Transfer of Freight Rate Volatility on Ship Sale and Purchase Prices

Document Type : Original Article

Author

Assistant Professor, Department of Marine Transport, Faculty of Economics and Management, Khorramshahr University of Marine Sciences and Technology, Khorramshahr, Iran

Abstract

This study investigates the freight rate volatility and the transfer of volatility to ship sale and purchase market. New-build and second-hand vessels are traded as capital goods; however, since the cost of maintaining a ship is very high, the shipping rate is the most important factor affecting ship's price. Therefore, market agents should have a proper understanding of the freight rate volatility and its impact on ship prices. To address this issue, the GARCH volatility model is used to explore the existence of volatility factors among ship markets, these markets are sale and purchase and the freight fare market. Based on the evaluation of the loss-making functions of the BEKK GARCH model, which considers the distribution of disruptive t-student, a more accurate estimate has been given to obtain a volatility transfer factor among the above markets.
The results show that freight market volatility in exist in VLCC and Suezmax markets based on the sales price index, but the mechanism of volatility is different among different types of ships. The two-way effect of the volatility transition has been observed in all markets, which shows that the lagged variance can affect the current variance in a similar market regardless of the transmission of volatility. A simple ratio is provided to guide investors optimize their cargo allocation. The findings of this paper can provide a good understanding of investment in these markets.
 
 
 

Keywords

References

این مقاله مستخرج از نتایج طرح تحقیقاتی اجرا شده با شماره قرارداد 128 از محل اعتبارات ویژه پژوهشی دانشگاه علوم و فنون دریایی خرمشهر می باشد.
-Alizadeh, A.H. and Nomikos, N.K. (2003), “The price–volume relationship in the sale and purchase market for dry bulk vessels”. Maritime Policy and Management, 30(4), pp.321–37.
-Bollerslev, T. Engle, J. Wooldridge, M. (1988), “A capital asset pricing model with time covariance”, Journal of Political Economy, 96 (1), pp.116-131
-Cullinane, K. (1992), “A short-term adoptive forecasting model for BIFFEX speculation: a Box-Jenkins approach”. Maritime Policy and Management, 19(2), pp.91–114.
-Dai, L. Hu, H. Chen, F. (2014), “Volatility transmission in the dry bulk new building and second-hand markets: Transportation Letters”, 6(2), pp.56-67.
-Engle, R.F. Kroner, K. (1995), “Multivariate simultaneous generalized ARCH”. Econometric Theory, 11 (1).
-Koekebakker, S. and Ådland, R. (2004), “Modelling forward freight rate dynamics—empirical evidence from time charter rates”. Maritime Policy and Management, 68 (5).
-Kroner, K. Ng, V. (1998), “Modelling asymmetric co-movements of asset returns, Review of Financial Studies”, 11 (4).
-Kavussanos, M.G. (1997), “The dynamics of time-varying volatilities in different size second-hand ship prices of the dry-cargo sector”. Applied Economics, 29,
pp.433–443.
-Kavussanos, M.G. and Alizadeh, A.H. (2001), “Seasonality patterns in the dry bulk shipping spot and time charter freight rates. Transportation Research, Part E, 37,
pp.443–67.
-Kavussanos, M.G. and Nomikos, N.K. (2000), Constant vs time varying hedge ratios and hedging efficiency in the BIFFEX market. Transportation Research, 36(4), pp.229–48.
-Lo, A.W. and MacKinlay A.C. (2008), “The size and power of the variance ratio tests in finite samples: a Monte Carlo investigation”. Journal of Econometrics, 40, pp.203–38.
-Sollis, R. (2005), “Predicting returns and volatility with macroeconomic variables – evidence from tests of encompassing. Journal of Forecasting, 24(3), pp.221–31.
-Stopford, M. (1997), “Maritime Economics. London: Routledge.
-Tvedt, J. (2003), “A new perspective on price dynamics of the dry bulk market. Maritime Policy and Management”, 30(3), pp. 221–30.
-Vavra, JS. (2013), “Inflation Dynamics and Time-Varying Volatility:  Quarterly Journal of Economics­”, 129(1), pp.216-257.
Journal of Transportation Research
Volume 15, Issue 2
July 2018
Pages 225-235

Files

Share

How to cite

Statistics