Cross-Region and Cross-Asset Volatility Analysis for Investing and Hedging

During the second session on Day 3 at CBOE’s Risk Management Hitendra Varsani, Head of Quantitative and Derivative Strategies from Morgan Stanley teamed up with John Moffatt, Portfolio Manager of the World Index Book from Capstone to discuss Cross-Region and Cross-Asset Volatility Analysis for Investing and Hedging.

Varsani began the session discussing the history of options noting the first option trading we know of involved the philosopher Thales in ancient Greece.  He cornered the olive press market through purchasing options for their use in anticipation of a bountiful harvest.  He then fast forwarded to 1973 with the creation of CBOE also mentioning milestones such as the creation of VIX derivatives.

After discussing the history of options Varsani moved on to talking about volatility risk premia in different markets such as equities, commodities, foreign exchange, and bonds.  He touched on unique characteristics of each market such as equities offering the most alternatives and that fixed income markets have a consistent flow of hedging demand from different market participants.

In the second section of Varsani’s presentation he notes the spillover effects of volatility events in different market sectors.   He noted that paying attention to a broad range of asset classes can help forecast potential volatility in different sectors.  For example there was an increase in volatility in different markets in late July and early August of 2015 that may have served as a warning for the equity market sell off in late August.

John Moffatt then took the stage to discuss how supply and demand imbalances impact equity index volatility surfaces globally.  He notes the imbalances have been around for years, he just notes they have recently become more pronounced.  He addressed skew and noted there are many different methods of measuring skew, but all measures tend to show very similar patterns.  His preference is to combine different measures of skew when analyzing the markets.

He notes that trading skew is a dynamic process and often a skew trade may turn into a vega trade if the market moves.  The S&P 500 has historically had the highest skew while most Asian skew curves are flatter than the US curve.  He cites the popularity of auto callable products in Asia contributing to the flatter skew in that region.  Turning back to the US he noted that skew has been trending higher for over 10 years.  He attributes the increase in skew to some regulatory changes in the US that may have inadvertently resulted in less supply of downside puts.  Rounding out a look at global skew, Moffatt noted that skew has been flattening in Europe which may be influenced by increased use of structured products and bullish sentiment toward Europe in the equity markets.