Skip to main content
×
Home
    • Aa
    • Aa

The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation

  • Peter Christoffersen (a1), Bruno Feunou (a2), Kris Jacobs (a3) and Nour Meddahi (a4)
Abstract
Abstract

Many studies have documented that daily realized volatility estimates based on intraday returns provide volatility forecasts that are superior to forecasts constructed from daily returns only. We investigate whether these forecasting improvements translate into economic value added. To do so, we develop a new class of affine discrete-time option valuation models that use daily returns as well as realized volatility. We derive convenient closed-form option valuation formulas, and we assess the option valuation properties using Standard & Poor’s (S&P) 500 return and option data. We find that realized volatility reduces the pricing errors of the benchmark model significantly across moneyness, maturity, and volatility levels.

Copyright
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

Y. Aït-Sahalia , and J. Jacod . “Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data.” Journal of Economic Literature, 50 (2012), 10071050.

Y. Aït-Sahalia , and R. Kimmel . “Maximum Likelihood Estimation of Stochastic Volatility Models.” Journal of Financial Economics, 83 (2007), 413452.

T. G. Andersen , and T. Bollerslev . “Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts.” International Economic Review, 39 (1998), 885905.

T. G. Andersen ; T. Bollerslev ; F. X. Diebold ; and P. Labys . “Modeling and Forecasting Realized Volatility.” Econometrica, 71 (2003), 579625.

D Andrews . “Tests for Parameter Instability and Structural Change with Unknown Change Point.” Econometrica, 61 (1993), 821856.

D. Andrews , and W. Ploberger . “Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative.” Econometrica, 62 (1994), 13831414.

O. E. Barndorff-Nielsen , and N. Shephard . “Econometric Analysis of Realized Volatility and Its Use in Estimating Stochastic Volatility Models.” Journal of the Royal Statistical Society, B, 64 (2002), 253280.

G. Barone-Adesi ; R. Engle ; and L. Mancini . “A GARCH Option Pricing Model with Filtered Historical Simulation.” Review of Financial Studies, 21 (2008), 12231258.

D Bates . “Post-87 Crash Fears in S&P 500 Futures Options.” Journal of Econometrics, 94 (2000), 181238.

T Bollerslev . “Generalized Autoregressive Conditional Heteroskedasticity.” Journal of Econometrics, 31 (1986), 307327.

T. Bollerslev , and J. M. Wooldridge . “Quasi-Maximum Likelihood Estimation and Inference in Dynamic Models with Time-Varying Covariances.” Econometric Reviews, 11 (1992), 143172.

X. Chen ; E. Ghysels ; and F. Wang . “HYBRID GARCH Models and Intra-Daily Return Periodicity.” Journal of Time Series Econometrics, 3 (2011), 1941–1928.

M. Chernov ; A. R. Gallant ; E. Ghysels ; and G. Tauchen . “Alternative Models for Stock Price Dynamics.” Journal of Econometrics, 116 (2003), 225257.

P. Christoffersen ; C. Dorion ; K. Jacobs ; and Y. Wang . “Volatility Components, Affine Restrictions, and Nonnormal Innovations.” Journal of Business and Economic Statistics, 28 (2010), 483502.

P. Christoffersen ; R. Elkamhi ; B. Feunou ; and K. Jacobs . “Option Valuation with Conditional Heteroskedasticity and Nonnormality.” Review of Financial Studies, 23 (2010), 21392183.

P. Christoffersen ; S. Heston ; and K. Jacobs . “The Shape and Term Structure of the Index Option Smirk: Why Multifactor Stochastic Volatility Models Work So Well.” Management Science, 55 (2009), 19141932.

P. Christoffersen ; K. Jacobs ; and K. Mimouni . “Volatility Dynamics for the S&P500: Evidence from Realized Volatility, Daily Returns, and Option Prices.” Review of Financial Studies, 23 (2010), 31413189.

P. Christoffersen ; K. Jacobs ; C. Ornthanalai ; and Y. Wang . “Option Valuation with Long-Run and Short-Run Volatility Components.” Journal of Financial Economics, 90 (2008), 272297.

F. Corsi ; N. Fusari ; and D. La Vecchia . “Realizing Smiles: Options Pricing with Realized Volatility.” Journal of Financial Economics, 107 (2013), 284304.

J. C Duan . “The GARCH Option Pricing Model.” Mathematical Finance, 5 (1995), 1332.

R Engle . “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of UK Inflation.” Econometrica, 50 (1982), 9871008.

R. Engle , and G. Gallo . “A Multiple Indicators Model for Volatility Using Intra-Daily Data.” Journal of Econometrics, 131 (2006), 327.

R. Engle , and C. Mustafa . “Implied ARCH Models from Options Prices.” Journal of Econometrics, 52 (1992), 289311.

R. Engle , and V. Ng . “Measuring and Testing the Impact of News on Volatility.” Journal of Finance, 48 (1993), 17491778.

L. Forsberg , and T. Bollerslev . “Bridging the Gap Between the Distribution of Realized (ECU) and ARCH Modelling (of the Euro): The GARCH-NIG Model.” Journal of Applied Econometrics, 17 (2002), 535548.

P. Hansen ; Z. Huang ; and H. Shek . “Realized GARCH: A Joint Model for Returns and Realized Measures of Volatility.” Journal of Applied Econometrics, 27 (2012), 877906.

P. Hansen , and A. Lunde . “A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data.” Journal of Financial Econometrics, 3 (2005), 525554.

K. Hsieh , and P. Ritchken . “An Empirical Comparison of GARCH Option Pricing Models.” Review of Derivatives Research, 8 (2005), 129150.

C Jones . “The Dynamics of Stochastic Volatility: Evidence from Underlying and Options Markets.” Journal of Econometrics, 116 (2003), 181224.

D. B Nelson . “Conditional Heteroskedasticity in Asset Returns: A New Approach.” Econometrica, 59 (1991), 347370.

P. Ritchken , and R. Trevor . “Pricing Options Under Generalized GARCH and Stochastic Volatility Processes.” Journal of Finance, 54 (1999), 377402.

A. Trolle , and E. Schwartz . “Unspanned Stochastic Volatility and the Pricing of Commodity Derivatives.” Review of Financial Studies, 22 (2009), 44234461.

L. Zhang ; P. Mykland ; and Y. Aït-Sahalia . “A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High-Frequency Data.” Journal of the American Statistical Association, 100 (2005), 13941411.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Journal of Financial and Quantitative Analysis
  • ISSN: 0022-1090
  • EISSN: 1756-6916
  • URL: /core/journals/journal-of-financial-and-quantitative-analysis
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×
Type Description Title
PDF
Supplementary Materials

Christoffersen Supplementary Material
Christoffersen Supplementary Material

 PDF (51 KB)
51 KB

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 139 *
Loading metrics...

Abstract views

Total abstract views: 489 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 19th August 2017. This data will be updated every 24 hours.