicting future earnings is the growth rate of the market or markets the corporation does business in. Growth has the most dramatic effect on long-term profitability. If one analyst predicts 5% earnings growth year-on-year and another predicts 10% growth, at the end of ten years the first analyst will expect 63% higher earnings while the second will be looking for 159% higher earnings. Clearly, in any situation where growth is exponential on a long time-scale, minute differences in the estimation of growth can lead to very large divergences in the valuation of a stock by different analysts.
This situation can be exacerbated even further if the net worth of the corporation is small compared to the expected value of future earnings. In this case, the future earnings are the dominant component of the value of the stock, and differences in the predictions of future earnings will create a high degree of uncertainty in the price of the stock.
This illustration shows the assets and liabilities, both hard items on a corporation's balance sheet, as metal coins since the value is very real. The revenue and expenditures are represented by the paper bills. The change in value of the corporation is a result of all of these numbers, and is usually small in comparison. From this chart, it's easy to see how minor fluctuations in these large numbers will produce large percentage changes in profit, causing profit and growth forecasts to vary greatly.
The big picture is starting to take shape, and it's obvious that fundamental analysis has a lot of room for error, particularly in situations where there a corporation has a small amount of assets relative to the size of its expected earnings or where the profit margin is tiny and very susceptible to minor fluctuations in revenue or expenses. What this tells us is that even in an imaginary stock market where the price is set solely by fundamental analysis, there is no perfect price to trade at, leading to the conclusion that fundamentals cannot be the end-all be-all of stock valuations.
This moves us to a second question of interest: Can a stock even trade at a theoretical best price if it exists? To begin answering this, take not that equity markets were originally conceived to facilitate capitalization and to alleviate supply-demand imbalances. Corporations obtain capital through Initial Public Offerings and other secondary offerings, and the market is where they go to sell those shares. Also, traders occasionally wish to move their assets and the market is what provides the medium of liquidity so that they can buy and sell when they need to. Managing supply and demand is a fundamental role of any market.
First to answer the question, supply-demand imbalances exist because not everyone wants to buy or sell at the same time even if they do know what price they would buy or sell at. To make this very clear, let's imagine that Leeroy Jenkens is a day trader worth millions of dollars and also likes to play World of Warcraft. One day Leeroy gets distracted while playing and realizes he's missing out a move he expects from BEBE. He hurriedly enters in an order, but due to carpal tunnel and the rush of the moment, accidentally enters in a few extra zeroes on the number of shares of his market order. Because he has enough cash on hand, the order goes live and wipes out all of the sell orders on the market, eating into higher and higher priced orders up to a theoretical infinity until other computer trading systems quickly catch on and cash in on poor Leeroy. This wouldn't likely happen in real life due to market makers managing such orders to give liquidity a hand, but the point is clear. If someone is buying or selling and has unlimited funds, anything is possible. Clearly the potential exists for localized supply imbalances, whatever the cause, to drive the price far from any expected best price.
To begin illustrating the extent to which these imbalances can affect the trading price, let's consider a different example. A village is visited by two trucks every six months. One is full of bread and the other is full of sneakers. At the day of their arrival, there is simply too much of both bread and sneakers for all of it to be sold. Being the clever merchant, you would look at the cheap prices and realize the opportunity for profit in the future when the demand recovered. However, you wouldn't be willing to accept the same discount on both products. Bread is a staple. It's necessity is guaranteed, so there is a high likelihood that the price will recover. Sneakers are discretionary, so there is a chance that people won't be willing to spare enough income for the prices to fully recover. By the time the price would have recovered, they may be out of style. You would only accept a large discount on the sneakers in order to reduce your exposure to risk. With bread, the price difference quickly becomes like arbitrage, where you trade an asset at a better price on another market. In this case, it's more like time-arbitrage. You just wait for the market to recover. However, with sneakers, the price changes involve more risk, which means it takes a deeper discount for the discount to translate to a sure profit. It takes longer for sneakers to become arbitrage-like than bread.
