Hedging in the Freight Futures Market

Price risks are everywhere, and a profusion of derivative instruments have been created to hedge them. The BIFFEX Baltic Freight Index futures contract, based on an index of ocean shipping costs for a set of standard routes, is one of the more unusual. An important problem with such a futures contract based on a nonstorable service is that there is no arbitrage trade to enforce cost of carry pricing. This allows considerable basis risk in the contract. In this article, Kavussanos and Nomikos examine the hedging characteristics of the BIFFEX contract within a GARCH framework that takes account of cointegration between the spot and futures markets. They find that allowing for time variation in the hedge ratio does improve hedge performance, but basis risk remains very large compared with other futures markets. A recent change in the contract, to use a narrower index, appears to have reduced the problem somewhat, but not enough to produce much increase in trading activity so far.

[1]  A. Zellner An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias , 1962 .

[2]  Bronwyn H Hall,et al.  Estimation and Inference in Nonlinear Structural Models , 1974 .

[3]  G. Schwarz Estimating the Dimension of a Model , 1978 .

[4]  G. Box,et al.  On a measure of lack of fit in time series models , 1978 .

[5]  L. Ederington,et al.  The Hedging Performance of the New Futures Markets , 1979 .

[6]  Anil K. Bera,et al.  Efficient tests for normality, homoscedasticity and serial independence of regression residuals , 1980 .

[7]  W. Fuller,et al.  LIKELIHOOD RATIO STATISTICS FOR AUTOREGRESSIVE TIME SERIES WITH A UNIT ROOT , 1981 .

[8]  R. Engle Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .

[9]  Stephen Figlewski,et al.  Hedging Performance and Basis Risk in Stock Index Futures , 1984 .

[10]  James J. Heckman,et al.  Handbook of Econometrics , 1985 .

[11]  T. Bollerslev,et al.  Generalized autoregressive conditional heteroskedasticity , 1986 .

[12]  P. Phillips Testing for a Unit Root in Time Series Regression , 1988 .

[13]  R. S. Sears,et al.  OIL PRICES AND ENERGY FUTURES , 1987 .

[14]  C. Granger,et al.  Co-integration and error correction: representation, estimation and testing , 1987 .

[15]  R. S. Sears,et al.  Oil prices and energy futures , 1987 .

[16]  T. Bollerslev,et al.  A CONDITIONALLY HETEROSKEDASTIC TIME SERIES MODEL FOR SPECULATIVE PRICES AND RATES OF RETURN , 1987 .

[17]  Tim Bollerslev,et al.  Quasi-maximum likelihood estimation of dynamic models with time varying covariances , 1988 .

[18]  T. Bollerslev,et al.  Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model , 1990 .

[19]  L. T. Thuong,et al.  THE HEDGING EFFECTIVENESS OF DRY-BULK FREIGHT RATE FUTURES , 1990 .

[20]  S. Johansen Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models , 1991 .

[21]  R. Myers Estimating timevarying optimal hedge ratios on futures markets , 1991 .

[22]  Robert J. Myers,et al.  Bivariate garch estimation of the optimal commodity futures Hedge , 1991 .

[23]  Michael Osterwald-Lenum A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics , 1992 .

[24]  J. Wooldridge,et al.  Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances , 1992 .

[25]  M. Lindahl Minimum variance hedge ratios for stock index futures: Duration and expiration effects , 1992 .

[26]  K. Kroner,et al.  Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures , 1993, Journal of Financial and Quantitative Analysis.

[27]  Asim Ghosh,et al.  Hedging with Stock Index Features: Estimating and Forecasting with Error Correction Model , 1993 .

[28]  Tae-Hwy Lee Spread and volatility in spot and forward exchange rates , 1994 .

[29]  Jesus Gonzalo,et al.  Five alternative methods of estimating long-run equilibrium relationships , 1994 .

[30]  Tim Bollerslev,et al.  Chapter 49 Arch models , 1994 .

[31]  R. Aggarwal,et al.  Global portfolio diversification : risk management, market microstructure, and implementation issues , 1995 .

[32]  G. Lypny,et al.  Hedging short‐term interest risk under time‐varying distributions , 1995 .

[33]  John M. Geppert A statistical model for the relationship between futures contract hedging effectiveness and investment horizon length , 1995 .

[34]  Simultaneously determined, time-varying hedge ratios in the soybean complex , 1995 .

[35]  Lorne N. Switzer,et al.  Bivariate GARCH estimation of the optimal hedge ratios for stock index futures: A note , 1995 .

[36]  R. Engle,et al.  Multivariate Simultaneous Generalized ARCH , 1995, Econometric Theory.

[37]  D. Lien,et al.  The effect of the cointegration relationship on futures hedging: A note , 1996 .

[38]  Tae-Hwy Lee,et al.  Cointegration tests with conditional heteroskedasticity , 1996 .

[39]  K. Kroner,et al.  Program trading, nonprogram trading, and market volatility , 1997 .

[40]  Manolis G. Kavussanos,et al.  The dynamics of time-varying volatilities in different size second-hand ship prices of the dry-cargo sector , 1997 .

[41]  Taufiq Choudhry Short‐run deviations and volatility in spot and futures stock returns: Evidence from Australia, Hong Kong, and Japan , 1997 .

[42]  Estimation of Time-Varying Hedge Ratios for Corn and Soybeans: BGARCH and Random Coefficient Approaches , 1997 .

[43]  Manolis G. Kavussanos,et al.  The forward pricing function of the shipping freight futures market , 1999 .