Conditional dynamics and optimal spreading in the precious metals futures markets

Wahab, Mahmoud

doi:10.1002/fut.3990150204

Cited by 24 publications

(15 citation statements)

References 47 publications

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“…Multivariate GARCH models allow the variance and covariance to depend on the information set in a vector ARMA manner (Engle and Kroner, 1995). This, in turn, leads to the unbiased and more precise estimate of the parameters (Wahab, 1995).…”

Section: Bivariate Garchmentioning

confidence: 99%

Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time‐varying beta

Choudhry

2008

Journal of Forecasting

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This paper investigates the forecasting ability of four different GARCH models and the Kalman filter method. The four GARCH models applied are the bivariate GARCH, BEKK GARCH, GARCH-GJR and the GARCH-X model. The paper also compares the forecasting ability of the non-GARCH model: the Kalman method. Forecast errors based on 20 UK company daily stock return (based on estimated time-varying beta) forecasts are employed to evaluate out-of-sample forecasting ability of both GARCH models and Kalman method. Measures of forecast errors overwhelmingly support the Kalman filter approach. Among the GARCH models the GJR model appears to provide somewhat more accurate forecasts than the other bivariate GARCH models. Copyright © 2008 John Wiley & Sons, Ltd.

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Section: Bivariate Garchmentioning

confidence: 99%

Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time‐varying beta

Choudhry

2008

Journal of Forecasting

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“…This study is significant as it indicated that static hedges are not effective over long hedging periods. After the studies of Franckle (1980) and Figlewski (1985), almost all studies on the optimal hedge ratio applied Ederington's (1979) SEMOLS including: Vishwanath (1993; Ghosh (1993), Chou et al (1996); Myers (1991); Park and Switzer (1995);Wahab (1995); Holmes (1996);Choudhry (2003); Laws and Thompson (2005); Yang and Allen (2005); as well as Bhaduria and Duraia (2008). Figlewski's (1985) study prompted an important question in financial economics literature: can one's portfolio remain hedged ad infinitum with the same hedge ratio?…”

Section: Literature Reviewmentioning

confidence: 99%

“…Multivariate GARCH methodology would consider changes in volatility in both spot and futures returns and the changes in their covariance. Wahab (1995) purported that Multivariate GARCH methodology provides unbiased parameter estimates compared to the univariate GARCH models for each variable. Wahab's (1995) use of a Multivariate GARCH method to estimate hedge ratios for precious metals, such as gold and silver, was well specified, as it took into account the related time dependent variation of the two time series used for index futures hedging, the spot time series and the corresponding futures time series.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Myers (1991), Park and Switzer (1995), as well as Wahab (1995) purported that the application of Multivariate Generalised Autoregressive Conditional Heteroskedasticity (GARCH) methods provide more effective and unbiased estimates of the optimal hedge ratio. , (14) where h ss , h ff and h sf are the respective conditional variances of the spot and futures returns' residuals and their conditional covariance with a constant mean model as the mean equation.…”

Section: Multivariate Generalised Autoregressive Conditional Heteroskmentioning

confidence: 99%

“…Studies by Ederington (1979), Franckle (1980), Figlewski (1985), Vishwanath (1993), Ghosh (1993), Chou et al (1996), Myers (1991), Park and Switzer (1995), Holmes (1996), Laws and Thompson (2005) as well as Yang and Allen (2005) have applied different | 2 econometric hedging methods in order to estimate the optimal hedge ratio. These methods range from the Single Equation Method estimated by Ordinary Least Squares (Ederington (1979), Franckle (1980) and Figlewski (1985)); the Vector Autoregression Method (Vishwanath (1993), Ghosh (1993) and Chou et al (1996)); Vector ErrorCorrection Method (Vishwanath (1993), Ghosh (1993) and Chou et al (1996)); to a class of Multivariate GARCH methods (Myers (1991), Park and Switzer (1995) Wahab (1995)). Consequently, it is important to determine the suitable econometric methodology for the appraisal of optimal hedge ratio.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The effectiveness of index futures hedging in emerging markets during the crisis period of 2008-2010: Evidence from South Africa

Bonga‐Bonga

Umoetok

2016

Applied Economics

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This paper provides an assessment of the comparative effectiveness of four econometric methods in estimating the optimal hedge ratio in an emerging equity market, particularly the South African equity and futures markets. The paper bases the effectiveness of hedging on volatility reduction and minimisation of the coefficient of variation of hedged returns as well as risk-aversion based utility maximisation. The empirical analysis shows that the single equation method estimated by ordinary least squares is the most effective over daily hedging periods. However, the vector error-correction method and multivariate GARCH methods are most effective over weekly and monthly hedging periods.

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What moves the gold market?

2001

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In this article, we provide a detailed characterization of the intraday return volatility in gold futures contracts traded on the COMEX division of the New York Mercantile Exchange. The approach allows the study of intraday patterns, interday ARCH effects, and announcement effects in a coherent framework. We show that the intraday patterns exert a profound impact on the dynamics of return volatility. Among the 23 U.S. macroeconomic announcements, we identify employment reports, gross domestic product, consumer price index, and personal income as having the greatest impact. Finally, by appropriately filtering out the intraday patterns, we find that the high‐frequency returns reveal long‐memory volatility dependencies in the gold market, which have important implications on the pricing of long‐term gold options and the determination of optimal hedge ratios. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:257–278, 2001

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Conditional dynamics and optimal spreading in the precious metals futures markets

Cited by 24 publications

References 47 publications

Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time‐varying beta

Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time‐varying beta

The effectiveness of index futures hedging in emerging markets during the crisis period of 2008-2010: Evidence from South Africa

What moves the gold market?

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