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Option Valuation with Macro-Finance Variables

Published online by Cambridge University Press:  01 November 2016

Christian Dorion
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Abstract

I propose a model in which the price of an option is partly determined by macro-finance variables. In an application using an index of current business conditions, the new model outperforms existing benchmarks in fitting underlying asset returns and in pricing options. The model performs particularly well when business conditions are deteriorating. Using the recent financial crisis as an out-of-sample experiment, the new model has option-pricing errors that are 18% below those of a nested 2-component volatility benchmark. Results are robust to using alternative business conditions proxies and comparing to different benchmark models.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 51 , Issue 4 , August 2016 , pp. 1359 - 1389
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2016 

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References

Alizadeh, S.; Brandt, M.; and Diebold, F.. “Range-Based Estimation of Stochastic Volatility Models.” Journal of Finance, 57 (2002), 1047–1091.Google Scholar
Andersen, T. G.; Bollerslev, T.; Diebold, F. X.; and Ebens, H.. “The Distribution of Realized Stock Return Volatility.” Journal of Financial Economics, 61 (2001), 43–76.CrossRefGoogle Scholar
Aruoba, S.; Diebold, F.; and Scotti, C.. “Real-Time Measurement of Business Conditions.” Journal of Business and Economic Statistics, 27 (2009), 417–427.CrossRefGoogle Scholar
Bakshi, G.; Cao, C.; and Chen, Z.. “Empirical Performance of Alternative Option Pricing Models.” Journal of Finance, 52 (1997), 2003–2049.Google Scholar
Bansal, R., and Yaron, A.. “Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles.” Journal of Finance, 59 (2004), 1481–1509.CrossRefGoogle Scholar
Bates, D.“Post-87 Crash Fears in S&P 500 Futures Options.” Journal of Econometrics, 94 (2000), 181–238.Google Scholar
Bates, D. S.“Maximum Likelihood Estimation of Latent Affine Processes.” Review of Financial Studies, 19 (2006), 909–965.CrossRefGoogle Scholar
Bernanke, B. S.“Irreversibility, Uncertainty, and Cyclical Investment.” Quarterly Journal of Economics, 98 (1983), 85–106.Google Scholar
Bernanke, B. S.; Gertler, M.; and Gilchrist, S.. “The Financial Accelerator in a Quantitative Business Cycle Framework.” In Handbook of Macroeconomics, Vol. I, Taylor, J. B. and Woodford, M., eds. North-Holland: Elsevier (1999), 1341–1393.Google Scholar
Black, F.“Studies of Stock Price Volatility Changes.” In Proceedings of the 1976 Meetings of the Business and Economic Statistics Section, Washington, DC: American Statistical Association (1976), 177–181.Google Scholar
Black, F., and Scholes, M. S.. “The Pricing of Options and Corporate Liabilities.” Journal of Political Economy, 7 (1973), 637–654.Google Scholar
Bloom, N.; Floetotto, M.; Jaimovich, N.; Saporta-Eksten, I.; and Terry, S. J.. “Really Uncertain Business Cycles.” U.S. Census Bureau Center for Economic Studies Paper No. CES-WP-14-18 (2014).Google Scholar
Bollerslev, T.“Generalized Autoregressive Conditional Heteroskedasticity.” Journal of Econometrics, 31 (1986), 307–327.CrossRefGoogle Scholar
Bollerslev, T., and Wooldridge, J.. “Quasi-Maximum Likelihood Estimation and Inference in Dynamic Models with Time-Varying Covariances.” Econometric Reviews, 11 (1992), 143–172.Google Scholar
Buraschi, A.; Trojani, F.; and Vedolin, A.. “Economic Uncertainty, Disagreement, and Credit Markets.” Management Science, 60 (2014), 1281–1296.Google Scholar
Calvet, L., and Fisher, A.. “Forecasting Multifractal Volatility.” Journal of Econometrics, 105 (2001), 27–58.CrossRefGoogle Scholar
Calvet, L., and Fisher, A.. “Multifractality in Asset Returns: Theory and Evidence.” Review of Economics and Statistics, 84 (2002), 381–406.CrossRefGoogle Scholar
Calvet, L., and Fisher, A.. “How to Forecast Long-Run Volatility: Regime-Switching and the Estimation of Multifractal Processes.” Journal of Financial Econometrics, 2 (2003), 49–83.Google Scholar
