Value-at-risk analysis of the asymmetric long-memory volatility process of dry bulk freight rates

This study aims to apply value-at-risk (VaR) models to evaluate the risk of dry bulk freight rates when there is an asymmetric long-memory volatility process. The VaR estimations as well as expected shortfalls for both short and long trading positions are conducted. We use the Fractionally Integrate...

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Veröffentlicht in:	Maritime economics & logistics 2014-09, Vol.16 (3), p.298-320
Hauptverfasser:	Chang, Chao-Chi, Chih Chou, Heng, Chou Wu, Chun
Format:	Artikel
Sprache:	eng
Schlagworte:	Business and Management Forecasting techniques Freight Logistics Operations Management Original Article Rates Risk analysis Shipping industry Stochastic models Studies Time series Volatility
Online-Zugang:	Volltext
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