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Mark Schroder (1989)
Computing the Constant Elasticity of Variance Option Pricing FormulaJournal of Finance, 44
S. Heston (1993)
A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency OptionsReview of Financial Studies, 6
E. Stein, J. Stein (1991)
Stock Price Distributions with Stochastic Volatility: An Analytic ApproachReview of Financial Studies, 4
James MacBeth, L. Merville (1980)
Tests of the Black-Scholes and Cox Call Option Valuation ModelsJournal of Finance, 35
P. Boyle, Yisong Tian (1999)
Pricing Lookback and Barrier Options under the CEV ProcessJournal of Financial and Quantitative Analysis, 34
David Bates (1995)
Testing Option Pricing ModelsDerivatives
P. Boyle (1986)
Option Valuation Using a Three Jump Process
Cheng-Few Lee, Ta-Peng Wu, Ren‐Raw Chen (2004)
The Constant Elasticity of Variance Models: New Evidence from S&P 500 Index OptionsReview of Pacific Basin Financial Markets and Policies, 07
D. Benton, K. Krishnamoorthy (2003)
Computing discrete mixtures of continuous distributions: noncentral chisquare, noncentral tComput. Stat. Data Anal., 43
J. Cox (1996)
The Constant Elasticity of Variance Option Pricing Model, 23
Steven Manaster (1980)
Discussion [Tests of the Black-Scholes and Cox Call Option Valuation Models]Journal of Finance, 35
D. Davydov, V. Linetsky (2001)
Pricing and Hedging Path-Dependent Options Under the CEV ProcessManag. Sci., 47
C. Lo, P. Yuen, C. Hui (2000)
Constant Elasticity of Variance Option Pricing Model With Time-Dependent ParametersDerivatives
J. Detemple, Weidong Tian (2002)
The Valuation of American Options for a Class of Diffusion ProcessesManag. Sci., 48
David Emanuel, James MacBeth (1982)
Further Results on the Constant Elasticity of Variance Call Option Pricing ModelJournal of Financial and Quantitative Analysis, 17
F. Delbaen, H. Shirakawa (2002)
A Note on Option Pricing for the Constant Elasticity of Variance ModelAsia-Pacific Financial Markets, 9
S. Beckers (1980)
The Constant Elasticity of Variance Model and Its Implications For Option PricingJournal of Finance, 35
M. Rubinstein. (1985)
Nonparametric tests of alternative option pricing models using all reported trades and quotes on the
G. Bakshi, C. Cao, Zhiwu Chen (2019)
Option Pricing and Hedging Performance Under Stochastic Volatility and Stochastic Interest RatesFinancial Econometrics, Mathematics and Statistics
Kwai Leung, Y. Kwok (2007)
Distribution of occupation times for constant elasticity of variance diffusion and the pricing of α-quantile optionsQuantitative Finance, 7
David Bates (1993)
Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Thephlx Deutschemark OptionsNBER Working Paper Series
J. Hull, Alan White (1990)
Valuing Derivative Securities Using the Explicit Finite Difference MethodJournal of Financial and Quantitative Analysis, 25
Y. Kwok, K. Leung (2006)
Distribution of Occupation Times for Cev Diffusions and Pricing of Alpha-Quantile OptionsS&P Global Market Intelligence Research Paper Series
F. Black, Myron Scholes (1973)
The Pricing of Options and Corporate LiabilitiesJournal of Political Economy, 81
D. Davydov, V. Linetsky (2003)
Pricing Options on Scalar Diffusions: An Eigenfunction Expansion ApproachOper. Res., 51
B. Kamrad, P. Ritchken (1991)
Multinomial Approximating Models for Options with k State VariablesManagement Science, 37
J. Jackwerth, M. Rubinstein. (2012)
Recovering Stochastic Processes from Option Prices, 94
S. Dyrting (2004)
Evaluating the Noncentral Chi-Square Distribution for the Cox-Ingersoll-Ross ProcessComputational Economics, 24
David Bates (2000)
Post-'87 crash fears in the S&P 500 futures option marketJournal of Econometrics, 94
P. Carr, V. Linetsky (2006)
A jump to default extended CEV model: an application of Bessel processesFinance and Stochastics, 10
J. Cox, J. Ingersoll, S. Ross (1985)
A theory of the term structure of interest rates'', Econometrica 53, 385-407
P. Boyle (1988)
A Lattice Framework for Option Pricing with Two State VariablesJournal of Financial and Quantitative Analysis, 23
C. Albanese, O. Chen (2004)
PRICING EQUITY DEFAULT SWAPS
Daniel Nelson, K. Ramaswamy (1990)
Simple Binomial Processes as Diffusion Approximations in Financial ModelsReview of Financial Studies, 3
G. Bakshi, C. Cao, Zhiwu Chen (2000)
Pricing and hedging long-term optionsJournal of Econometrics, 94
G. Bakshi, C. Cao, Zhiwu Chen (1997)
Empirical Performance of Alternative Option Pricing ModelsJournal of Finance, 52
B. Eckbo, K. Thorburn (1999)
Gains to Bidder Firms Revisited: Domestic and Foreign Acquisitions in CanadaJournal of Financial and Quantitative Analysis, 35
James Wiggins (1987)
Option values under stochastic volatility: Theory and empirical estimatesJournal of Financial Economics, 19
C. Jones (2003)
The dynamics of stochastic volatility: evidence from underlying and options marketsJournal of Econometrics, 116
K. Chan, G. Andrew, Karolyi, F. Longstaff, A. Sanders, G. Karolyi, W. Bailey, Emilio Barone, F. Black, T. Bollerslev, Stephen Buser, John Campbell, Jennifer Conrad, G. Constantinides, K. Dunn, Margaret Forster, Campbell Harvey, P. Hendershott, D. Mayers, Huston Mcculloch, Daniel Nel-Son, D. Shimko, Renl Stulz, S. Turnbull, C. Wells, Finance Workshop (1992)
An Empirical Comparison of Alternative Models of the Short-Term Interest RateJournal of Finance, 47
J. Hull, Alan White (1987)
The Pricing of Options on Assets with Stochastic VolatilitiesJournal of Finance, 42
Louis Scott (1997)
Pricing Stock Options in a Jump‐Diffusion Model with Stochastic Volatility and Interest Rates: Applications of Fourier Inversion MethodsMathematical Finance, 7
J. Cox, S. Ross (1976)
The valuation of options for alternative stochastic processesJournal of Financial Economics, 3
Louis Scott (1987)
Option Pricing when the Variance Changes Randomly: Theory, Estimation, and an ApplicationJournal of Financial and Quantitative Analysis, 22
In this essay, 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 closed form 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.
Review of Pacific Basin Financial Markets and Policies – World Scientific Publishing Company
Published: Jun 1, 2009
Keywords: Constant–Elasticity-of-Variance (CEV) process option pricing model empirical performance numerical experiment
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