Skew as alpha generator?

Moments of distribution play a crucial role in various financial market applications, including risk premia investing. Traditionally, the mean of past returns serves as the foundation for momentum strategies, representing the first moment. Volatility, the second moment, is commonly employed in risk premia strategies. However, instead of measuring risk solely in terms of volatility, a more insightful approach could involve estimating volatility selectively, such as when returns deviate below a mean level (semi-deviation) or turn negative (downside-deviation).

Higher-order moments provide valuable insights into the distribution's departure from Gaussian. Skewness, indicating distribution asymmetry, and positive excess kurtosis, signaling "long tails," are crucial across asset classes.

Skewness, aside from being defined as the third moment of a distribution, measures the asymmetry of the distribution's shape. Skewness, can be further defined as "fractile skewness," a measure that evaluates the asymmetry of a distribution relative to fractile values. Fractile skewness is particularly well-suited for distributions that may contain outliers or extreme values. Unlike traditional measures of skewness, which rely solely on the mean and standard deviation, fractile skewness takes into account the distribution of data across various fractile levels, providing a more robust assessment of skewness, especially in cases where the presence of outliers can significantly impact the overall shape of the distribution.

How can investors harness the profitable trading potential of skewness?

By leveraging investors' aversion to assets with negative skewness and their preference for positively skewed assets, a skewness strategy aims to capitalize on these tendencies through long and short positions, respectively. For instance, both Trend-Following and Skewness, being returns-based strategies consistent across asset classes, present skew strategies as excellent diversifiers to Cross-Asset Trend-Following strategies.

In the Black-Scholes world, with an extension to volatility surface dynamics, skew can be linked to the Vanna second-order derivative, arising from the difference between implied and realized measures of spot/vol correlation, volatility, and volatility-of-volatility. Skew-sensitive products such as Risk-reversals and ratio spreads can be a source of consistent alpha in traded products with naturally positive skew, for example, equity index put options finding a bid and safe-haven currencies like the Japanese Yen (until recently) and the US Dollar. Currencies where the sign of the skew is to some extent persistent over time. The comparison of implied and realized spot/vol correlation reveals close alignment, with realized estimates typically exhibiting higher volatility. Moreover, they find common use among various market participants for hedging and trading purposes. Compared to vol-convexity, skew-related trades exhibit fewer spurious and path-dependent effects, necessitating less intensive monitoring.