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Pricing and Hedging European Energy Derivatives: A Case Study of WTI Oil Options[Note 1. The reported numbers are the average quoted bid‐ask mid‐point ...]
Author(s) -
Hsu ChihChen,
Lin ShihKuei,
Chen TingFu
Publication year - 2014
Publication title -
asia‐pacific journal of financial studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 15
eISSN - 2041-6156
pISSN - 2041-9945
DOI - 10.1111/ajfs.12050
Subject(s) - mean reversion , economics , jump diffusion , valuation of options , financial economics , rational pricing , econometrics , west texas intermediate , volatility (finance) , spot contract , commodity , black–scholes model , capital asset pricing model , futures contract , jump , finance , physics , quantum mechanics
This study extends the mean‐reversion dynamic framework of (Pilipovic, Energy risk: Valuing and managing energy derivatives, 1997) and (Schwartz, The stochastic behavior of commodity prices: Implications for pricing and hedging, Journal of Finance 52 , 1997, 923) and focuses on developing a variety of continuous‐time commodity‐pricing and hedging models by analyzing the pricing and hedging errors found in an empirical investigation of options contracts on light sweet crude oil traded on the New York Mercantile Exchange. Thus, this study contributes to furthering the applicability of the models developed. The inclusion of the benchmark Black‐Scholes pricing model generates systematic biases that are consistent with (Bakshi, Cao and Chen, Handbook of Quantitative Finance and Risk Management, 2010). The mean‐reversion jump‐diffusion and seasonality option‐pricing model best describes the extreme price volatility experienced during a financial collapse, but the mean‐reversion and seasonality option‐pricing model offers the best pricing and hedging capability for other periods. The performances of hedging models are generally consistent with pricing errors.