The Construction, Forecasting and Applications of the Composite Sentiment Index in Dry-Bulk Shipping Market

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基本資料

Project title

Code/計畫編號

MOST107-2410-H019-025

Translated Name/計畫中文名

散裝海運市場綜合情緒指標之建構、預測與運用

Project Coordinator/計畫主持人

Heng-Chih Chou

Funding Organization/主管機關

National Science and Technology Council

Department/Unit

Department of Shipping and Transportation Management

Website

https://www.grb.gov.tw/search/planDetail?id=12677637

Year

2018

Start date/計畫起

01-08-2018

Expected Completion/計畫迄

31-07-2019

Bugetid/研究經費

585千元

ResearchField/研究領域

經濟學

過去文獻多是藉由運力供給與需求，以分析運價波動行程。行為財務學興起之後，學術界開始探討市場情緒(market sentiments)對資產價格的影響。近年來學術界著重編制適當的情緒指標以衡量市場情緒，多數實證結果也支持情緒指標對資產價格的解釋力。然而，行為財務學在海運市場的研究剛在起步。海運市場是個複雜的市場，由新船、二手船、運價以及拆船市場所組成。而且作為物流運輸業的一環，海運屬於衍生的需求，深受總體經濟循環所影響。因此單一情緒指標可能僅捕捉到某一面向，而忽略其他重要面向。若能建構一個綜合情緒指標，抽取各船型市場以及總體經濟的關鍵因子，應更能反映整體海運市場的情緒。所以，本計畫將整合 Papapostolou et al. (2014)所提的5種情緒指標：船舶募資、船舶本益比、二手/新造船價比、船舶淨變動以及船舶周轉率，加上代表總體經濟的『市場利率』與『原油價格』因子，一共7個單一情緒指標以建構綜合指標。本計畫擬利用主成份分析法，首先分別針對散裝船的四種船型，整合7種因子成為各船型的市場情緒指標，一共先產生四個市場情緒指標。其次，擬再次利用主成份分析法，整合各船型的市場情緒指標，建構一個散裝海運市場的綜合情緒指數，以完整衡量暨分析散裝航運市場的投資人情緒以及情緒的轉變。在建構綜合情緒指標之後，本計畫擬進一步分析此綜合情緒指標的時間序列特性，以及情緒指標與運價（報酬率及波動性）的互動關係。本計畫將分別就各船型的綜合情緒指標，分別以適當落後期的自我迴歸移動平均模型(ARMA)配適其行程，並以樣本外資料檢測ARMA模型的預測績效。接著擬以向量自我迴歸（VAR）的Granger 因果分析以檢測綜合情緒指標與運價的領先落後關係，最後則擬以適當的波動模型(volatility model)檢測綜合情緒指標對於運價波動的影響。本計畫擬採用『EGARCH』與『ACARR模型』兩類不對稱波動模型，探討情緒指標對運價波動率的影響是否呈現不對稱性效果。The topic of this study is “The construction, forecasting, and applications of the composite sentiment index in dry-bulk shipping market,” and the purpose of the study is to understand whether the market sentiments significantly affect the dry-bulk freight rates, to help the industry forecast and manage freight rate risk, and ultimately increase the operation efficiency. This study plans to use seven sentiment proxies including two macroeconomic factors, LIBOR and Brent oil price, and five industry factors proposed by Papapostolou et al. (2014) to construct a composite sentiment index for the dry-bulk shipping market. The results of the study will help us grasp the behavioral characteristics of freight rate risk, and manage the risk successfully as well. The sampling data for testing in the study include the monthly data of the four vessel types in dry bulk shipping: capsize, panamax, handysize and supramax. Overall, the purpose of the study includes the following parts: (1) using principal component approach to construct an individual sentiment index for each dry-bulk vessel market, (2) constructing a composite sentiment index for the whole dry-bulk market, (3) fitting adequate ARMA for sentiment index time series data and testing the forecasting performance, (4) examining the lead-lag relationship between sentiment index and freight rate, and (5) exploring the impact of sentiment index on freight rate volatilities. The sample period is from 1996/01 to 2017/12, and the monthly data will be collected and analyzed. The results of the study will not only provide some valuable knowledge regarding the dynamics of freight rate risk, but also make up for the shortage of literature in this area. The results of the research can make up for the lack of literature, extend many follow-up studies, and help the shipping industry to grasp the market sentiment.

Keyword(s)

散裝航運
運價風險
主成份分析
情緒指標
Dry-bulk Shipping
Freight Rate Risk
Principal Component Approach
Market Sentiments

DSpace CRIS

The Construction, Forecasting and Applications of the Composite Sentiment Index in Dry-Bulk Shipping Market

基本資料

Description