Calvet, L., and Fisher, A.. “Multifrequency News and Stock Returns.” Journal of Financial Economics, 86 (2007), 178–212.CrossRefGoogle Scholar
Campbell, J.“A Variance Decomposition for Stock Returns.” Economic Journal, 101 (1991), 157–179.Google Scholar
Campbell, J., and Shiller, R.. “The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors.” Review of Financial Studies, 1 (1988), 195–228.Google Scholar
Chauvet, M., and Piger, J.. “A Comparison of the Real-Time Performance of Business Cycle Dating Methods.” Journal of Business and Economic Statistics, 26 (2008), 42–49.Google Scholar
Chernov, M.; Gallant, R.; Ghysels, E.; and Tauchen, G.. “Alternative Models for Stock Price Dynamics.” Journal of Econometrics, 116 (2003), 225–257.Google Scholar
Chernov, M., and Ghysels, E.. “A Study Towards a Unified Approach to the Joint Estimation of Objective and Risk Neutral Measures for the Purpose of Option Valuation.” Journal of Financial Economics, 56 (2000), 407–458.CrossRefGoogle Scholar
Christoffersen, P. F.; Dorion, C.; Jacobs, K.; and Wang, Y.. “Volatility Components, Affine Restrictions and Non-Normal Innovations.” Journal of Business and Economic Statistics, 28 (2010), 483–502.CrossRefGoogle Scholar
Christoffersen, P. F.; Elkamhi, R.; Feunou, B.; and Jacobs, K.. “Option Valuation with Conditional Heteroskedasticity and Non-Normality.” Review of Financial Studies, 23 (2010), 2139–2183.CrossRefGoogle Scholar
Christoffersen, P.; Feunou, B.; Jacobs, K.; and Meddahi, N.. “The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation.” Journal of Financial and Quantitative Analysis, 49 (2014), 663–697.Google Scholar
Christoffersen, P. F.; Heston, S.; and Jacobs, K.. “Option Valuation with Conditional Skewness.” Journal of Econometrics, 131 (2006), 253–284.CrossRefGoogle Scholar
Christoffersen, P. F.; Heston, S.; and Jacobs, K.. “Capturing Option Anomalies with a Variance-Dependent Pricing Kernel.” Review of Financial Studies, 26 (2013), 1962–2006.Google Scholar
Christoffersen, P. F., and Jacobs, K.. “Which GARCH Model for Option Valuation?” Management Science, 50 (2004), 1204–1221.CrossRefGoogle Scholar
Christoffersen, P. F.; Jacobs, K.; and Ornthanalai, C.. “Dynamic Jump Intensities and Risk Premiums: Evidence from S&P500 Returns and Options.” Journal of Financial Economics, 106 (2012), 447–472.Google Scholar
Christoffersen, P. F.; Jacobs, K.; Ornthanalai, C.; and Wang, Y.. “Option Valuation with Long-Run and Short-Run Volatility Components.” Journal of Financial Economics, 90 (2008), 272–297.Google Scholar
Conrad, C., and Loch, K.. “Anticipating Long-Term Stock Market Volatility.” Journal of Applied Econometrics, 30 (2015), 1090–1114.CrossRefGoogle Scholar
Corradi, V.; Distaso, W.; and Mele, A.. “Macroeconomic Determinants of Stock Market Volatility and Volatility Premiums.” Journal of Monetary Economics, 60 (2013), 203–220.Google Scholar
David, A., and Veronesi, P.. “Options Prices with Uncertain Fundamentals.” Working Paper, University of Chicago (2002).Google Scholar
David, A., and Veronesi, P.. “What Ties Return Volatilities to Price Valuations and Fundamentals?” Journal of Political Economy, 121 (2012), 682–746.Google Scholar
Duan, J.-C.“The GARCH Option Pricing Model.” Mathematical Finance, 5 (1995), 13–32.CrossRefGoogle Scholar
Duan, J.-C., and Simonato, J.-G.. “Empirical Martingale Simulation for Asset Prices.” Management Science, 44 (1998), 1218–1233.CrossRefGoogle Scholar
Engle, R. F.“Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of UK Inflation.” Econometrica, 50 (1982), 987–1008.Google Scholar
Engle, R.; Ghysels, E.; and Sohn, B.. “Stock Market Volatility and Macroeconomic Fundamentals.” Review of Economics and Statistics, 95 (2013), 776–797.CrossRefGoogle Scholar
Engle, R. F., and Lee, G.. “A Permanent and Transitory Component Model of Stock Return Volatility.” In Cointegration, Causality, and Forecasting: A Festschrift in Honor of Clive W. J. Granger, Engle, R. and White, H., eds. New York, NY: Oxford University Press (1999), 475–497.Google Scholar
