Discusses basic issues and results when attempting to back-test the Directional Movement formula.
Data: S&P500 Emini Futures
Futures Contract Rollover: Arbitrarily set on second Friday of every Mar, Jun, Sep and Dec
Period: 28 Dec 2008 - 31 Mar 2012 (Hourly Chart)
VBA Code: Method B of Code
Excel Version: 2010
Note: 1) As with the Aroon Indicator, the Directional Movement can be used for other time frames and not necessarily daily data as is the context when I wrote the Directional Movement explanation page.
2) The directional movement indicator refers to an implementation of the directional movement formula. What this page attempts to do is to backtest the directional movement formula, not the directional movement index and also not the directional movement indicator. Return to the technical analysis page for links to the respective indicators, codes and backtest results.
Click here for background information, formula, calculation steps and the entire VBA code.
There are multiple variations on how to apply an indicator. I seek your understanding that the work done below are experiments and are for information purposes only.
Results Summary
Divergence does not signify that a trend is forming in the hourly charts based on my dataset. I inverted this trading rule and arrived with a strategy that is profitable before transaction costs, as expected. Given the large number of trades generated, the naive trading rule applied will most likely not be profitable after costs. The interesting fact is that this is the second or third indicator I found where the usual trading rule I read from other sources has to be inverted in order for the strategy to even show before transaction cost profitability.
Results Summary
Divergence does not signify that a trend is forming in the hourly charts based on my dataset. I inverted this trading rule and arrived with a strategy that is profitable before transaction costs, as expected. Given the large number of trades generated, the naive trading rule applied will most likely not be profitable after costs. The interesting fact is that this is the second or third indicator I found where the usual trading rule I read from other sources has to be inverted in order for the strategy to even show before transaction cost profitability.
Procedure in Brief
Pasted the code into Excel with changes made as per comments in code to direct application to ranges with input data (High, Low, Close columns). Screen Shot 1 shows the output (the last four columns). |
| Screen Shot 1 |
Detailed Findings and Results
Summary of Trading Rules -
1) Calculate Positive DM Minus Negative DM. Recall that Negative DM is a positive value. Negative refers to the fact that a new low was created in the current bar.
2) If (Positive DM Minus Negative DM) is greater than 0, Long
3) If (Positive DM Minus Negative DM) is lower than 0, Short
4) Else maintain long or short position
517 index points of profit (before transaction costs) were generated on a large set of 6,687 trades. Average return is very small at just 0.08 points per trade, which means that such an application will not cover trading costs for most people (I guess?). 59% of trades were profitable. Standard deviation of returns for each trade is 4.93 points. The profit trajectory of this indicator and trading rules is shown in Chart 1.
 |
| Chart 1: Cumulative Profit of Strategy (Before Costs) |
Conclusion
Although this application of the DM generated a lot of trades, just like my attempt with the Aroon Indicator, the trading rule in this case did not generate statistically significant profitability based on the student t statistic. The low per trade profitability of this approach negated the statistical effect of a large number of trades in reducing standard error. I end this post at this juncture as we will be using this Directional Movement formula in various forms when backtesting the directional movement index and the directional movement indicator. More can be elaborated then.
Any suggestions or comments are welcome.
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