| Stock market cycles may help to maximize ROI. | | | | analysis, as well as, any other technique cannot |
| One of the market characters is that it has powerful | | | | guarantee 100% accuracy of prediction. |
| and pretty consistent cycles. Its performance curve | | | | Back-testing helps to improve prediction accuracy. |
| can be considered as a sum of the cyclical functions | | | | One of the techniques to improve a prediction |
| with different periods and amplitudes. Some cycles | | | | accuracy is back-testing. It is the process of testing |
| known by investors for long, for example, four-year | | | | prediction on prior time periods. At the beginning, |
| presidential cycle or annual and quarterly fiscal | | | | instead of calculating the prediction for the time |
| reporting cycles. By identifying the cycles it is possible | | | | period forward, we could simulate the forecast on |
| to anticipate tops and bottoms, as well as, to | | | | relevant past data in order to estimate the accuracy |
| determine trends. So that the cycles can be a good | | | | of prediction with certain parameters. Then the |
| opportunity to maximize return on investments. | | | | optimization of these parameters could help to reach |
| It is hard to identify cycles using a simple chart | | | | a better precision in forecast. |
| analysis. | | | | Software makes possible using cycle analysis for |
| It is not easy to analyze the repetition of typical | | | | stock price prediction. |
| patterns in a performance curve because often | | | | To discover different patterns in the price |
| cycles mask themselves; sometimes they overlap to | | | | movement, including cycles, investors use different |
| form an abnormal extremum or offset to form a flat | | | | software tools. They are able to extract basic cycles |
| period. The presence of multiple cycles of different | | | | of the stock market (indexes, sectors, or well-traded |
| periods and magnitudes in conjunction with linear and | | | | shares). To build an extrapolation (i.e., forecast), |
| non-linear trends can form a complex pattern of the | | | | normally they use the following two-step approach: |
| curve. Evidently, a simple chart analysis has a certain | | | | (1) applying spectral (time series) analysis to |
| limit in identifying cycles parameters and using them | | | | decompose the curve into basic functions, (2) |
| for predicting. Therefore, a mathematical statistical | | | | composing these functions beyond the historical data. |
| model implemented in a computer program could be a | | | | Also the best software tools should include |
| solution. | | | | back-testing feature. |
| Be aware: no predictive model guarantees 100% | | | | Conclusion |
| precision. | | | | The stock market is an alive system - around can be |
| Unfortunately, any predictive model has own limit. | | | | joy or fear but its buy-sell pulse always exists. To |
| The major obstacle in using cycle analysis for the | | | | discover different patterns in the market movement, |
| stock market prediction is a cycle instability. Due to a | | | | including cycles, investors use different software |
| probabilistic nature of the market, cycles sometimes | | | | tools. Sometimes, these computer tools are called |
| repeat, sometimes not. In order to avoid excessive | | | | "stock market software." The stock market |
| confidence and, therefore, losses it is important to | | | | software tools help investors and traders to |
| remember about a semi-cyclical nature of the market. | | | | research, analyze, and predict the stock market. |
| In other words, the prediction based on cycle | | | | |