<b>RE: too many variables to find the deterministic motion:</b> I'm with darkhorse on this one. Although, I certainly do not believe that we can create a 100% accurate predictor of market action, we can create profitable predictors/rules for when to buy & sell. I especially like the notion of finding 'clarity pockets' and would say that both discretionary and mechanical traders should look for these.
Certainly, there are "random" effects that perturb the price action. The "random" arrival of buyers and sellers is guaranteed to create minor order imbalance transients (Queuing theory is useful for thinking about this one). News creates so-called exogenous shocks that cause market participants to reevaluate the fundamental value of financial instruments (we'd need a separate thread to discuss whether most really are exogenous or not). I'd even bet that data storms on the internet have an effect by slowing down the trader's cycle of information gathering and trading action. These and other effects then participate in feedback loops that may be positive (e.g., a minor, totally random cluster of buyers leads to a short-term rally and subsequent fall-back on a stock).
The examples from science of randomness (Brownian motion, radioactive decay, etc.) are useful for thinking about some aspects of the markets, but they have crucial limits. Whereas an air molecule has no incentive to either hit or avoid a dust mote, traders have strong incentive to hit or avoid a bid. Whereas a coin has no knowledge of its history, traders are acutely aware of the price history of their tradables. That traders (and investors) share common and knowable thought processes and incentives determines the extent that price action follows common and knowable dynamical patterns.
<b>RE: Descriptive vs. predictive rules:</b> As darkhorse indicates, this is a tricky area. Its too easy to misapply middle-of-the-chart, descriptive rules (the after-the-fact why) to trading. And, its very hard to maintain a right-edge-of-the-chart mentality when looking at historical data. Just about any kind of backtesting will be prone to survivorship bias. For example, I'd bet that not many traders are backtesting any bullish trading systems against WCOM or ENE historical data -- its too obvious and too easy to avoid data on stocks that we now know did not make it.
<b>RE:the distribution:</b>The distribution of price changes (returns) of stocks and stock indexes is nearly normal. But its not quite normal, much to the consternation of believers in the central limit theorem (and an excellent example of darkhorse's comment about the difference between academia and the markets). The distribution of returns differs from normality in being both skewed and heavy-tailed (kurtotic). Some researchers have used what are called stable Pareto-Levy distributions to model the fat-tailed distributions of returns. Others have turned to the t-distribution. Another aspect of the distribution of price changes is that the variance (volatility) changes over time and, historically speaking, returns have a positive bias. If you want to know more and are very mathematically inclined, look at "A Non-Random Walk Down Wall Street" by Lo and MacKinlay or the older, somewhat overlapping "The Econometrics of Financial Markets" by Campbell, Lo, & MacKinlay. And if you want something a bit more introductory, try "Quantitative Methods in Finance" by Watsham and Parramore, although I have found errors in that book.
I think this modification of Arthur C. Clark's quote says it best:
"Any sufficiently complex pattern is indistinguishable from randomness."
This is the essential conundrum for those concerned about whether the markets are random (and all traders should be concerned with this). Nobody can prove that the markets are random, they can only prove that they fail to conform to any of a long and growing list of models. The problem is that along the way, its too easy to find deterministic models that seem to work (for a while)
I don't believe the markets are random and I hope that I am right. In the meantime, I'm working to ensure that I am not Fooled by Randomness (or at least not too fooled by it.
).
Until I learn that the markets are random, I'm Traden4Alpha
P.S. I was first intrigued by alpha when I studied modern portfolio theory. But, more recently, Ben Warwick's very interesting book called "In Search of Alpha" did indeed inspire the nickname.
