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Option Valuation with Macro-Finance Variables

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  • Dorion, Christian

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.

Suggested Citation

  • Dorion, Christian, 2016. "Option Valuation with Macro-Finance Variables," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(4), pages 1359-1389, August.
    • Handle: RePEc:cup:jfinqa:v:51:y:2016:i:04:p:1359-1389_00
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    Cited by:

    1. Yang, Xinglin & Shang, Yuhuang, 2024. "Pricing VIX futures with mixed frequency macroeconomic information," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 847-857.
    2. Christian Conrad & Melanie Schienle, 2020. "Testing for an Omitted Multiplicative Long-Term Component in GARCH Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 229-242, April.
    3. Zhang, Yuanyuan & Zhang, Qian & Wang, Zerong & Wang, Qi, 2024. "Option valuation via nonaffine dynamics with realized volatility," Journal of Empirical Finance, Elsevier, vol. 77(C).
    4. Badescu, Alexandru & Quaye, Enoch & Tunaru, Radu, 2022. "On non-negative equity guarantee calculations with macroeconomic variables related to house prices," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 119-138.
    5. Naimoli, Antonio, 2022. "The information content of sentiment indices for forecasting Value at Risk and Expected Shortfall in equity markets," MPRA Paper 112588, University Library of Munich, Germany.
    6. Naimoli, Antonio, 2023. "The information content of sentiment indices in forecasting Value at Risk and Expected Shortfall: a Complete Realized Exponential GARCH-X approach," International Economics, Elsevier, vol. 176(C).
    7. Augustyniak, Maciej & Badescu, Alexandru & Bégin, Jean-François, 2023. "A discrete-time hedging framework with multiple factors and fat tails: On what matters," Journal of Econometrics, Elsevier, vol. 232(2), pages 416-444.

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