Leveraged ETFs Research: Volatility Skew

I have blogged before about inverse and leveraged ETFs, about how their performance depends on their volatility, and also about pricing options on these ETFs. While I try to focus specifically on original research, here are some important research publications from academia, along with my comments.

Volatility skew of leveraged and inverse ETFs is a topic that is dear to my heart - I recently left a trading firm that specializes in volatility arbitrage in ETF space, where over the past year I conducted mathematical research and developed software to create a comprehensive trading system. It is now in production on (almost) all US optionable ETFs. Unfortunately my contract prevents me from disclosing any details about my own research.

1 Dr Jian Zhang thesis, which I believe is the first publication to address correct pricing of LEFT options. I wrote about shortcomings of his three approaches in my previous post.

2 Consistent Pricing of Options on Leveraged ETFs by Andrew Ahn, et al, first provides an important generalization for pricing LEFT options, applying it to Heston model, and also 2 jumps models via Monte-Carlo. They show experimentally model-dependency (that results from path-dependency) for pricing LEFT options.

3 Most recent, is Implied Volatility of Leveraged ETF Options by Tim Leung and Ronnie Sircar. They apply stochastic volatility-based iv asymptotics framework developed in Multiscale Stochastic Volatility for Equity, Interest Rate, and Credit Derivatives, which is an excellent book! Authors also address the issue of different volatility premiums across related products.

4 Structural Slippage of Leveraged ETFs by Doris Dobi and Marco Avellaneda "shows" that you can make money by shorting ETFs and capitalizing on slippage. Despite their findings I don't this that there are any serious money to be made here - 1 borrowing costs are collected from a retail, not institutional broker, 2 actual borrowing costs are not known until stock settles, 3 execution slippage is usually highest at the time of greatest ETF decay. 

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