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A regime switching approach for hedging tanker shipping freight rates

TLDR
In this paper, the authors investigate the performance of alternative hedging methods, including a bivariate Markov Regime Switching GARCH model, in hedging tanker freight rates and find evidence supporting the argument that the tanker freight market is characterized by different regimes.
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This article is published in Energy Economics.The article was published on 2015-05-01 and is currently open access. It has received 58 citations till now.

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A survey of shipping finance research: setting the future research agenda

TL;DR: In this article, a comprehensive and structured survey of all published research in the area of shipping finance and investment is presented, including 162 studies published in 48 scholarly journals, complemented with select books and book chapters.
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Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach

TL;DR: In this article, the authors employed a GARCH-Copula-CoVaR approach to address the debate on the extreme risk spillovers from commodity market to maritime market and provided new evidence regarding risk transmission from oil and ex-energy sector to the maritime markets, as well as the interactions between different subsectors of maritime market.
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The Minimum-CVaR strategy with semi-parametric estimation in carbon market hedging problems

TL;DR: In this article, a semi-parametric approach with Cornish-Fisher expansion, which approximates the quantile using the higher moments of the distribution, is provided to estimate hedging ratios using CVaR as risk objective function.
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Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war

TL;DR: In this paper, the authors employ the tri-variate Markov regime switching (MRS) copula model to investigate the dynamic dependence between the shipping freight and stock markets.
References
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Estimating the Dimension of a Model

TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.

Estimating the dimension of a model

TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
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Co-integration and Error Correction: Representation, Estimation and Testing

TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
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Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation

Robert F. Engle
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TL;DR: In this article, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced, which are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances.
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Testing for a Unit Root in Time Series Regression

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Q1. What are the contributions mentioned in the paper "A regime switching approach for hedging tanker shipping freight rates" ?

The aim of this paper is to investigate the performance of these instruments in managing tanker freight rate risk. Using a data set for six major tanker routes covering the period between 2005 and 2013, the authors examine the effectiveness of alternative hedging methods, including a bivariate Markov Regime Switching GARCH model, in hedging tanker freight rates. 

The authors provide three explanations for the poor performance of tanker FFAs for risk management. The future for freight futures ? The case of the futures-cash basis. 

A primary instrument used by tanker shipping market participants to manage theirfreight exposure risk is forward freight agreements (FFAs). 

There are other alternative freight risk management techniques available to the participants in the tanker industry which includes time-charter contracts, contracts of affreightment (CoAs), and freight options. 

In addition, Investigating the hedging effectiveness of contracts with different delivery choices, Pirrong, et al. (1994) argue that having multiple delivery choices can reduce liquidity and increase basis risk, which in turn reduces the hedging effectiveness. 

Because the conditional moments can change as new information arrives in the market and the information set is updated, it is believed that the time-varying hedge ratios should provide superior risk reduction compared to conventional and static hedges. 

The main approach proposed in the literature to deal with structural shifts and regimechanges in the behaviour and relation between variables is the Markov Regime Switching (MRS) model (Hamilton, 1989). 

The second possible explanation for the poor hedging performance of tanker FFAs isrelated to the weak linkage between the spot and FFA prices. 

In fact, it seems that the best out-of-sample hedging performance in terms of variance reduction is realized when the naïve and conventional hedging strategies are employed. 

According to the coefficients of excess kurtosis and Jarque-Bera statistics (Jarque and Bera, 1980), the spot and FFA returns series appear to significantly depart from normality and to be leptokurtic, which is consistent with the demand and supply pattern of shipping markets. 

For instance, Kavussanos and Visvikis (2004a, 2010) examine the effectiveness of dry-bulk FFAs as a risk management instrument for Panamax and Capesize freight rates. 

In order to integrate the state dependent variances and residuals, the authors use Gray’s (1996) integrating method as adopted by Lee and Yoder (2007). 

Given that hedgers are interested in obtaining an ex-ante indication of their potentialexposure, the authors extend their analysis further to determine whether the MRS-GARCH model can improve the out-of-sample hedging performance of tanker FFAs.