| 摘要 |
A method and product for identifying and categorizing pivot points in a time series, such as a time series of financial data (e.g. stock prices) or medical data (e.g. ECG, EEG). The method permits categorization of pivot points in a time series according to their spatial importance and temporal occurrence. The time series has a predetermined end point, predetermined maximum and minimum box sizes, and a predetermined box size increment. The method consists of determining a breakout direction for the time series. Then, for each incremental box size from the maximum to the minimum, pivot points are identified. Commencing at the end point and working backwards through the time series, any point where a reversal of more than the current box size occurs is identified. For each such identified point, the previous extreme, its associated lag from the end point, and the box size at which it is first identified is then recorded
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