Turning back to the inaccuracy of fundamental analysis, the role of certainty of fundamentals in determining the sensitivity of the supply-demand relationship to price fluctuations can be made clear. A corporation whose earnings have more potential to fluctuate wildly and has a small amount of hard assets per share will require deeper discounts to attract more dollars. Every buy or sell order will require a large relative price change to succeed in executing a trade. Corporations with lots of hard assets, consistent earnings, and high margins will become arbitrage-like very quickly. In short, the uncertainty of fundamental analysis has a dominant effect on the supply-demand relationship.
The big picture is nearly finished. Not only is there no exact best price, but even if there was a theoretical best price, due to supply-demand imbalances this price can't always be traded at. Furthermore, the potential for valuation to fluctuate due to uncertainty in earnings has a direct effect on how powerful supply-demand imbalances will be in determining what price shares ultimately change hands at.
The last question is, does the theoretical best price stay constant over time? To answer this, we can simply look at what drives fundamental analysis. Existing and emerging financial data, news breaks with relevant impact on expectations, and insider information etc are all used to create the fundamental analysts estimates. In the case of existing data, it exists and won't change over time. This would form a static picture of the stock's valuation. However, the fact that there is emerging financial news will produce changes in this picture, making it dynamic as new data or news emerges.
To integrate this all into a single model, turn back to the idea that all information enters the market via fundamental analysis of some sort, be it insider information or SEC filings becoming expressed in expectations, followed by trading activity. We would expect that due to variations in expectations, that there is in fact no best price, but instead a range of plausible prices, with fundamentals creating a containment effect whereby supply-demand imbalances are evened out whenever the trading price becomes a less plausible valuation, attracting more counteracting trades. Near the edges of the range of plausible prices, supply-demand imbalances will be corrected more quickly. In regions where prices changes all result in plausible valuations, there is little sensitivity to price changes and other mechanisms are dominant. As new information becomes available one way or another, the range of plausible valuations is changed, giving us new locations to expect resistance to supply-demand imbalances to exist.
To visualize this, recall the cigarette diagrams. While turbulent smoke can take many paths, the underlying physics always act to ensure that the path that any particular smoke plume takes is going to fall within a certain range of likelihood. Within this range, the particular shape is more dominated by chaotic effects. If the cigarette was inside a region of slowly churning air, the range the smoke would exist in would so migrate, taking the smoke with it. This should start to seem very familiar to any seasoned trader. The range of likelihoods of smoke is analogous to the range of plausible valuations. The turbulent path within this range is analogous to the trading price as it ultimately exists at any given time. The migration of the smoke plume caused by tiny winds is analogous to the changes in plausible valuations that occurs as new information becomes available.
Turning back to the million dollar question of whether a stock can trade at any price, it's already been made clear that extreme supply-demand imbalances can exist and can severely impact the stock price one way or another. Upon first inspection, this would seem to suggest that it is in fact possible for any price to exist at any time. Internet stocks and the recently failed bank stocks are two examples where valuations can seem to indeed demonstrate that any price is possible. However, lets look at what the model says about these two situations. With internet stocks, they had low assets, high expected earnings growth, and little or no current earnings, all factors which increased the uncertainty in valuations and thereby decreased the response to supply-demand imbalances. Thus we saw the stocks trading at very generous valuations even if they were to ultimately fail. The potential earnings were so high that there was little to rein in the price at the top end. In the case of failed banks, it could be said that the banks had low volatility in earnings predictions leading up to the collapse of the stock price, but they also were affected considerably by emerging news. Lehman Brother announcing bankruptcy was a major change to the set of existing data, which facilitated a huge move in the stock price. What we begin to see in these examples is that, while at first glance almost any stock price does seem possible, extreme valuations and changes to valuations will only occur in the presence of large uncertainty in fundamentals or when those fundamentals themselves have been greatly modified by new data. What this says is that, while any stock price can be possible over time, at any one given time, only certain stock prices are likely. In short, $60 Lehman would never have traded at $2. It was emerging news that facilitated this price. It can and did trade that way over time, but these valuations are not plausible for every stock at any time.
