Financial Markets : The Forces Behind The Moves.
This general discussion of how the dynamics of the financial markets - how they really work - is an expansion of an article originally published in the Belgian business magazine "Trends et Tendances" of April 14, 1994.
The Markets: Unpredictable but beatable...
Centuries ago it was thought that inspection of the entrails of dead animals provided the data necessary for the prediction of future events. Astrological techniques were an improvement - at least in terms of hygiene. The British, a nation with many curious habits, took to interpreting the patterns of dead leaves left in the bottom of their tea-cups. This was, of course, before the invention of the tea-bag.
More recently, with the aid of telecommunications and computers, more sophisticated methods of arriving at future projections have been applied, particularly to the financial markets:
So, based on the results of the application of all of this awesome intellectual and electronic power, where will the yen, or the London stock market, or shares in Siemens, or US treasury bonds be next week - or next month - or next year ?
Not only does nobody know by how much any of these instruments will go up or down: it is impossible to predict the direction of the next move in any market in any time-frame. The only exceptions to this rule are:
The academic consensus used to be that it was impossible to "beat" freely fluctuating markets on a regular basis because they were inherently unpredictable. Two theories were advanced in support of this proposition:
The "efficient market theory" postulated that everything now known which is relevant to a particular market has already been taken into account by market participants in determining the current price. It followed that only unknown future events could influence the price up or down. This argument:
Mr. Soros' Quantum fund is reputed to have made a billion dollar profit speculating against Sterling during the most recent EMS crisis. The Malaysian national bank, whose then governor is now otherwise occupied, lost more than that betting the other way (ironically, Mr. Soros himself admitted to losing $600 Mn. in speculation, notably in the Yen, early in 1994).
The "random walk theory" is a development of the same line of thought, postulating that "Price action is random, and therefore unpredictable, since the markets are continually reacting to a random stream of positive and negative news of randomly varying intensity". Prices do not, however, behave randomly (or at least not entirely randomly).
The really significant difference between random and real price-series is that in real markets the variations in volatility are much wider: markets go through long periods of relative calm punctuated by dramatic moves with much wider period-to-period variations.
The bar-chart shown below (with "RSI" underneath it) was generated using Excel's random-number generator. The program used to generate is available for free down-load here. Every time the worksheet is recalculated a new chart will be generated.
The above randomly-generated "time-series" shows surprisingly persistent "trends", interrupted by "corrections", as will the others you generate if you run the program.
The methods used to generate the charts are detailed on the spread-sheet.
The following two charts compare the "Frequency Distributions" of a randomly generated series with 5-minute moves in the Standard & Poors stock-index futures over three months, excluding the first and last half-hours of each day to ensure that the results are not skewed by the influence of the overnight gap:
The chart on the left shows a typical bell-shaped random distribution. On the right the "real-market" distribution is taller and thinner, with broad, relatively flat extremities. It confirms what experienced market observers already know:
Note that while the "body" of the S&P chart is shifted to the right (more positive than negative moves in an up-trend) the largest move is on the left (a vicious correction).
In the simplest possible terms, the reason that neither of the above theories holds true is that while, over the long term, market prices will always adjust to changes in the underlying fundamentals, it is also true that the underlying fundamentals are continually influenced by changes in market prices.
A simple example: if share prices are under-valued in relation to net company assets (as they are in the depths of a bear-market), alert financiers can make large profits by buying companies and selling-off their assets. This has a number of effects including the triggering of a general rise in equity prices, which has the effect of increasing everyone's wealth, and in particular the collateral value of shares against which money can be raised to carry out additional leveraged deals, which then accelerate the process. At the same time "real-world" activity is stimulated. Increasing asset-valuations encourage investment. The economy and consumption expand. These processes become self-feeding and continue until levels of excess are reached, deals start to fail, and the process reverses.
These observations are not original, of course. This was the story of the 1980's and the processes are well understood. The key points are:
Whether or not these processes are "Chaotic" in the mathematical sense is open to debate. Chaos theory postulates that dynamical systems, where the future values of the variables involved (such as market prices, the weather, population sizes or gross national product) depend both on each other and on their own previous values, evolve in series of persistent cyclical trends. The cycles are never however identical, and are extremely sensitive to tiny changes in the initial conditions. In other words, even if the markets are governed by deterministic forces (which would imply that they can be predicted by accurate modeling of the current situation and the forces which apply to each variable including the price), it would paradoxically still be impossible to predict them because tiny and unavoidable errors in the definition of the initial conditions would cause major errors to appear in the results after a very few iterations. Of course if they are not deterministic, then any attempt to build forecasting models is futile. Either way, forecasters and econometric modelers are doomed to failure.
Dynamical systems can remain in a trend much longer than expected (as when stocks remain in a bull market long after most commentators consider them to be over-valued). At other times they break down unexpectedly, the 1994 collapse in bond prices world-wide being a case in point. When this happens scapegoats are quickly identified. In 1987 it was "program trading", in 1994 it was "hedge funds".
Notwithstanding all of the above, there are numerous different strategies, both "fundamental" and "technical" which can be successfully deployed to obtain above-average returns from the markets. All of them involve the disciplined assumption of risk, and the willingness to get out as soon as it becomes apparent either that the initial analysis was wrong or that conditions have changed.
My own preferred approach is technical because everything which is relevant to a particular market is reflected in the evolution of its price. Alert interpretation of the manner in which a price is acting, as revealed by price-charts, gives clues as to its future movement which are at least as likely to be correct as the attempted analysis of all of the many outside factors which are thought likely to influence it: and it is much easier to do. Equally importantly, the market tells me directly (and brutally) when I am wrong, and I can act accordingly.