Engle, R. F., and Rangel, J. G.. “The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes.” Review of Financial Studies, 21 (2008), 1187–1222.CrossRefGoogle Scholar
Eraker, B.“Affine General Equilibrium Models.” Management Science, 54 (2008), 2068–2080.Google Scholar
Forsberg, L., and Ghysels, E.. “Why Do Absolute Returns Predict Volatility So Well?” Journal of Financial Econometrics, 5 (2007), 31–67.Google Scholar
Ghysels, E.; Santa-Clara, P.; and Valkanov, R.. “There Is a Risk-Return Trade-Off After All.” Journal of Financial Economics, 76 (2005), 509–548.Google Scholar
Ghysels, E.; Sinko, A.; and Valkanov, R.. “MIDAS Regressions: Further Results and New Directions.” Econometric Reviews, 26 (2007), 53–90.Google Scholar
Hamilton, J., and Susmel, R.. “Autoregressive Conditional Heteroskedasticity and Changes in Regime.” Journal of Econometrics, 64 (1994), 307–333.CrossRefGoogle Scholar
Heston, S. L.“A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bonds and Currency Options.” Review of Financial Studies, 6 (1993), 327–343.Google Scholar
Heston, S. L., and Nandi, S.. “A Closed-Form GARCH Option Valuation Model.” Review of Financial Studies, 13 (2000), 585–626.Google Scholar
Hsieh, K. C., and Ritchken, P.. “An Empirical Comparison of GARCH Option Pricing Models.” Review of Derivatives Research, 8 (2005), 129–150.CrossRefGoogle Scholar
Liu, J.; Pan, J.; and Wang, T.. “An Equilibrium Model of Rare-Event Premia and Its Implication for Option Smirks.” Review of Financial Studies, 18 (2005), 131–164.Google Scholar
Lucas, R. E.“Understanding Business Cycles.” Carnegie-Rochester Conference Series on Public Policy, 5 (1977), 7–29.CrossRefGoogle Scholar
McDonald, R., and Siegel, D.. “The Value of Waiting to Invest.” Quarterly Journal of Economics, 101 (1986), 707–727.Google Scholar
Merton, R. C.“Theory of Rational Option Pricing.” Bell Journal of Economics and Management Science, 4 (1973), 141–183.Google Scholar
Merton, R. C.“On the Pricing of Corporate Debt: The Risk Structure of Interest Rates.” Journal of Finance, 29 (1974), 449–470.Google Scholar
Nandi, S.“How Important Is the Correlation between Returns and Volatility in a Stochastic Volatility Model? Empirical Evidence from Pricing and Hedging in the S&P 500 Index Options Market.” Journal of Banking and Finance, 22 (1998), 589–610.Google Scholar
Newey, W. K., and West, K. D.. “Automatic Lag Selection in Covariance Matrix Estimation.” Review of Economic Studies, 61 (1994), 631–653.Google Scholar
Ornthanalai, C.“Lévy Jump Risk: Evidence from Options and Returns.” Journal of Financial Economics, 112 (2014), 69–90.Google Scholar
Paye, B. S.“‘Déjà vol’: Predictive Regressions for Aggregate Stock Market Volatility Using Macroeconomic Variables.” Journal of Financial Economics, 106 (2012), 527–546.Google Scholar
Renault, E.“Econometric Models of Option Pricing Errors.” In Advances in Economics and Econometrics, Seventh World Congress, Econometric Society Monographs, Kreps, D. and Wallis, K., eds. Cambridge, UK: Cambridge University Press (1997), 223–278.Google Scholar
Ritchken, P., and Trevor, R.. “Pricing Options under Generalized GARCH and Stochastic Volatility Processes.” Journal of Finance, 54 (1999), 377–402.Google Scholar
Schwert, W. G.“Why Does Stock Market Volatility Change Over Time?” Journal of Finance, 44 (1989), 1115–1153.Google Scholar
Stentoft, L.“Pricing American Options When the Underlying Asset Follows GARCH Processes.” Journal of Empirical Finance, 12 (2005), 576–611.Google Scholar
Stock, J., and Watson, M.. “New Indexes of Coincident and Leading Economic Indicators.” NBER Macro Annual, 4 (1989), 351–409.Google Scholar
Veldkamp, L., and Wolfers, J.. “Aggregate Shocks or Aggregate Information? Costly Information and Business Cycle Comovement.” Journal of Monetary Economics, 54 (2007), 37–55.CrossRefGoogle Scholar
Veronesi, P.“Stock Market Overreaction to Bad News in Good Times: A Rational Expectations Equilibrium Model.” Review of Financial Studies, 12 (1999), 975–1007.Google Scholar
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