Description
Simple Mean Reversion is a strategy created by Anthony Garner. It is based on the theory that when prices move too far away from the mean, there is a chance of price reversion. The strategy adds simulated buy and sell signals based on the following values: price, two simple moving averages, and zScore. The latter is the ratio of the difference between the price and its average to the standard deviation of the price.
The strategy adds simulated orders based on the following conditions:
- Buy to open: zScore falls below -1.0 while the faster SMA is above the slower one;
- Sell to close: zScore rises above -0.5;
- Sell to open: zScore rises above 1.0 while the faster SMA is below the slower one;
- Buy to close: zScore falls below 0.5.
By default, the faster SMA has the length equal to the length with which zScore is calculated. The slower SMA has the length ten times the length of zScore. All the mentioned numbers can be customized in the input parameters.
Input Parameters
|
Parameter |
Description |
|---|---|
price
|
The price for which the averages and zScore are to be calculated. |
length
|
The length with which zScore is to be calculated. |
fast length factor
|
The factor by which length is to be multiplied to obtain the length of the faster moving average.
|
slow length factor
|
The factor by which the length is to be multiplied to obtain the length of the slower moving average.
|
z score entry level
|
Defines the critical value of zScore for triggering a simulated sell-to-open order. For simulated buy-to-open orders, the opposite number is used. |
z score exit level
|
Defines the critical value of zScore for triggering a simulated buy-to-close order. For simulated sell-to-close orders, the opposite number is used. |
Plots
|
Plot |
Description |
|---|---|
FastMA
|
The fast moving average plot. |
SlowMA
|
The slow moving average plot. |
Further Reading
1. "Backtesting A Mean-Reversion Strategy In Python" by Anthony Garner. Technical Analysis of Stocks & Commodities, May 2019.