SPY: Impact of Correlation

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With this post I want to share some very interesting research insight from the world of correlation.  Correlation metrics get a lot of attention during severe bear markets. That's because most markets go down together, hence correlation is raising among the various markets and asset classes. Conventional market wisdom says: high correlation among markets and assets classes is a sign of fear.  But what about the opposite?  So I wanted to understand if conventional wisdom is right and what short-term impact correlation has on the US stock market and how to use this in my trading.

Background

  • SPY is used as a proxy to trade the US stock market.
  • Data is adjusted for cash dividends and splits
  • Tests don't consider trading cost / slippage
  • History: January 1993 – February 2012

I calculated correlation among all SP500 members (survivorship bias free)  using daily bars. The calculation is conducted after the last trading day of the week has finished, that's most likely Friday. The actual trade is taken the next day @OPEN, that's most likely Monday. The trade is then held until next week (Monday). No other stops  or exists are used.

In the second column of each test you find a benchmark value. That is the strategy as described until here without any filter or market timing components. So we end up with almost 1000 trades, hence the benchmark strategy is 100% invested. The following columns show weekly returns (=weekly trades) under different correlation conditions.

Test 1: Looking at absolute correlation levels

The test is dividing the correlation measure into quartiles. We see very little difference among the first two buckets where the market is in 90+% of the time. Though high (peak ) correlation has a positive impact on next week's performance.

Test 2: Higher or lower correlation

For this test we look into falling or raising correlation regardless of it's absolute level. Friday's level  compared to previous day (t-1) or five days ago (t-5).  There is a significant difference in performance and risk adjusted measures.

Weeks after falling correlation are way better than weeks after raising correlation!

Test 3: Using relative strength or weakness

In the final test we look at the RSI2 level of the average market correlation. RSI2 has the advantage that it's less binary compared to looking at absolute changes to previous days. I think the results are outstanding! Being invested in weeks after RSI2 is bellow 25 delivered higher returns than the benchmark strategy while only being invested 38% of the time. Furthermore volatility is reduced significantly. The benchmark strategy had a max. drawdown of about 55% while the RSI2<25 strategy had  21% only.

A picture says more than thousands word

Now the pessimists among us might ask if this is time stable?

Let me know what YOU think about this test or how YOU use correlation in your trading.

Should you be interested in a weekly correlation outlook ,then read my weekly 360° view here.

# Frank

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