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基于信息分解视角的香港股市运行效率研究
  • ISSN号:1000-6788
  • 期刊名称:《系统工程理论与实践》
  • 时间:0
  • 分类:O212.1[理学—概率论与数理统计;理学—数学] TS934.9[轻工技术与工程]
  • 作者机构:[1]Research Center for Applied Finance, University of International Business and Economics, Beijing 100029,China., [2]School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, China., [3]Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences,Beijing 100190, China.
  • 相关基金:This research was supported by the National Natural Science Foundation of China under Grant No. 71401033.
中文摘要:

The decomposition-based vector autoregressive model(DVAR) provides a new framework for scrutinizing the efficiency of technical analysis in forecasting stock returns. However, its relationships with other technical indicators still remain unknown. This paper investigates the relationships of DVAR model with the Japanese Candlestick indicators using simulations, theoretical explanations and empirical studies. The main finding of this paper is that both lower and upper shadows in Japanese Candlestick Granger contribute to the DVAR model explanation power, and thus, providing useful information for improving the DVAR forecasts. This finding makes sense as it means that the information contained in the lower and upper shadows should be used when modeling the stock returns with DVAR. Empirical studies performed on China SSEC stock index demonstrate that DVAR model with upper and lower shadows as exogenous variables does have informative and valuable out-of-sample forecasts.

英文摘要:

The decomposition-based vector autoregressive model (DVAR) provides a new framework for scrutinizing the efficiency of technical analysis in forecasting stock returns. However, its relation- ships with other technical indicators still remain unknown. This paper investigates the relationships of DVAR model with the Japanese Candlestick indicators using simulations, theoretical explanations and empirical studies. The main finding of this paper is that both lower and upper shadows in Japanese Candlestick Granger contribute to the DVAR model explanation power, and thus, providing useful information for improving the DVAR forecasts. This finding makes sense as it means that the infor- mation contained in the lower and upper shadows should be used when modeling the stock returns with DVAR. Empirical studies performed on China SSEC stock index demonstrate that DVAR model with upper and lower shadows as exogenous variables does have informative and valuable out-of-sample forecasts.

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期刊信息
  • 《系统工程理论与实践》
  • 中国科技核心期刊
  • 主管单位:中国科学技术协会
  • 主办单位:中国系统工程学会
  • 主编:汪寿阳
  • 地址:北京市海淀区中关村东路55号
  • 邮编:100190
  • 邮箱:xtll@chinajournal.net.cn
  • 电话:010-82541407
  • 国际标准刊号:ISSN:1000-6788
  • 国内统一刊号:ISSN:11-2267/N
  • 邮发代号:2-305
  • 获奖情况:
  • 第三届中国出版政府奖提名奖
  • 国内外数据库收录:
  • 荷兰文摘与引文数据库,美国工程索引,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国国家哲学社会科学学术期刊数据库,中国北大核心期刊(2000版)
  • 被引量:56095