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GARCH Approach (garch + approach)

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Business, Economics, Finance and Accounting	100%

Selected Abstracts

Optimal Hedging Ratios for Wheat and Barley at the LIFFE: A GARCH Approach

JOURNAL OF AGRICULTURAL ECONOMICS, Issue 2 2000
P. J. Dawson
Over 100,000 futures contracts for cereals are traded annually on the London International Financial Futures Exchange. The proportion of the spot position held as futures contracts - the hedging ratio - is critical to traders and traditional estimates, using OLS, are constant over time. In this paper, we estimate time-varying hedging ratios for wheat and barley contracts using a multivariate generalised autoregressive conditional heteroscedasticity (GARCH) model. Results indicate that GARCH hedging ratios do change through time. Moreover, risk using the GARCH hedge is reduced significantly by around 4 per cent for wheat and 2 per cent for barley relative to the no hedge position, and significantly by around 0.2 per cent relative to the constant hedge. The optimal, expected utility-maximising, and the risk-minimising hedging ratios are equivalent. [source]

A Note on Estimating Market,based Minimum Capital Risk Requirements: A Multivariate GARCH Approach

THE MANCHESTER SCHOOL, Issue 5 2002
C. Brooks
Internal risk management models of the kind popularized by J. P. Morgan are now used widely by the world's most sophisticated financial institutions as a means of measuring risk. Using the returns on three of the most popular futures contracts on the London International Financial Futures Exchange, in this paper we investigate the possibility of using multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models for the calculation of minimum capital risk requirements (MCRRs). We propose a method for the estimation of the value at risk of a portfolio based on a multivariate GARCH model. We find that the consideration of the correlation between the contracts can lead to more accurate, and therefore more appropriate, MCRRs compared with the values obtained from a univariate approach to the problem. [source]

The Impact of Macroeconomic and Financial Variables on Market Risk: Evidence from International Equity Returns

EUROPEAN FINANCIAL MANAGEMENT, Issue 4 2002
Dilip K. Patro
Using a GARCH approach, we estimate a time,varying two,factor international asset pricing model for the weekly equity index returns of 16 OECD countries. We find significant time,variation in the exposure (beta) of country equity index returns to the world market index and in the risk,adjusted excess returns (alpha). We then explain these world market betas and alphas using a number of country,specific macroeconomic and financial variables with a panel approach. We find that several variables including imports, exports, inflation, market capitalisation, dividend yields and price,to,book ratios significantly affect a country's exposure to world market risk. Similar conclusions are obtained by using lagged explanatory variables, and thus these variables may be useful as predictors of world market risks. Several variables also significantly impact the risk,adjusted excess returns over this time period. Our results are robust to a number of alternative specifications. We further discuss some economic hypotheses that may explain these relationships. [source]

Estimation and hedging effectiveness of time-varying hedge ratio: Flexible bivariate garch approaches

THE JOURNAL OF FUTURES MARKETS, Issue 1 2010
Sung Yong Park
Bollerslev's (1990, Review of Economics and Statistics, 52, 5,59) constant conditional correlation and Engle's (2002, Journal of Business & Economic Statistics, 20, 339,350) dynamic conditional correlation (DCC) bivariate generalized autoregressive conditional heteroskedasticity (BGARCH) models are usually used to estimate time-varying hedge ratios. In this study, we extend the above model to more flexible ones to analyze the behavior of the optimal conditional hedge ratio based on two (BGARCH) models: (i) adopting more flexible bivariate density functions such as a bivariate skewed- t density function; (ii) considering asymmetric individual conditional variance equations; and (iii) incorporating asymmetry in the conditional correlation equation for the DCC-based model. Hedging performance in terms of variance reduction and also value at risk and expected shortfall of the hedged portfolio are also conducted. Using daily data of the spot and futures returns of corn and soybeans we find asymmetric and flexible density specifications help increase the goodness-of-fit of the estimated models, but do not guarantee higher hedging performance. We also find that there is an inverse relationship between the variance of hedge ratios and hedging effectiveness. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:71,99, 2010 [source]