關鍵字查詢 | 類別:期刊論文 | | 關鍵字:The ARJI-Trend Model

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1 108/1 財金系 黃健銘 助理教授 期刊論文 發佈 Analyzing the Impacts of Foreign Exchange and Oil Price on Biofuel Commodity Futures , [108-1] :Analyzing the Impacts of Foreign Exchange and Oil Price on Biofuel Commodity Futures期刊論文Analyzing the Impacts of Foreign Exchange and Oil Price on Biofuel Commodity FuturesChiang, S.M.; Chen, C.D.; HuangChien-MingCommodity futures;U.S. dollar index;Oil price;ARJI-trend modelJournal of International Money and Finance 96, p.37-48This paper employs an ARJI-trend model that combines the autoregressive jump intensity (ARJI) and component models to analyze the effects of the U.S. dollar index and oil prices on the dynamic properties of biofuel-related commodity futures. The results show that the ARJI-trend model not only provides a better fit for the data on the volatility dynamics of corn, soybean, and wheat futures, but also performs better in terms of out-of-sample forecasting. The U.S. dollar index and oil prices both generate significant impacts on the returns of the futures. Since the coexistence of permanent component, transitory component, and time-varying jumps are observed in thos
2 97/2 財金系 邱建良 教授 期刊論文 發佈 Permanent and Transitory Components in the Chinese Stock Market: The ARJI-Trend Model , [97-2] :Permanent and Transitory Components in the Chinese Stock Market: The ARJI-Trend Model期刊論文Permanent and Transitory Components in the Chinese Stock Market: The ARJI-Trend ModelChiang, Shu-Mei; Yeh, Chin-Piao; Chiu, Chien-Liang淡江大學財務金融學系ARJI-trend model;jump;permanent component;structural break;transitory componentArmonk: M.E. Sharpe, Inc.Emerging Markets Finance and Trade 45(3), pp.35-55This study applies the ARJI-trend model in conjunction with the procedure proposed by Bai and Perron (2003) to investigate the coexistence of permanent and transitory components and time-varying jumps in the A and B stock market indices of the Shanghai and Shenzhen Stock Exchanges. Although the response to outside innovations is greater within the transitory component, it is short-lived; conversely, though there is a high level of persistence in the trend, new information has only a lesser effect on the permanent component. Jump variance can also affect total variance, though the effect is far lower than
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