Double Momentum Investing

With our Double Momentum Investing (DMI) strategy, we will look for the best of two worlds. As the name suggests, it is a trend following strategy. Trend-following strategies are based on the finding that throughout the different stock market cycles, the probability that a trend will continue is greater than the probability that the trend will reverse.

This strategy is similar to the Dual Momentum Investing Strategy, introduced by Gary Antonacci. We could not reproduce the results with the dual momentum strategy as described in the book. In fact we found no better results with that strategy than with the best of the underlying ETF’s. So we made some adaptations. Because of this we gave the strategy a different name: Double Momentum Investing strategy. And, of course, we will perform rigorous backtesting calculations on our own strategy as well.

For our back tests we start with a cash amount of 100 ($, €,…). Calculations are made with the adjusted closing price (hereafter simply referred to as the closing price). With DMI, we compare the closing price of the previous trading day with the closing price of x number of days earlier on each trading day. We call this “x number of days” the interval. The closing price on that day is the reference price. We compare this difference between price of the previous day and reference price for two ETF’s/indexes.

We will buy or stay in the ETF, for which the difference between previous day closing price and reference price is highest. Unless this difference is smaller than zero. In that case we will sell our ETF’s or stay in cash.

We will make an estimate of the impact of transaction costs and we will answer the question whether following up your investments daily is necessary to obtain the best results.

In the last part of the analysis of the DMI strategy we will perform out-of-sample tests. For these tests we calculate the optimal interval for a period in the past. Next we apply this optimal interval in the subsequent period and calculate the return and maximum breakdown. These out-of-sample tests will give us an indication of the predictive value of the applied strategy.

The analysis can be found under this link: