Forecasting the term structure of volatility of crude oil price changes

Balaban, Ercan; Lu, Shan

doi:10.1016/j.econlet.2016.02.015

Cited by 4 publications

(4 citation statements)

References 13 publications

(9 reference statements)

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“…In a category of its own, a fewer number of studies approach crude oil price and returns in relation to other commodities also including natural gas [64][65][66][67][68][69]. Finally, and as for other traded commodities, a highly sophisticated category of research is available on both volatility modelling and forecasting evaluation [8][9][10][11][12][13][14][15]21,[70][71][72][73], both perhaps the most relevant areas for our research.…”

Section: Methodsmentioning

confidence: 99%

Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices

Cansado-Bravo

Rodríguez‐Monroy

2018

Energies

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Regardless of the rapid development of national gas centers around the world, oil price indexation remains the prevailing pricing process in Continental Europe and the Far East. The instance of Spain is a genuine case where gas supply conditions may, to some extent, clarify the slower pace of execution of a traded gas hub in the nation. This article seeks to explain the persistence of oil-indexed pricing mechanisms, a price model that differs oddly from that of other major commodities, the price of which is normally discovered on the market. In order to do that, we examine time-varying volatility to find that since 2013 until 2016, just about 33% of gradual volatility clustering rooted within oil Brent prices is reflected in Spanish gas prices. In this sense, our research provides quantitative tools to better understand that market-based approaches such as spot and medium-term supply alternatives seem to be a key driver for success in transforming gas markets. Regular updates on the size of the effects observed should facilitate an exact appraisal of the level of progression of national gas liberalization processes and enhance gas markets transparency, these issues of extraordinary importance for both policymakers and gas market agents.

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Section: Methodsmentioning

confidence: 99%

Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices

Cansado-Bravo

Rodríguez‐Monroy

2018

Energies

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“…However, due to the stochastic feature of volatility, this multiplicative method for computing multi-day ahead conditional variance forecasts may handicap the forecasting performance of implied volatility measures, and may lead to a different ranking of forecasting performance compared to the ranking produced in the evaluation of one-day ahead forecast. The squareroot-of-time rule for compounding short-term volatility for long-horizons are discussed and empirically tested in Balaban and Lu (2016); Danielsson and Zigrand (2006); Diebold, Hickman, Inoue, and Schuermann (1998).…”

Section: Rvtmentioning

confidence: 99%

Testing the Predictive Ability of Corridor Implied Volatility Under GARCH Models

2018

Asia-Pac Financ Markets

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This paper studies the predictive ability of corridor implied volatility (CIV) measure. It is motivated by the fact that CIV is measured with better precision and reliability than the model-free implied volatility due to the lack of liquid options in the tails of the risk-neutral distribution. By adding CIV measures to the modified GARCH specifications, the out-of-sample predictive ability of CIV is measured by the forecast accuracy of conditional volatility. It finds that the narrowest CIV measure, covering about 10% of the RND, dominate the one-day ahead conditional volatility forecasts regardless of the choice of GARCH models in high volatile period; as market moves to non volatile periods, the optimal width broadens. For multi-day ahead forecasts narrow and mid-range CIV measures are favoured in the full sample and high volatile period for all forecast horizons, depending on which loss functions are used; whereas in non turbulent markets, certain mid-range CIV measures are favoured, for rare instances, wide CIV measures dominate the performance. Regarding the comparisons between best performed CIV measures and two benchmark measures (market volatility index and at-the-money Black-Scholes implied volatility), it shows that under the EGARCH framework, none of the benchmark measures are found to outperform best performed CIV measures, whereas under the GARCH and NAGARCH models, best performed CIV measures are outperformed by benchmark measures for certain instances.

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“…Since only lag 1 market volatility expectation is available at each forecast origin, the calculable forecast is one-day ahead conditional variance forecast, whereas multihorizon forecasts are not computable by dynamic forecasting. The multiplicative method in Blair et al (2001) by multiplying one-day ahead volatility forecast by the number of days in the forecast horizon may handicap the forecasting performance of market volatility expectations due to the stochastic feature of volatility; discussions and empirical research work on the square-root-of-time rule for compounding short-term volatility for long-horizons can be referred to Diebold, Hickman, Inoue & Schuermann (1998), Danielsson & Zigrand (2006), Balaban & Lu (2016).…”

Section: Model Specification and Volatility Forecastsmentioning

confidence: 99%

The Information Content of Corridor Implied Variances and Their Economic Difference in the DJX Options Market

2017

SSRN Journal

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This paper investigates the ability of corridor implied variances (CIV) with different corridors to forecast conditional volatility of DJIA index returns, and compares their performance with a CBOE volatility index, VXD, by employing several GARCH models in a model-based out-of-sample context. Besides, it explores the reasons behind the differences in the forecasting ability of CIVs and VXD through a decomposition of the model-free implied volatility. In addition, it addresses the economic difference among aforementioned implied volatility measures in a simulated options market. We find that narrow-corridor CIVs outperform wide-corridor CIVs and VXD in terms of the forecasting ability, as wide-corridor CIVs and VXD impound information from deep out-of-the-money options whose prices contain large volatility risk premiums and may not reflect a fair market expectation of volatility. In the economic sense, wide-corridor CIVs and VXD outperform narrow-corridor CIVs in turbulent periods, while narrow-corridor CIVs outperform wide-corridor CIVs and VXD in medium-and low-volatility periods. The profitability pattern is consistent both in-sample and out-of-sample, before and after transaction costs are considered, and is also robust to option strategy choices.

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Forecasting the term structure of volatility of crude oil price changes

Cited by 4 publications

References 13 publications

Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices

Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices

Testing the Predictive Ability of Corridor Implied Volatility Under GARCH Models

The Information Content of Corridor Implied Variances and Their Economic Difference in the DJX Options Market

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