Title :
A jump diffusion model for option pricing with three properties: leptokurtic feature, volatility smile, and analytical tractability
Author_Institution :
Dept. of Ind. Eng. & Oper. Res., Columbia Univ., New York, NY, USA
Abstract :
Brownian motion and normal distribution have been widely used to study option pricing and the return of assets. Despite the successes of the Black-Scholes-Merton model based on Brownian motion and normal distribution, two puzzles which emerged from many empirical investigations, have had much attention recently: 1) the leptokurtic and asymmetric features; 2) the volatility smile. Much research has been conducted on modifying the Black-Scholes models to explain the two puzzles. To incorporate the leptokurtic and asymmetric features, a variety of models have been proposed. The article proposes a novel model which has three properties: 1) it has leptokurtic and asymmetric features, under which the return distribution of the assets has a higher peak and two heavier tails than the normal distribution, especially the left tail; 2) it leads to analytical solutions to many option pricing problems, including: call and put options, and options on futures; interest rate derivatives such as caplets, caps, and bond options; exotic options, such as perpetual American options, barrier and lookback options; 3) it can reproduce the “volatility smile”
Keywords :
costing; finance; modelling; normal distribution; Black-Scholes-Merton model; Brownian motion; analytical solutions; analytical tractability; asymmetric features; bond options; empirical investigations; exotic options; futures; interest rate derivatives; jump diffusion model; leptokurtic feature; lookback options; normal distribution; option pricing; option pricing problems; perpetual American options; put options; return distribution; return of assets; volatility smile; Chaos; Cities and towns; Contracts; Economic indicators; Floors; Fractals; Gaussian distribution; Pricing; Probability distribution; Web pages;
Conference_Titel :
Computational Intelligence for Financial Engineering, 2000. (CIFEr) Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-7803-6429-5
DOI :
10.1109/CIFER.2000.844610