V.11:1 (51-54): Spectral Forecasting And The Financial Markets by Denis Ridley, Ph.D..

V.11:1 (51-54): Spectral Forecasting And The Financial Markets by Denis Ridley, Ph.D..
Item# \V11\C01\SPECTRA.PDF
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Spectral Forecasting And The Financial Markets by Denis Ridley, PhD.

Ever considered spectral wave analysis to determine cycles in the stock market? Denis Ridley tells you how.

As a rule, the financial markets are not easy to forecast. While forecasting every future value of the index is not a reasonable objective, predicting sharp changes in very short-term trends is useful for trading, and that is really all that should matter to the trader. While we cannot and will not prove or disprove the random walk theory, we will look at some predictable elements that do exist in the DJIA and are of interest to the trader. When a variable is observed over a period, the series of observations is referred to as a time series. Many financial time series have been classified as random walks, in which case forecasting may be impossible. What sort of cyclical content exists in the Dow Jones Industrial Average (DJIA)? Are there any predictable elements?


The spectral approach offers a better way of estimating cyclical components. When recombined by the moving window spectral (MWS) method, the effect of cycles aligning will produce a forecast of major turning points, which in turn represent changes in the short-term trend. The information needed to make predictions are embedded as component cycles.

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