Description
Seasonal Trading is a strategy designed by Perry J. Kaufman in an attempt to explore seasonal patterns in stock price. The strategy analyzes monthly price action using the Monthly Seasonality study and adds simulated buy and sell orders based on the resulting values. As monthly action is taken into account, this strategy is to be used on monthly charts only.
Calculation
The price data is run through Monthly Seasonality to reveal seasonal patterns and identify the months with the highest and the lowest frequency of positive returns. The default level of high positive-return frequency is 75. For low positive-return frequency, the default level is 25. The frequency is calculated for each month over the last four years by default.
Simulated orders
Seasonal Trading adds simulated orders according to the following rules:
- A Buy simulated order is added at the end of a month with a consistently low frequency of positive returns.
- A Sell simulated order is added at the end of a month with a consistently high frequency of positive returns.
Input Parameters
| Parameter | Description |
|---|---|
years | The period for which the frequencies of positive returns for each month are to be calculated. |
high frequency | The minimum high-frequency level. |
low frequency | The maximum low-frequency level. |
Further Reading
1. "A Simple Way To Trade Seasonality" by Perry J. Kaufman. Technical Analysis of Stocks & Commodities, September 2019.
Backtesting is the evaluation of a particular trading strategy using historical data. Results presented are hypothetical, and there is no guarantee that the same strategy implemented today would produce similar results.
Technical analysis is not recommended as a sole means of investment research.
For educational purposes only. Not a recommendation of a specific security or investment strategy.
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