The Stock Market And Chaos


According to most authorities, stock markets are non-linear, dynamic systems. Chaos theory is the mathematics of studying just that- non-linear, dynamic systems. Chaos analysis has determined that stock market prices are highly random, but with a trend. The amount of the trend varies from market to market and from time frame to time frame. A concept involved in chaotic systems is fractals. Fractals are objects which are "self-similar" in the sense that the individual parts are related to the whole. A popular example of this is a tree. While the branches get smaller and smaller, each is similar in structure to the larger branches and the tree as a whole. Similarly, in market price action, as you look at monthly, weekly, daily, and intra day bar charts, the structure has a similar appearance. Just as with natural objects, as you move in closer and closer, you see more and more detail. Another characteristic of chaotic markets is called "sensitive dependence on initial conditions." This is what makes dynamic market systems so difficult to predict. Because we cannot accurately describe the current situation band because of errors in the descriptions, they are hard to find due to the system's overall complexity. Accurate predictions become impossible. Even if we could predict tomorrow's stock market change exactly (which we can't), we would still have zero accuracy trying to predict only twenty days ahead. A number of thoughtful traders and experts have suggested that those trading with intra day data such as five-minute bar charts are trading random noise and thus wasting their time. Over time, they are doomed to failure by the costs of trading. At the same time these experts say that longer-term price action is not random. Traders can succeed in trading from daily or weekly charts if they follow trends. The question naturally arises how can short-term data be random and longer-term data not be in the same market? If short-term (random) data accumulates to form long-term data, wouldn't that also have to be random? As it turns out, such a paradox can exist. A system can be random in the short-term and deterministic in the long term.