Jump-Diffusion Models for Option Pricing versus the Black Scholes Model
Håkon Båtnes Storeng
Abstract
Open-access reader
Håkon Båtnes Storeng
Abstract
Open-access reader
In general, the daily logarithmic returns of individual stocks are not normally distributed. This poses a challenge when trying to compute the most accurate option prices. This thesis investigates three different models for option pricing, The Black Scholes Model (1973), the Merton Jump-Diffusion Model (1975) and the Kou Double-Exponential Jump-Diffusion Model (2002).\nThe jump-diffusion models do not make the same assumption as the Black Scholes model regarding the behavior of the underlying assets’ returns; the assumption of normally distributed logarithmic returns. This could make the models more able to produce accurate results.\nBoth the Merton Jump-Diffusion Model and the Kou Double-Exponential Jump-Diffusion Model shows promising results, especially when looking at how they are able to reproduce the leptokurtic feature and to some extent the “volatility smile”. However, because the observed implied volatility surface is skewed and tends to flatten out for longer maturities, the two models abilities to produce accurate results are reduced.\nAnd while visual study reveals some difference between the models, the results are not significant.
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In general, the daily logarithmic returns of individual stocks are not normally distributed. This poses a challenge when trying to compute the most accurate option prices. This thesis investigates three different models for option pricing, The Black Scholes Model (1973), the Merton Jump-Diffusion Model (1975) and the Kou Double-Exponential Jump-Diffusion Model (2002).\nThe jump-diffusion models do not make the same assumption as the Black Scholes model regarding the behavior of the underlying assets’ returns; the assumption of normally distributed logarithmic returns. This could make the models more able to produce accurate results.\nBoth the Merton Jump-Diffusion Model and the Kou Double-Exponential Jump-Diffusion Model shows promising results, especially when looking at how they are able to reproduce the leptokurtic feature and to some extent the “volatility smile”. However, because the observed implied volatility surface is skewed and tends to flatten out for longer maturities, the two models abilities to produce accurate results are reduced.\nAnd while visual study reveals some difference between the models, the results are not significant.
Key concepts: Jump diffusion, Black–Scholes model, Valuation of options, Logarithm, Jump, Stochastic volatility, Econometrics, Volatility (finance)