Analysis Of Applicability And Price Estimation Of Shanghai Containerized Freight Index Derivatives

Shanghai Shipping Exchange officially released the new version ofShanghai Containerized Freight Index (SCFI) in2009, followed by thelaunch of related derivatives. Since its release, SCFI derivatives have beendisputed for the difficulty in evaluating its applicability and determiningapplicable conditions for market participants. Besides, there are also scarceclear and in-depth researches on decision making of derivatives exchangeon basis of estimated spot and futures prices. To combat these problems,the thesis discusses SCFI derivatives’applicability and price estimation.The thesis draws on qualitative and quantitative analysis methodswhich were applied to researches of international authoritative shippingfreight indexes. Firstly, it introduces SCFI and its derivatives. Throughcomparison with other freight indexes, it finds SCFI’s volatilitycharacteristics. Besides, it concludes that SCFI derivatives work bestamong small and medium-sized shippers. Then the thesis classifiescontainerized commodities and analyzes the impact of freight rates’volatility on profit of different commodity categories’ export trades to findthe suitable derivatives trade conditions of commodity category and tradeprice terms. Then it studies the interactional relations between SCFIderivatives’ spot and futures prices with cointegration test and causalitytest. After that, this thesis estimates prices using VAR model. Finally, thisthesis estimates the SCFI derivatives’ spot and futures prices which aretreated as independent time sequences using neural network model. Theestimation results are better than VAR model’s results. To conclude, SCFI derivatives market’s applicability is limited. When low price and highdensity commodities are exported in trade business using CIF trade priceterms, the freight fluctuation risk management tool is the most meaningfulfor small and medium-sized shippers. Besides, short-term forecastingbased on VAR model and BP neural network method is effective, and theestimation results of the latter are better. Additionally, under applicableconditions, good estimation of spot and futures prices could help small andmedium-sized shippers to make SCFI derivatives trading decisions.