Volatility Forecasts Embedded in the Prices of Crude-Oil Options

Leonidas Tsiaras, Dudley Gilder

Research output: Contribution to journalArticle

Abstract

This paper evaluates and compares the ability of alternative option-implied volatility measures to forecast the monthly realized volatility of crude-oil returns. We find that a corridor implied volatility measure that aggregates information from a narrow range of option contracts consistently outperforms forecasts obtained by the popular Black-Scholes and model-free volatility expectations, as well as those generated by a high-frequency realized volatility model. In particular, this measure ranks favorably in all regression-based tests, delivers the lowest forecast errors under either symmetric or asymmetric loss functions, and generates economically significant gains in volatility timing exercises. We also find that that the CBOE's ``oil-VIX'' (OVX) index performs poorly, as it routinely produces the least accurate forecasts. Our narrow corridor measure continues to outperform other alternatives when we construct volatility forecasts using options on the United States Oil Fund (USO), i.e. the ETF that underlies the calculation of the OVX.
Original languageEnglish
JournalJournal of Futures Markets
Publication statusAccepted/In press - 1 Dec 2019

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Crude oil
Volatility forecasts
Oil
Volatility index
Realized volatility
Implied volatility
Loss function
Volatility models
Exercise
Option contract
Black-Scholes
Volatility timing
Forecast error
Asymmetric loss

Keywords

  • Volatility forecasting, crude-oil, option-implied volatility, OVX

Cite this

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title = "Volatility Forecasts Embedded in the Prices of Crude-Oil Options",
abstract = "This paper evaluates and compares the ability of alternative option-implied volatility measures to forecast the monthly realized volatility of crude-oil returns. We find that a corridor implied volatility measure that aggregates information from a narrow range of option contracts consistently outperforms forecasts obtained by the popular Black-Scholes and model-free volatility expectations, as well as those generated by a high-frequency realized volatility model. In particular, this measure ranks favorably in all regression-based tests, delivers the lowest forecast errors under either symmetric or asymmetric loss functions, and generates economically significant gains in volatility timing exercises. We also find that that the CBOE's ``oil-VIX'' (OVX) index performs poorly, as it routinely produces the least accurate forecasts. Our narrow corridor measure continues to outperform other alternatives when we construct volatility forecasts using options on the United States Oil Fund (USO), i.e. the ETF that underlies the calculation of the OVX.",
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Volatility Forecasts Embedded in the Prices of Crude-Oil Options. / Tsiaras, Leonidas; Gilder, Dudley.

In: Journal of Futures Markets, 01.12.2019.

Research output: Contribution to journalArticle

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AB - This paper evaluates and compares the ability of alternative option-implied volatility measures to forecast the monthly realized volatility of crude-oil returns. We find that a corridor implied volatility measure that aggregates information from a narrow range of option contracts consistently outperforms forecasts obtained by the popular Black-Scholes and model-free volatility expectations, as well as those generated by a high-frequency realized volatility model. In particular, this measure ranks favorably in all regression-based tests, delivers the lowest forecast errors under either symmetric or asymmetric loss functions, and generates economically significant gains in volatility timing exercises. We also find that that the CBOE's ``oil-VIX'' (OVX) index performs poorly, as it routinely produces the least accurate forecasts. Our narrow corridor measure continues to outperform other alternatives when we construct volatility forecasts using options on the United States Oil Fund (USO), i.e. the ETF that underlies the calculation of the OVX.

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