Volatility Dynamics for the S&P500: Evidence from Realized Volatility, Daily Returns, and Option Prices

被引:169
|
作者
Christoffersen, Peter [1 ]
Jacobs, Kris [2 ,3 ]
Mimouni, Karim [4 ]
机构
[1] McGill Univ, Desautels Fac Management, Montreal, PQ H3A 1G5, Canada
[2] Univ Houston, Houston, TX 77004 USA
[3] Tilburg Univ, Tilburg, Netherlands
[4] Amer Univ Dubai, Dubai, U Arab Emirates
来源
REVIEW OF FINANCIAL STUDIES | 2010年 / 23卷 / 08期
关键词
MAXIMUM-LIKELIHOOD-ESTIMATION; CHANGED LEVY PROCESSES; STOCHASTIC VOLATILITY; PRICING-MODELS; GMM ESTIMATION; ASSET PRICES; MONTE-CARLO; RISK PREMIA; VALUATION; JUMP;
D O I
10.1093/rfs/hhq032
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Most recent empirical option valuation studies build on the affine square root (SQR) stochastic volatility model. The SQR model is a convenient choice, because it yields closed-form solutions for option prices. We investigate alternatives to the SQR model, by comparing its empirical performance with that of five different but equally parsimonious stochastic volatility models. We provide empirical evidence from three different sources: realized volatilities, S&P500 returns, and an extensive panel of option data. The three sources of data all point to the same conclusion: the best volatility specification is one with linear rather than square root diffusion for variance. This model captures the stylized facts in realized volatilities, it performs well in fitting various samples of index returns, and it has the lowest option implied volatility mean squared error in and out of sample. (JEL G12)
引用
收藏
页码:3141 / 3189
页数:49
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