This study tests the traditional MACD indicator and derived two methods, MACDR1 and MACDR2 (R: Refinement), which significantly improve the MACD trading results and outperform the benchmark of holding a no-risk security, the Treasury bond and holding the underlying instrument, the NASDAQ-100. A big problem when testing technical analysis rules is the aspect of data snooping, which increases the chance of falsely rejecting the null hypothesis, which in this study is the random walk hypothesis of no predictability.
To address data-snooping concerns, the methods MACDR1 and MACDR2 are derived from data of the Dow Jones Industrial Average from May 30, 1989 to May 30, 1999. The methods were derived firstly by simple visual observation of the functioning of the MACD indicator and then by numerical trial and error calculations. The methods were then tested out-of-sample for the NASDAQ-100 stocks, individually, for the same 10-year time period. Altogether, this study uses 314,645 daily closing prices and 92,328 resulting buy and sell signals to verify the methods involved.
Model MACDR1
A crucial issue when using moving averages is to determine the correct timing of the opening purchase or sell. The first model, called MACDR1, attempts to eliminate buy and sell signals when the averages MACD1 and the Signal are crossing each other frequently in a short period of time, thus in a case, where there is no clear trend. Instead, the trading signal is given three days after the actual crossing if the trend is still intact.
Thus, the position is opened at the closing price of the third day after the crossing, if no crossing has appeared on day 2 and 3. A further important issue is to close the trade at the right point in time. Since the MACD indicator is a lagging indicator, the reversal of a successful trade is often done too late, especially because a trend reversal often happens very quickly. This fast reversal is hard to anticipate, but it is devastating when failed to predict, because the first few days after the reversal often have the most significant price move.
Model MACDR1 (and model MACDR2) resolve this problem by indicating a closing signal when a predetermined profit has been reached. In this study we test profit levels of 3% and 5%. Thus, the models gives a signal to close an open position when a 3% or 5% target gain has been reached or if another crossing occurs before the target is reached. A lower target will naturally be reached more often but there is an opportunity cost involved when closing a position too early and missing out on bigger profits.
Model MACDR2
Model MACDR2 is a further refinement of method MACDR1. Method MACDR2 produces trading signals when the trend is stronger than method MACDR1. It naturally generates fewer buy and sell signals than model MACDR1, but it has a higher success rate for each trade. The basic concept of model MACDR2 is the same as in model MACDR1.
However, the buy or sell signal is given, if the difference between the moving averages is bigger or equal than a certain percentage of the stock price at the end of the third day after a crossing. We test crossing-levels from 0.5% to 3.5%. For levels over 3.5%, hardly any trading signals occur. To illustrate method MACDR2, let’s assume the stock price is $100, the MACD1 = 2 and the Signal = 1 on the third day after a crossing. The difference between the averages is 1, which is 1% of the stock price. This would generate a trading signal for crossing-levels bigger or equal than 1%. This method assures that the stock movement at the beginning of a trend is significant and not a random movement in a narrow trading range.
In this study, the correlation between model MACDR2 and the volatility of each stock as well as the market capitalization of each stock are tested. Furthermore, it is shown that the trading results can be improved significantly, when combined with option trading. We also test if the results of the traditional MACD indicator and our method MACDR2 can be improved when moving averages of different time lengths are used.
Finally, we compare the outcome of the method MACDR2 with two benchmarks, the risk-less Treasury bond and the underlying instrument, the NASDAQ-100 to challenge the random walk hypothesis.
Gunter Meissner, Albin Alex and Kai Nolte
Next: Results
Summary: Index