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| Title: | 台灣股市的成交量預測_以主成分分析為例
Forecasting the Trading Volume in Taiwan Stock Market by Principle Components |
| Authors: | 陳鈺淳
Chen, Yu Chun |
| Contributors: | 郭維裕
鄭鴻章
Kuo, Wei Yu
Cheng, Hung Chang
陳鈺淳
Chen, Yu Chun |
| Keywords: | 主成分分析
成交量預測
總體因子
principle components
forecast
macroeconomic data |
| Date: | 2011 |
| Issue Date: | 2012-10-30 10:55:23 (UTC+8) |
| Abstract: | 本論文探討利用總體因子預測台灣股市的月成交量，並討論其預測準確度。總體因子主要利用主成分分析法從大量的總體資料中抽出，台灣股市月成交量資料主要來自TEJ資料庫，並將其分為九類：水泥窯業、食品業、塑膠化工業、紡織業、機電業、造紙業、營建業、金融業和加權指數。
結果發現三個月後的預測值比一個月後的預測值準確，而從RMSE跟MAE的結果，發現食品業、塑膠化工業、紡織業、機電業、造紙業預測的準確度較高。
This paper discusses forecasting monthly turnover by static principle components method, and testing accuracy of forecasting. The monthly turnover is from Taiwan stock market as nine turnover classification, Cement & Kiln industry, Food industry, Plastic & Chemical industry, Textile industry, Mechanical & Electrical industry, Paper-making industry, Construction industry, Financial industry and Value-Weighted Index. The principle components extracted from large macroeconomic datasets have the explanatory power to monthly turnover. In addition, for basic forecasting, the accuracy of three-month prediction is better than one-month prediction in both subsamples. To test accuracy, RMSE (PC) and MAE (PC) are outperformed the same in Food industry, Textile& Fibers industry. However, MAE (PC) in Plastic & Chemical industry, RMSE (PC) in Mechanical & Electrical industry and Paper-making industry still show the good prediction as well. |
| Reference: | References
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Lo, A. W., Wang, J. (2000). "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," Review of Financial Studies 13(2, Summer): 257-300.
Madhavan, A. N. (2002). "VWAP Strategies Transaction Performance," Institutional Investor Journals Spring 2002 (Transaction Performance): 32-39.
Martell, F. T., Wolf, A. S. (1987). "Determinants of Trading Volume in Futures Markets," Journal of Futures Markets 7 (3): 233-244.
Schumacher, C., Bundesbank, D. (2007). "Forecasting German GDP Using Alternative Factor Models Based on Large Datasets," Journal of Forecasting 26(4): 271-302.
Stock, J. H., Watson, M. W. (2002). "Forecasting Using Principle Components from a Large Number of Predictors," Journal of the American Statistical Association 97: 1167-1179. |
| Description: | 碩士
國立政治大學
國際經營與貿易研究所
99351031
100 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0099351031 |
| Data Type: | thesis |
| Appears in Collections: | [國際經營與貿易學系 ] 學位論文
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