Stock Market Prediction Using Cycle Analysis

Stock market cycles can help maximize ROI.

One of the characters in the market is that it has powerful and fairly consistent cycles. Its performance curve can be considered as a sum of the cyclical functions with different periods and amplitudes. Some cycles known to investors for a long time, for example, the four-year presidential cycle or the annual and quarterly fiscal reporting cycles. By identifying cycles, it is possible to anticipate highs and lows, as well as determine trends. So that cycles can be a good opportunity to maximize return on investment.

It is difficult to identify cycles using a simple chart analysis.

It is not easy to analyze the repetition of typical patterns in a performance curve because cycles are often masked; sometimes they overlap to form an abnormal end or shift to form a flat period. The presence of multiple cycles of different periods and magnitudes together with linear and non-linear trends can form a complex pattern of the curve. Obviously, a simple graphical analysis has a certain limit to identify the parameters of the cycles and use them to predict. Therefore, a mathematical statistical model implemented in a computer program could be a solution.

Please note: no predictive model guarantees 100% accuracy.

Unfortunately, any predictive model has its own limit. The main obstacle in using cycle analysis for stock market prediction is the instability of the cycle. Due to the probabilistic nature of the market, cycles sometimes repeat, sometimes not. To avoid overconfidence and therefore losses, it is important to remember the semi-cyclical nature of the market. In other words, prediction based on cycle analysis, as well as any other technique, cannot guarantee 100% prediction accuracy.

Back testing helps improve prediction accuracy.

One of the techniques to improve the accuracy of a prediction is back testing. It is the process of testing the prediction in previous time periods. At first, instead of calculating the prediction for the time period onwards, we could simulate the forecast on relevant past data to estimate the precision of the prediction with certain parameters. So optimizing these parameters could help to achieve higher forecast accuracy.

The software makes it possible to use cycle analysis for stock price prediction.

To discover different patterns in price movement, including cycles, investors use different software tools. They are able to extract basic cycles of the stock market (indices, sectors or well-traded stocks). To build an extrapolation (i.e. forecast), they typically use the following two-step approach: (1) apply spectral analysis (time series) to decompose the curve into basic functions, (2) compose these functions beyond the data historical. Also, the best software tools should include backtesting.

conclusion

The stock market is a living system: there may be joy or fear, but its buying and selling pulse is always there. To discover different patterns in the market movement, including cycles, investors use different software tools. These computer tools are sometimes called “stock market software.” Stock market software tools help investors and traders research, analyze, and predict the stock market.