In addition, since the popularity of volatility indices has recently become widespread in the finance industry, a comparison between the OVX and other option‐implied alternatives appears to be long overdue. −

when applying our subsampled RV estimator in Equation (6). i

025 With respect to MSE losses, univariate models that utilize OIV measures deliver sharper forecasts compared to augmented specifications. C p To make our analysis more realistic, we also take into consideration transaction costs. Both volatility measures have been relatively high this month: on March 16, the VIX index measured 82.7, a level higher than any point during the financial crisis of 2008–09, the last time the global economy experienced a significant recession. With that in mind, and consistent with the spirit of our paper, the alternative OVX indices we construct are only evaluated with respect to their forecast accuracy. The skewness and kurtosis of CRV1–CRV3 are also markedly lower.

Implied volatility measures an asset’s expected range of near-term price changes. 2 Please check your email for instructions on resetting your password. It is clear that the effective range for the OVX measure exhibits substantial time‐variation throughout our sample. To do so, we compare the risk‐premia associated exclusively with extreme strike options, defined as, All our alternative OVX indices are computed by applying the CBOE methodology on same option chains, but each of them differs on how the cut‐off point, determining which options will be included in the calculation of the measure, is decided. O First, we examine the forecast performance of CIV measures vis‐à‐vis a collection of competing alternatives, including HAR, MFIV, OVX, and ATMIV forecasts, for the case of crude‐oil. Direxion Daily Natural Gas Related Bear 3x Shares, How the U.S. Election Results Could Impact Stock Markets. 1 The first-stage regressions show a positive coefficient on the quadratic term, suggesting that the market exhibits ‘Implied Volatility Smile’ and hence violates the Black-Scholes predictions. β Its implied volatility fell 9.7% during that period. Some improvement was obviously expected since for the case of crude‐oil forecasts there was a mismatch between the target quantity (crude‐oil volatility) and the underlying asset of the options used in the OVX calculation (USO ETF). With subsampling, CRV is calculated as follows: Time‐series plots of different corridor implied volatility measures for the 1996–2016 period. x Crude oil’s implied volatility spiked to 56.3% on July 13, 2016. X It is also worth noting that while models that include the CIV, corridor implied volatility; MFIV, model‐free implied volatility [Color figure can be viewed at.

Since 1999, daily WTI crude oil futures prices have settled within 2% of the previous trading day’s price about 70% of the time. 0.015 Instead of fitting a polynomial function to our implied volatility data, we have opted for a parametric GB2 risk‐neutral density (RND) estimation instead.2626 The cubic spline method is also not the preferred approach of two studies closely related to ours, namely Andersen and Bondarenko (2007) and Andersen et al. ) Again, the HAR‐CIV1 results in the highest realized utility, while, besides the OVX‐HAR case, all augmented HAR models generate a realized utility higher than that of the HAR. measures are very stable across time. The VIX, a measure of implied volatility, or the market’s expected range of near-term price changes on Standard and Poor’s (S&P) 500 index options, closed higher than the OVX, a measure of implied volatility on crude oil options. 1 Energy-Related Carbon Dioxide Emissions, Energy-Related Carbon Dioxide Emissions at the State Level, 2005-2016, Energy-Related Carbon Dioxide Emissions at the State Level, through 2017, Monthly Crude Oil and Natural Gas Production ›, Midwest and Rocky Mountain Transportation Fuels Markets, East Coast and Gulf Coast Transportation Fuels Markets, Oil market volatility is at an all-time high, Organization of the Petroleum Exporting Countries (OPEC) and partner countries. However, the extracted measure is not a risk‐neutral expectation of IVAR but CIVAR, that is return variation accumulated only when the asset price lies within a corridor of two prespecified price levels. OVX measures the implied volatility of oil prices and is calculated using movements in the prices of financial options for WTI, the light, sweet crude oil priced at Cushing, Oklahoma. Agnolucci (2009) also favors models that combine GARCH and option‐implied forecasts, however, the former appear to be more accurate than the latter in individual forecast comparisons. .25 .

, Crude oil prices have fallen significantly since the beginning of 2020, largely driven by the economic contraction caused by the 2019 novel coronavirus disease (COVID-19) and a sudden increase in crude oil supply following the suspension of agreed production cuts among the Organization of the Petroleum Exporting Countries (OPEC) and partner countries. Thus far, the bias in OIVs has been corrected for by generating out‐of‐sample forecasts through either univariate (Equation (11)) or augmented (Equation (12)) regression models.

V The performance of the OVX, while somewhat improved in this data set, continues to be unimpressive. , respectively, and subsequently evaluating Equation (5).

Along these lines, we examine the statistical properties of the ratios between the CRV and RV measures (i.e., Panel A reports results for the full sample while Panel B summarizes results for the Post‐Fin sample. O This was not a concern for the crude‐oil data set since, unlike case of the USO, a long record of historical futures prices is available.

In fact, volatility is the key component to pricing an option as it is the only "unknown" variable in an option pricing model. O Finally, in contrast to Prokopczuk and Simen (2014), we find that ATMIV is more informative about future crude‐oil volatility than the MFIV measure,77 The same result is also reported in Andersen and Bondarenko (2007) for the case of the S&P 500, and Taylor et al. is a strictly positive (càdlàg) stochastic process, so volatility can exhibit jumps. OVX measures the implied volatility of oil prices and is calculated using movements in the prices of financial options for WTI, the light, sweet crude oil priced at Cushing, Oklahoma. . CBOE Crude Oil Volatility Overview Comprehensive information about the Crude VIX index. (.

Therefore, the pattern in forecasting performance observed with the statistical loss functions is retained when we use an economic loss function. are comparatively low, indicating that narrow corridors are associated with fewer extreme CVRPs values. j The advantage of this approach is that one can select a corridor width that, while containing a wide‐range of option prices, excludes those with extreme strikes, avoiding both price extrapolations and liquidity‐driven cut‐off points that may influence the reliability of the extracted measure. If a forecast is unbiased, then we would expect Third, the skewness and kurtosis of This sample, which we refer to as USO sample, spans the period between May 2007 and December 2016.
Energy & Financial Markets: What Drives Crude Oil Prices? F It is therefore tempting to expand the information set of standard time‐series models, which rely exclusively on the record of historical prices, with measures that have “forward‐looking” features by construction. CBOE Crude Oil Volatility Index (^OVX) Add to watchlist. Any queries (other than missing content) should be directed to the corresponding author for the article. Under this loss function the HAR‐based forecasts outperform the bias‐corrected forecasts, with the most accurate forecasts being those of HAR‐CIV1. As it can be seen therein, the CIV1 forecasts have the highest correlation with the target quantity, followed by CIV2, CIV3, and CIV4. The first column of Panel A reports the realized utility.