题名

The Return-Risk Tradeoff Relationship of Tanker Shipping Freight Indices

并列篇名

油輪運價指數之報酬與風險抵換關係

DOI

10.6665/JLYIT.2016.15.1

作者

張超琦(Chao-Chi Chang)

关键词

油輪運價指數 ; 長期記憶 ; 風險溢酬係數 ; Tanker Shipping Freight Indices ; Long Memory ; Risk Premium Coefficient

期刊名称

蘭陽學報

卷期/出版年月

15期(2016 / 07 / 01)

页次

1 - 11

内容语文

英文

中文摘要

本文旨在探究油輪運費指數的報酬與風險抵換關係。研究結果顯示,BDTI指數在偏態t分配的長期記憶GARCH模型(FIGARCH及HYHARC)下,其風險與報酬為正相關且顯著;但是,BCTI指數在長期記憶GARCH模型(FIGARCH及HYHARC)下,其風險與報酬的關係皆不顯著。因此,對於油輪運價指數的報酬與風險抵換關係的估計,可將此結果納入考量,並可將其運用在實務界從事油輪運費市場之風險管理。

英文摘要

This study aims to investigate whether we may find the return-risk tradeoff relationship among the observations of tanker shipping freight indices. We estimate the risk premium coefficient and test the significance concerning the GARCH, FIGARCH, HYHARCH and FIEGARCH models. Our results show that the risk premium coefficients, coefficients of ARCH-in-mean, for BDTI are positive and significant under the skewed Student-t distribution concerning the GARCH, FIGARCH and HYHARCH models. However, the return-risk tradeoff relationship doesn't exist for BCTI concerning the GARCH, FIGARCH, HYHARCH and FIEGARCH models. That means the higher risk of BDTI gives us the possibility of higher returns, but it also means higher potential losses. However, the situation doesn't exist for the BCTI. Our results suggest that we could extend these findings to the risk management in the tanker shipping freight markets.

主题分类 人文學 > 人文學綜合
基礎與應用科學 > 基礎與應用科學綜合
醫藥衛生 > 醫藥衛生綜合
生物農學 > 生物農學綜合
工程學 > 工程學綜合
社會科學 > 社會科學綜合
社會科學 > 社會學
参考文献
  1. Chang, C.C.(2013).Long Memory Analysis of Tanker Freight Rates.Journal of Lang-Yang Institute of Technology,12,61-76.
    連結:
  2. Chou, H.C.,Chang, C.C.(2011).The Return-Risk Trade-off Relationship of Baltic Dry Index.Journal of Logistics and Management,10(2),31-39.
    連結:
  3. Baillie, R.T.,Bollerslev, T.,Mikkelsen, H.O.(1996).Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity.Journal of Econometrics,73(1),151-184.
  4. Bollerslev, T.(1986).Generalized autoregressive conditional heteroskedasticity.Journal of Econometrics,31,307-327.
  5. Bollerslev, T.,Mikkelsen, H.O.(1996).Modelling and Pricing Long Memory in Stock Market Volatility.Journal of Econometrics,11(05),447-469.
  6. Chang, C.C.,Chou, H.C.,Wu, C.C.(2014).Value-at-Risk Analysis of the Asymmetric Long Memory Volatility Process of Dry Bulk Freight Rates.Maritime Economics & Logistics,16(3),298-320.
  7. Chen, Y.S.,Wang, S.T.(2004).The empirical evidence of the leverage effect on volatility in international bulk shipping market.Maritime Policy & Management,31(2),109-124.
  8. Davidson, J.(2004).Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and a New Model.Journal of Business & Economic Statistics,22(1),16-29.
  9. Geweke, J.,Porter-Hudak, S.(1983).The estimation and application of long memory time series models.Journal of time series analysis,4(4),221-238.
  10. Kavussanos, M. G.(2003).Time Varying Risks among Segments of the Tanker Freight Markets.Maritime Economics and Logistics,5(3),227-250.
  11. Kavussanos, M.G.(1996).Price risk modelling of different size vessels in tanker industry using Autoregressive Conditional Heteroscedasticity (ARCH) models.Logistics and Transportation Review,32(2),161-176.
  12. Kavussanos, M.G.,Dimitrakopoulos, D.N.(2011).Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets.International Review of Financial Analysis,20(5),258-268.
  13. Laulajainen, R.(2008).Operative Strategy in Tanker (Dirty) Shipping.Maritime Policy and Management,35(3),313-339.
  14. Nelson, D.B.(1991).Conditional Heteroskedasticity in Asset Returns: A New Approach.Econometrica,59(2),347-370.
  15. Phillips, P.C.B.,Shimotsu, K.(2004).Local Whittle estimation in nonstationary and unit root cases.The Annals of Statistics,32(2),656-692.
  16. Robinson, P.M.(1995).Gaussian Semiparametric Estimation of Long-Range Dependence.Annals of Statistics,23,1630-1661.
  17. Robinson, P.M.,Henry, M.(1999).Long and Short Memory Conditional Heteroskedasticity in Estimating the Memory Parameter in Levels.Economic Theory,15,299-336.
  18. Robinson, P.M.,Zaffaroni, P.(1998).Nonlinear time series with long memory: a model for stochastic volatility.Journal of Statistical Planning and Inference,68(2),359-371.
  19. Stopford, M.(2009).Maritime Economics-3rd Edition.Routledge.