The keen scholar would say that the potential for supply-demand imbalances to move a stock to any price would negate the assertion that there is such a thing as a trading range. However, consider a different field of study that can and does tolerate such local variance. Quantum physics, in stark contrast to classical physics, only requires that things are conserved on the average. Essentially, there is a finite chance that particles can appear out of absolute total nothing, but the chance is small and, on average, the balance of particles just randomly appearing and disappearing out of thin nothing is zero. To get a better idea of why this doesn't break the model, consider the recent popular movie, The Watchmen, in which a main character, Dr. Manhattan, declares he longs to see oxygen turn into gold. While theoretically possible with a finite chance that is about as close to zero as it can get, Dr. Manhatten should be disappointed to find out that his one atom of gold, while worth nearly $1000 per ounce, is almost worthless. To rephrase this, likely events will happen with great effect and are very tradable while small variances are not tradable and will happen with fleeting effect on the larger market.
To start, let's imagine a market established solely to determine the value of shares while paying no attention to whether they can be bought or sold in volume at that price. Looking back at the relationship between fundamental analysis and technical analysis, since fundamental analysis is the only avenue for information to enter the market through trading while technical analysis is effectively blind without some fundamental analysis or an existing trading pattern, it's clear that fundamental analysis is the only technique that would be able to determine the value of shares in the absence of trading and market data. Therefore we need to look more closely at what fundamental analysis is and where it loses traction in order to find out why stocks seem to trade so erratically sometimes.
The goal of the fundamental analyst should be to determine the price of the stock based on equity per share and future earnings. Equity per share is just an acknowledgment that the corporation does indeed have assets, cash and non-cash, that if liquidated will be worth an approximate value per share, effectively establishing a certain amount of "hard" value to the share. That is, the share is representative to a certain extent of at least that amount of real assets.
The value of future earnings is much trickier. For one, the value one should pay for earnings that have yet to be booked isn't well agreed upon. Good measures are usually derived from other more stable investments such as CD's and bonds. The value of potential earnings can be benchmarked against relatively guaranteed earnings and using various approximations for risk, the price one is willing to pay for future earnings can be obtained.
However, analysts don't always agree about their earnings predictions, growth rates, and the equity in a corporation. Depending on their models, the data their using, how they interpret it, their instincts through experience and hunches, and even whether or not the investment bank they work for is trying to get a banking deal with the corporation, their earnings estimates and target prices will differ. Different analysts will apply different growth models and will make approximations using different methods. This alone is enough to tell us that the problem of establishing the price a stock should trade at is not straightforward.
Two issues are responsible for most of the difficulty in calculating future earnings, which is a big part of the value per share. The first is that earnings is the difference between revenue and expenses per share. If revenue and expenses are relatively large compared to their difference, then relatively minor fluctuations in either revenue or expenses can produce huge percentage differences in the earnings. This is a condition known as low-margin, and it just means that there is little separation between revenue and expenses. Wall street likes the sound of high-margin because it means that earnings are much less sensitive to minor fluctuations in revenue and costs.
The second challenge to accurately predicting future earnings is the growth rate of the market or markets the corporation does business in. Growth has the most dramatic effect on long-term profitability. If one analyst predicts 5% earnings growth year-on-year and another predicts 10% growth, at the end of ten years the first analyst will expect 63% higher earnings while the second will be looking for 159% higher earnings. Clearly, in any situation where growth is exponential on a long time-scale, minute differences in the estimation of growth can lead to very large divergences in the valuation of a stock by different analysts.
This situation can be exacerbated even further if the net worth of the corporation is small compared to the expected value of future earnings. In this case, the future earnings are the dominant component of the value of the stock, and differences in the predictions of future earnings will create a high degree of uncertainty in the price of the stock.
