Footnote:
In: Applied Economics, Volume 50, Issue 10, pp. 1122-1137
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments July 11, 2017 erstellt
Description:
This paper investigates the pricing/hedging conundrum, i.e. the observation of a mismatch between derivatives models' pricing and hedging performances, that has so far been under-emphasized as the literature tends to focus on increasingly complicated option pricing models, without adequately addressing hedging performance. Hence, we analyze the ability of the Black-Scholes, Practitioner Black-Scholes, Heston-Nandi and Heston models to Deltahedge a set of call options on the S&P500 index and Apple stock. We extend earlier studies in that we consider the impact of asset dynamics, apply a stringent payoff replication strategy, look at the impact of moneyness at maturity and test for the robustness to the parameters' calibration frequency and Delta-Vega hedging. The study shows that adding risk factors to a model, such as stochastic volatility, should only be considered in light of the data dynamics. Even then, however, more complicated models generally fare poorly for hedging purposes. Hence, a better fit of a model to option prices is not a good indicator of its hedging performance, and so of its ability to describe the underlying dynamics. This can be understood for reasons of over-fitting. Those findings hint to a potentially appealing hedging-based calibration of models' parameters, rather than the standard pricing-based one