TY - CHAP

T1 - Empirical performance of the constant elasticity variance option pricing model

AU - Chen, Ren Raw

AU - Lee, Cheng Few

AU - Lee, Han Hsing

N1 - Publisher Copyright:
© 2021 by World Scientific Publishing Co. Pte. Ltd.

PY - 2020/1/1

Y1 - 2020/1/1

N2 - In this chapter, we empirically test the Constant-Elasticity-of-variance (CEV) option pricing model by Cox (1975, 1996) and Cox and Ross (1976), and compare the performances of the CEV and alternative option pricing models, mainly the stochastic volatility model, in terms of European option pricing and cost-accuracy-based analysis of their numerical procedures. In European-style option pricing, we have tested the empirical pricing performance of the CEV model and compared the results with those by Bakshi et al. (1997). The CEV model, introducing only one more parameter compared with Black-Scholes formula, improves the performance notably in all of the tests of in-sample, out-of-sample and the stability of implied volatility. Furthermore, with a much simpler model, the CEV model can still perform better than the stochastic volatility model in short-term and out-of-the-money categories. When applied to American option pricing, high-dimensional lattice models are prohibitively expensive. Our numerical experiments clearly show that the CEV model performs much better in terms of the speed of convergence to its closedform solution, while the implementation cost of the stochastic volatility model is too high and practically infeasible for empirical work. In summary, with a much less implementation cost and faster computational speed, the CEV option pricing model could be a better candidate than more complex option pricing models, especially when one wants to apply the CEV process for pricing more complicated path-dependent options or credit risk models.

AB - In this chapter, we empirically test the Constant-Elasticity-of-variance (CEV) option pricing model by Cox (1975, 1996) and Cox and Ross (1976), and compare the performances of the CEV and alternative option pricing models, mainly the stochastic volatility model, in terms of European option pricing and cost-accuracy-based analysis of their numerical procedures. In European-style option pricing, we have tested the empirical pricing performance of the CEV model and compared the results with those by Bakshi et al. (1997). The CEV model, introducing only one more parameter compared with Black-Scholes formula, improves the performance notably in all of the tests of in-sample, out-of-sample and the stability of implied volatility. Furthermore, with a much simpler model, the CEV model can still perform better than the stochastic volatility model in short-term and out-of-the-money categories. When applied to American option pricing, high-dimensional lattice models are prohibitively expensive. Our numerical experiments clearly show that the CEV model performs much better in terms of the speed of convergence to its closedform solution, while the implementation cost of the stochastic volatility model is too high and practically infeasible for empirical work. In summary, with a much less implementation cost and faster computational speed, the CEV option pricing model could be a better candidate than more complex option pricing models, especially when one wants to apply the CEV process for pricing more complicated path-dependent options or credit risk models.

KW - Constant-elasticity-of-variance (CEV) process

KW - Empirical performance

KW - Finite difference method of the sv model

KW - Numerical experiment

KW - Option pricing model

KW - Stochastic volatility option pricing model

UR - http://www.scopus.com/inward/record.url?scp=85096273267&partnerID=8YFLogxK

U2 - 10.1142/9789811202391_0051

DO - 10.1142/9789811202391_0051

M3 - Chapter

AN - SCOPUS:85096273267

SN - 9789811202384

SP - 1903

EP - 1942

BT - Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (In 4 Volumes)

PB - World Scientific Publishing Co.

ER -