This illustration shows the assets and liabilities, both hard items on a corporation's balance sheet, as metal coins since the value is very real. The revenue and expenditures are represented by the paper bills. The change in value of the corporation is a result of all of these numbers, and is usually small in comparison. From this chart, it's easy to see how minor fluctuations in these large numbers will produce large percentage changes in profit, causing profit and growth forecasts to vary greatly.The big picture is starting to take shape, and it's obvious that fundamental analysis has a lot of room for error, particularly in situations where there a corporation has a small amount of assets relative to the size of its expected earnings or where the profit margin is tiny and very susceptible to minor fluctuations in revenue or expenses. What this tells us is that even in an imaginary stock market where the price is set solely by fundamental analysis, there is no perfect price to trade at, leading to the conclusion that fundamentals cannot be the end-all be-all of stock valuations.
This moves us to a second question of interest: Can a stock even trade at a theoretical best price if it exists? To begin answering this, take not that equity markets were originally conceived to facilitate capitalization and to alleviate supply-demand imbalances. Corporations obtain capital through Initial Public Offerings and other secondary offerings, and the market is where they go to sell those shares. Also, traders occasionally wish to move their assets and the market is what provides the medium of liquidity so that they can buy and sell when they need to. Managing supply and demand is a fundamental role of any market.
First to answer the question, supply-demand imbalances exist because not everyone wants to buy or sell at the same time even if they do know what price they would buy or sell at. To make this very clear, let's imagine that Leeroy Jenkens is a day trader worth millions of dollars and also likes to play World of Warcraft. One day Leeroy gets distracted while playing and realizes he's missing out a move he expects from BEBE. He hurriedly enters in an order, but due to carpal tunnel and the rush of the moment, accidentally enters in a few extra zeroes on the number of shares of his market order. Because he has enough cash on hand, the order goes live and wipes out all of the sell orders on the market, eating into higher and higher priced orders up to a theoretical infinity until other computer trading systems quickly catch on and cash in on poor Leeroy. This wouldn't likely happen in real life due to market makers managing such orders to give liquidity a hand, but the point is clear. If someone is buying or selling and has unlimited funds, anything is possible. Clearly the potential exists for localized supply imbalances, whatever the cause, to drive the price far from any expected best price.
To begin illustrating the extent to which these imbalances can affect the trading price, let's consider a different example. A village is visited by two trucks every six months. One is full of bread and the other is full of sneakers. At the day of their arrival, there is simply too much of both bread and sneakers for all of it to be sold. Being the clever merchant, you would look at the cheap prices and realize the opportunity for profit in the future when the demand recovered. However, you wouldn't be willing to accept the same discount on both products. Bread is a staple. It's necessity is guaranteed, so there is a high likelihood that the price will recover. Sneakers are discretionary, so there is a chance that people won't be willing to spare enough income for the prices to fully recover. By the time the price would have recovered, they may be out of style. You would only accept a large discount on the sneakers in order to reduce your exposure to risk. With bread, the price difference quickly becomes like arbitrage, where you trade an asset at a better price on another market. In this case, it's more like time-arbitrage. You just wait for the market to recover. However, with sneakers, the price changes involve more risk, which means it takes a deeper discount for the discount to translate to a sure profit. It takes longer for sneakers to become arbitrage-like than bread.
Turning back to the inaccuracy of fundamental analysis, the role of certainty of fundamentals in determining the sensitivity of the supply-demand relationship to price fluctuations can be made clear. A corporation whose earnings have more potential to fluctuate wildly and has a small amount of hard assets per share will require deeper discounts to attract more dollars. Every buy or sell order will require a large relative price change to succeed in executing a trade. Corporations with lots of hard assets, consistent earnings, and high margins will become arbitrage-like very quickly. In short, the uncertainty of fundamental analysis has a dominant effect on the supply-demand relationship.
The big picture is nearly finished. Not only is there no exact best price, but even if there was a theoretical best price, due to supply-demand imbalances this price can't always be traded at. Furthermore, the potential for valuation to fluctuate due to uncertainty in earnings has a direct effect on how powerful supply-demand imbalances will be in determining what price shares ultimately change hands at.
