The Trading Performance of Dynamic Hedging Models: Time Varying Covariance and Volatility Transmission Effects

Michael T. Chng () and Gerard L. Gannon
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Michael T. Chng: Deakin University
Gerard L. Gannon: Deakin University

Chapter 61 in Encyclopedia of Finance, 2022, pp 1411-1435 from Springer

Abstract: Abstract In this chapter, we investigate the value of incorporating implied volatility from related option markets in dynamic hedging. We comprehensively model the volatility of all four S&P 500 cash, futures, index option and futures option markets simultaneously. Synchronous half-hourly observations are sampled from transaction data. Special classes of extended simultaneous volatility systems (ESVL) are estimated and used to generate out-of-sample hedge ratios. In a hypothetical dynamic hedging scheme, ESVL-based hedge ratios, which incorporate incremental information in the implied volatilities of the two S&P 500 option markets, generate profits from interim rebalancing of the futures hedging position that are incremental over competing hedge ratios. In addition, ESVL-based hedge ratios are the only hedge ratios that manage to generate sufficient profit during the hedging period to cover losses incurred by the physical portfolio.

Keywords: Volatility transmission; Dynamic hedging; Optimal hedge ratio; S&P 500 (search for similar items in EconPapers)
JEL-codes: G14 G28 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-91231-4_61

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DOI: 10.1007/978-3-030-91231-4_61

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