Be Careful of Big Years

While doing research on a mean reversion strategy, I was really happy with the Compounded Annual Returns (CAR) of 51%. I was thinking, I may have a new strategy to add to my stable of trading of trading strategies. A big fact I liked was the strategy used no market regime filter.

Then I looked at the yearly returns. The 2020 return through July 31 as 444%! How much did the CAR depend on this year’s numbers?

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The importance of testing different exits

When developing a strategy, exits are often not given a second thought. If you are creating a mean reversion, you may default to using Close greater than the 2-period RSI. If you are trading a trend strategy, you may default to trailing exit using 14-day ATR. You try a bunch of entry filters but rarely try a different exit. Or maybe a slight change in the exit.

If you are having success, with your strategy. You think great and don’t change the exit. If you are not getting anywhere, you think well this idea did not work and stop testing.

A slight change in your exit can have a huge impact on the results as was driven into me during some recent research. I am guilty of not be as thorough in my testing of exits as I should be. Hopefully, this will convince you to look at them more at the beginning of your research.

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How to turn off a strategy using historical volatility

A very common question I get, is “when should I turn off a strategy?” Given the very volatile markets we have had the last few months, I can relate. Some strategies can thrive in these high volatility markets. While others can suffer.

In the June 2020 issue of Technical Analysis of Stocks and Commodities, Perry Kaufman writes an article about using the historical volatility of the equity curve to decide when to turn off a strategy. I always read Perry’s articles because they are full of good ideas and this was another one that I liked and had not tried before.

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S&P 500 Dividend Aristocrats

Back in 2018, I wrote a post, Backtesting a Dividend Strategy, which was conceptually based on the S&P 500 Dividend Aristocrats. Just recently, Norgate Data started offering historical constituent data for the S&P 500 Dividend Aristocrats index. This would be a much ‘cleaner’ version compared to what I was trying to do in my original post. Would using this index produces better results?

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Market Cap vs. Crash Severity

Has the market sell-off and subsequent bounce treated all stocks the same? A good portion of the bull market move from 2009 to 2019 has been led by the big-cap stocks. Did they hold up better during the March sell-off? What about with the bounce? Did the smaller-cap stocks have a bigger bounce?

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Correlations go to One

There is a saying: “in bear markets correlations go to one.” I wanted to see how true that is for both stocks and a basket of ETFs. Now they don’t go to exactly one, not that I expected that, but they take some large steps towards one.

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Escalator on way up. Broken elevator on the way down.

I have been waiting for a close under 2350 to write this post. Today the $SPX closed at 2304.92.

Markets slowly grind up. But crash quickly. How quickly? I will be looking at each new drawdown low since the market top on February 19, 2020 and then seeing how many days of market gains were erased since the previous time

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Trading Multiple Strategies

Using strategy diversification is one of the easiest ways to improve the performance and reduce risk of your overall portfolio. Trading one strategy is risky because you never know when it may stop working or simply go into a period of under-performance.

Given two strategies to trade, the questions I have are, what is the performance of trading them together? What percentage of the total portfolio should be allocated to each strategy? How often should I rebalance that allocation?

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Market will be up 9.7% in 3 months!

When this sell-off indicator triggers, it is correct 100% of the time! On average the market is up only 2.6% in 3 months.

OR NOT!

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Inverse Volatility Sizing Index

In my last post, Inverse Volatility Position Sizing, I tested inverse volatility sizing on a monthly rotation strategy. I saw very little difference in the rest results versus equal position sizing. I was talking to a trading friend about the research and how I was surprised at how there was not any difference in the results. He suggested creating an index using this method.

Now, this sounded like an idea with good potential. And even better it should be easy to test since I had the code written already.

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