The last question is, does the theoretical best price stay constant over time? To answer this, we can simply look at what drives fundamental analysis. Existing and emerging financial data, news breaks with relevant impact on expectations, and insider information etc are all used to create the fundamental analysts estimates. In the case of existing data, it exists and won't change over time. This would form a static picture of the stock's valuation. However, the fact that there is emerging financial news will produce changes in this picture, making it dynamic as new data or news emerges.
To integrate this all into a single model, turn back to the idea that all information enters the market via fundamental analysis of some sort, be it insider information or SEC filings becoming expressed in expectations, followed by trading activity. We would expect that due to variations in expectations, that there is in fact no best price, but instead a range of plausible prices, with fundamentals creating a containment effect whereby supply-demand imbalances are evened out whenever the trading price becomes a less plausible valuation, attracting more counteracting trades. Near the edges of the range of plausible prices, supply-demand imbalances will be corrected more quickly. In regions where prices changes all result in plausible valuations, there is little sensitivity to price changes and other mechanisms are dominant. As new information becomes available one way or another, the range of plausible valuations is changed, giving us new locations to expect resistance to supply-demand imbalances to exist.
To visualize this, recall the cigarette diagrams. While turbulent smoke can take many paths, the underlying physics always act to ensure that the path that any particular smoke plume takes is going to fall within a certain range of likelihood. Within this range, the particular shape is more dominated by chaotic effects. If the cigarette was inside a region of slowly churning air, the range the smoke would exist in would so migrate, taking the smoke with it. This should start to seem very familiar to any seasoned trader. The range of likelihoods of smoke is analogous to the range of plausible valuations. The turbulent path within this range is analogous to the trading price as it ultimately exists at any given time. The migration of the smoke plume caused by tiny winds is analogous to the changes in plausible valuations that occurs as new information becomes available.
Turning back to the million dollar question of whether a stock can trade at any price, it's already been made clear that extreme supply-demand imbalances can exist and can severely impact the stock price one way or another. Upon first inspection, this would seem to suggest that it is in fact possible for any price to exist at any time. Internet stocks and the recently failed bank stocks are two examples where valuations can seem to indeed demonstrate that any price is possible. However, lets look at what the model says about these two situations. With internet stocks, they had low assets, high expected earnings growth, and little or no current earnings, all factors which increased the uncertainty in valuations and thereby decreased the response to supply-demand imbalances. Thus we saw the stocks trading at very generous valuations even if they were to ultimately fail. The potential earnings were so high that there was little to rein in the price at the top end. In the case of failed banks, it could be said that the banks had low volatility in earnings predictions leading up to the collapse of the stock price, but they also were affected considerably by emerging news. Lehman Brother announcing bankruptcy was a major change to the set of existing data, which facilitated a huge move in the stock price. What we begin to see in these examples is that, while at first glance almost any stock price does seem possible, extreme valuations and changes to valuations will only occur in the presence of large uncertainty in fundamentals or when those fundamentals themselves have been greatly modified by new data. What this says is that, while any stock price can be possible over time, at any one given time, only certain stock prices are likely. In short, $60 Lehman would never have traded at $2. It was emerging news that facilitated this price. It can and did trade that way over time, but these valuations are not plausible for every stock at any time.
The keen scholar would say that the potential for supply-demand imbalances to move a stock to any price would negate the assertion that there is such a thing as a trading range. However, consider a different field of study that can and does tolerate such local variance. Quantum physics, in stark contrast to classical physics, only requires that things are conserved on the average. Essentially, there is a finite chance that particles can appear out of absolute total nothing, but the chance is small and, on average, the balance of particles just randomly appearing and disappearing out of thin nothing is zero. To get a better idea of why this doesn't break the model, consider the recent popular movie, The Watchmen, in which a main character, Dr. Manhattan, declares he longs to see oxygen turn into gold. While theoretically possible with a finite chance that is about as close to zero as it can get, Dr. Manhatten should be disappointed to find out that his one atom of gold, while worth nearly $1000 per ounce, is almost worthless. To rephrase this, likely events will happen with great effect and are very tradable while small variances are not tradable and will happen with fleeting effect on the larger market.
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