Tag: quant

Volatility Lookbacks

Volatility is calculated over a time period – the lookback. While developing a strategy, it is typical to try a range of lookbacks and pick one that looks reasonable for the strategy being built. However, is there an “ideal” lookback period?

This is where a volatility signature plot comes into the picture. It is typically used in high frequency trading but there is no reason not to use it on a lower frequency time series.

If you plot the distribution of volatility over different lookbacks, this is how it looks:

Ideally, you want the box to be small, the median in the middle and the wicks to be short. After all, if you are using volatility to drive a strategy, if the distribution of volatility itself is too wonky, then how do you trust the output?

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Correlation Timing

The previous post discussed how high correlation environments have fat left-tails. Can correlation states be used for timing?

A quick look suggests that it might not be possible. Both LO (long-only) and LS (long-short) strategies that use the correlation state seem to underperform buy-and-hold.

There was some “crisis alpha” in using correlation for timing during the COVID crash of 2020. However, Buy & Hold ruled the roost both before…

… and after things normalized.

The slightly better drawdown performance of LO in some circumstances might be interesting for levered investors but the unlevered returns of these timing strategies are not much to write home about.

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Correlation vs. Returns & Volatility

The previous post presented historical NIFTY 50 constituent pair-wise correlation distributions and discussed how high correlation environments persist. How do the 5th-quintile return and volatility look like?

If you focus on the 5, 10 and 20-day pair-wise correlations (T5, T10 & T20), you’ll see large left-tailed returns and high volatility in the 5th quintile compared to the others (1st, 2nd, 3rd & 4th).

Looking at this the other way, T10 – the 10-day pairwise correlation – has this profile:

It looks like if you dodge the 5th quintile here, you might be able to boost returns in linear strategies.

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Index pair-wise Correlation

Sometimes, it feels like all stocks in an index are moving in the same direction. Very rarely is there full “chaos.” Sometimes, even when there is some dispersion, it is overshadowed by larger moves in a few index heavy-weights. To get some intuition around this, we calculated the pair-wise correlation of the NIFTY 50 constituents since 2015 across different lookbacks, bucketed the median daily correlations into quintiles and plotted them.

If you do an rle, you’ll get an idea about the number of consecutive days spent in each quintile. It looks like quintile 5, representing a highly correlated state, is sort of sticky.

For example, if you zoom into the 20-day lookback distribution, notice how quintile 5 stands out.

It appears that low-correlation environments are actually not that sticky. So, if you see a quintile 5 form, bet on it lasting a few days.

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