Pricing and hedging competitiveness of the tree option pricing models: Evidence from India

Vipul Kumar Singh ()
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Vipul Kumar Singh: National Institute of Industrial Engineering (NITIE)

Journal of Asset Management, 2016, vol. 17, issue 6, No 5, 453-475

Abstract: Abstract The study focusses on the price convergences, implied volatility structures, and hedging competencies of the discrete tree options pricing models. In addition, the paper also studies the efficiency of optimization techniques involved in the calibration of discrete time models. The process involves matching of quoted market option prices with the model prices – relied on the assumption that there are sufficiently large numbers of liquidly traded options. To minimize the price bias between the model and market, this paper uses Differential Evolution and Simulated Annealing methods of optimization. To benchmark, price statistics of European-style Nifty index options and American-style stock options traded on the National Stock Exchange (the world’s third largest Futures and Options exchange) of India have been used. The concepts of optimization and relative pricing are used to demonstrate the price effectiveness of the tree models with respect to continuous-time classical options pricing model of Black–Scholes–Merton. The outcome of the research reveals that the pricing and hedging errors of forward-inducted implied that binomial and trinomial trees are stable and lower with Simulated Annealing methods of optimization than their backward-inducted counterparts.

Keywords: binomial; Black–Scholes; implied volatility; Nifty index; options; optimization; trinomial (search for similar items in EconPapers)
JEL-codes: C53 C55 C61 C63 (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1057/s41260-016-0024-5

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