Few months ago CBOE released new correlation indexes - instead of the previous terminal expirations coinciding with leaps expirations, now we have normal rolling indexes:
- Tenor Indices (tickers: COR1M, COR3M, COR6M, COR9M, COR1Y), which are calculated using 50 delta implied volatilities and show market expectations of correlation risk over time
- Delta Skew Indices (tickers: COR10D, COR30D, COR3MD, COR70D, COR90D), which are calculated using three-month implied volatilities and signify market expectations of correlation during different delta shock scenarios
This conceptually makes sense, but I wish that CBOE would explicitly write out the formulas when they updated the whitepaper
Correlation, like volatility is not static, and implied correlation is an important market stress indicator, just like VIX. Different market conditions cause widening or narrowing of the spread between implied volatility of index and its constituent options, which has important implications for PL of statistical arbitrage strategies - in options ( dispersion trading ) but also for stocks statistical arbitrage.
Lower correlation means greater dispersion - and more opportunity to trade on mean-reversion of idiosyncratic movements. Medium frequency stat arb PL tends to be correlated with implied correlation, however high frequency tends to do better in the periods of high volatility, so the relationship is quite complex.
Finally, there is a macro angle: we have been in a bear market lately, and it’s fairly common in bear markets for correlations to relax. The chart below depicts the 1 Month CBOE Implied Correlation Index from 2006 until now, and we can plainly see that COR1M is very correlation with VIX, but not identical. As we can see from the graph, the correlation is in an uptrend; rising from a low of 13 the the start of the year to over 50.
Delta Skew Indexes are something completely new, allowing for calculation of correlation skew. Note - all delta skew indexes have 3 months tenor. I tried plotting 10 delta vs 90 delta indexes on the CBOE website, but the chart is a mess.
I downloaded the data for correlation indexes to construct the chart below - 10-90 correlation skew, and 3 month moving average. Maybe in the later posts I will try to write more about correlation skew, and how it can be used as a macro trading indicator.
Russian people are not slaves, they have a choice. In 2014 Olga Simonova outraged at Russia's occupation of Crimea bought a one-way ticket to Ukraine and became a paramedic with the Ukrainian Armed Forces. A week ago she was killed at the frontline.
Alexander Adamchuk is someone I have met several times - he was heavily involved with the U of Chicago Financial Mathematics program, curriculum and events. When rockets were raining on Ukrainian cities, he posted the following on linkedin
Translation with my comments to explain references in parenthesis:
Russian America is a part of GREAT RUSSIA
FOR THE REUNION ( spelled with extra "Z" )
Kingdom of Poland
Kingdom of Lodomeria ( in western Ukraine)
Russian Galicia ( also in western Ukraine)
For Russia ( spelled with extra "Z" )
great and multifaceted,
Ours is the Small Land ( Малороссия - central Ukraine )
and the New Land ( Новороссия - southern Ukraine )
and the New World ( Alaska )
