Methodology

Back to Linear Regression Slope

I wanted to do more work on presentation, and calculating this properly was not simple. At the moment, XLQ is doing the calculation on what it calls the weighted price (Open + High + Low + Close) / 4. I was unable to get the Excel Slope function to return correct results, must be some mistake I’m making. That’s not simple to test but XLQ results matched Tradestation and Stockcharts.

Anyway, the results look pretty good from the end of 2017 until now. That is a good period for this strategy.

ETF Summary

The strategy returns 60.8% better than buy and hold did, makes me afraid to look at other time periods. The returns could have been enhanced by not trading XRT or XLU, 2 industries not many would argue about dropping – there is still exposure to those groups with the major market ETFs.

Industrials Summary

This doesn’t include DWDP, the downloading software was giving me grief about it earlier, so I took it off the list. These results are quite good, but obviously not as spectacular as the ETFs.

Observations

My current theory on why ETFs outperform individual stocks: individual stocks have more down movement at the end of a move, that is somewhat mitigated by strength rotation among similar securities in an ETF.

This strategy (and the rate of change) is quite robust. It is quite unusual to see a strategy play so many different stocks well.

I was surprised to see I had developed the game framework (momentum averaging) several years ago to play the MACD Histogram and had forgotten about it. There are multiple possibilities for the strategy to be improved.

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