V. 19:11 (56-61): Nearest Neighbor Prediction by Hans Uhlig, Ph.D.
Product Description
Nearest Neighbor Prediction by Hans Uhlig, Ph.D.
Forecast the direction of the market using this model based on chaos theory.
Although it made many traders happy, the stock market of the 1990s was in some ways quite boring. It was a one-way street leading up, and during that period, the buy-and-hold strategy worked unusually well. This historically abnormal market behavior led to a widespread overestimation of the buy-and-hold strategy and an underestimation of market timing.
Now, of course, the picture has changed drastically. Indices are no longer climbing to new highs; instead, they’re testing their lows. In times like these, applying a buy-and-hold strategy may not be the ideal choice. As a result, we must look at other approaches to investing in the stock market.
One approach I use is a method borrowed from chaos research, called nearest neighbor prediction (NNP). I will show you how to use NNP to make one-week forecasts of the stock market direction, using the weekly closes of the Standard & Poor’s 500 as my example. This method clearly outperformed buy-and-hold over the last five years, even when the buy-and-hold method was working well.
The beauty of NNP is that it requires only an ordinary spreadsheet program. The operating principle is easy to grasp, decisions are always explicable, and there is no lengthy training phase. The method is robust and even self-improving over time as more data becomes available.
Forecast the direction of the market using this model based on chaos theory.
Although it made many traders happy, the stock market of the 1990s was in some ways quite boring. It was a one-way street leading up, and during that period, the buy-and-hold strategy worked unusually well. This historically abnormal market behavior led to a widespread overestimation of the buy-and-hold strategy and an underestimation of market timing.
Now, of course, the picture has changed drastically. Indices are no longer climbing to new highs; instead, they’re testing their lows. In times like these, applying a buy-and-hold strategy may not be the ideal choice. As a result, we must look at other approaches to investing in the stock market.
One approach I use is a method borrowed from chaos research, called nearest neighbor prediction (NNP). I will show you how to use NNP to make one-week forecasts of the stock market direction, using the weekly closes of the Standard & Poor’s 500 as my example. This method clearly outperformed buy-and-hold over the last five years, even when the buy-and-hold method was working well.
The beauty of NNP is that it requires only an ordinary spreadsheet program. The operating principle is easy to grasp, decisions are always explicable, and there is no lengthy training phase. The method is robust and even self-improving over time as more data becomes available.
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