SVI Volatility Surfaces and Luck in Mutual Fund Performance

Summary

This research roundup describes two separate studies. The first examines the Stochastic Volatility Inspired (SVI) parameterization for modeling implied volatility surfaces. It reports theoretical results and empirical analysis suggesting that, under specified constraints, SVI can produce surfaces that fit observed data while avoiding arbitrage. The document does not provide the model equations, dataset, or details of the constraints, so readers cannot assess the fit or reproduce the analysis from this page alone.

The second study argues that luck, rather than fund managers’ skill, explains the excess returns of most funds. The page gives no methodology, sample, statistical tests, or quantitative findings to evaluate that claim. It is therefore best read as a brief guide to two papers rather than as a self-contained treatment: researchers interested in volatility modeling or fund evaluation would need the linked source material for assumptions, evidence, and limitations.

Key ideas

• The roundup presents SVI as a parameterization for implied volatility surfaces.
• The reported results associate constrained SVI surfaces with accurate fitting and absence of arbitrage.
• A separate study attributes most funds’ excess returns to luck rather than manager skill.
• The page omits the methods and evidence needed to independently evaluate either study.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.