Physicists like to think that all you have to do is say, these are the conditions, now what happens next?
Richard P. Feynman
What follows are random headlines from the front cover of Futures Magazine:
- How will grain prices fare?
- Will the fed hike a third time?
- Sky high: will grains come back to earth?
- Will metals heat up in the cooled economy?
- The fed effect: what's the market to do?
- Top ten trading systems of all time!
- How will stock market react to Fed over next 12 months?
- Gore vs. Bush: who will corner the market?
- Will energy markets heat up?
- Stocks: will the bears return?
- Should you trade on government statistics?
- How to navigate the currency maze?
- Bull or bust: where are softs headed?
- How sentiment moves the market.
- Bears to crash stock market's party?
- Will the U.S. dollar keep chugging?
- Is the bull back?
- How to profit in a modernized Europe.
How many questioned the prediction folly of these headlines at the time?
Prediction Impossible
The headlines above all imply that market prediction works. They seem to back the ruse that a crystal ball will help see the chaotic future. Trend Following food for thought:
The world of mathematics has been confined to the linear world for centuries. That is to say, mathematicians and physicists have overlooked dynamical systems as random and unpredictable. The only systems that could be understood in the past were those that were believed to be linear, that is to say, systems that follow predictable patterns and arrangements. Linear equations, linear functions, linear algebra, linear programming, and linear accelerators are all areas that have been understood and mastered by the human race. However, the problem arises that we humans do not live in an even remotely linear world; in fact, our world must indeed be categorized as nonlinear; hence, proportion and linearity is scarce. How may one go about pursuing and understanding a nonlinear system in a world that is confined to the easy, logical linearity of everything? This is the question that scientists and mathematicians became burdened with in the 19th Century; hence, a new science and mathematics was derived: chaos theory.
Manus J. Donahue III
An Introduction to Chaos Theory and Fractal Geometry
The stock markets are said to be nonlinear, dynamic systems. Chaos theory is the mathematics of studying such nonlinear, dynamic systems. Does this mean that chaoticians can predict when stocks will rise and fall? Not quite; however, chaoticians have determined that the market prices are highly random, but with a trend. The stock market is accepted as a self-similar system in the sense that the individual parts are related to the whole. Another self-similar system in the area of mathematics are fractals. Could the stock market be associated with a fractal? Why not? In the market price action, if one looks at the market monthly, weekly, daily, and intra day bar charts, the structure has a similar appearance. However, just like a fractal, the stock market has sensitive dependence on initial conditions. This factor is what makes dynamic market systems so difficult to predict. Because we cannot accurately describe the current situation with the detail necessary, we cannot accurately predict the state of the system at a future time. Stock market success can be predicted by chaoticians. Short-term investing, such as intra day exchanges are a waste of time. Short-term traders will fail over time due to nothing more than the cost of trading. However, over time, long-term price action is not random. Traders can succeed trading from daily or weekly charts if they follow the trends. A system can be random in the short-term and deterministic in the long term.
Manus J. Donahue III
An Introduction to Chaos Theory and Fractal Geometry
