In one of the final sessions today at CBOE RMC Europe Riddhi Prasad from Deutsche Bank and Arne Staal of Standard Life Investments delivered a talk titled Designer Dispersion: Identifying Optimized Risk Premium.
The pair discussed dispersion trades for extracting risk adjusted value which is separate from the volatility risk premium. They also discussed what drives performance in different volatility regimes. By ‘designer dispersion’ they are referring to using optimized approaches to create hedges. They also shared views on systematic and quantitative approaches versus more fundamental or tactical approaches.
Dispersion trading has not been a traditional focus of the conversation at RMC, bu this year it has come up many times. Riddhi’s presentation concluded with some myths that are related to dispersion trading. I felt these were worth sharing in this space.
Myth 1- Dispersion trades are most sensitive to implied correlation levels. This is not true and she showed that there are several instances of profitable dispersion trading at medium and low volatility levels.
Myth 2 – Dispersion trades are high risk in deep market sell offs. Once again, she demonstrates this is untrue, but also notes that dispersion trading profit or losses are convex when related to downside market moves as measured by the Euro Stoxx 50.
Myth 3 – Dispersion trading involves having a view on many single stocks. She shows that a large portion of stock dispersion happens at the industry level and that there are global opportunities using exposures to different regions.
Myth 4 – Optimized dispersion cannot incorporate market thematic views. To debunk this my she shows a dispersion trade that benefits from an outlook on the oil market.
Myth 5 – Liquidity constraints render dispersion trades unattractive at large size. She has worked with the trading desk to show that the cost of implementing a large dispersion trade is commonly in line with trading costs associated with other types of trading.