Abstract
A big data Bayesian approach to earnings profitability in the S&P 500
Highlights
Can an earnings announcement provide a volatility arbitrage opportunity that allows an investor to profit from a sudden, sharp drop in implied volatility (IV) that triggers a steep decline in an option’s value? Tan and Bing (2014) developed a methodology that allows an investor to profit from this volatility crush phenomena
This understanding in turn helps traders to formulate strategies that can circumvent the undefined risk associated with trading options strategies such as writing strangles
This study has indicated that an earnings announcement can provide a volatility mispricing opportunity to allow an investor to profit from a sudden, sharp drop in IV
Summary
Can an earnings announcement provide a volatility arbitrage opportunity that allows an investor to profit from a sudden, sharp drop in implied volatility (IV) that triggers a steep decline in an option’s value? Tan and Bing (2014) developed a methodology that allows an investor to profit from this volatility crush phenomena. The strategy allows for shorting strangles while containing the risk associated with this option strategy. This profitable strategy relies on a set of qualifying parameters including liquidity, premium collection, volatility differential, expected market move and market sentiment. Building upon this framework, we investigate the effects of persistence and leverage on reducing risk associated with trading options during earnings announcement, in the post earnings event scenario. We select companies that qualify in terms of liquidity, volume and open interest. We will accept no more than a 10-cent spread
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