An empirical study of contrarian and momentum effects in the Japanese stock market

日本股市逆向效应和动量效应的实证研究

• 批准号: 20530265
• 负责人: ISHIDA Isao
• 金额: $ 2.83万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2008
• 资助国家: 日本
• 起止时间: 2008 至 2010
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-20530265/
• 关键词: ファイナンス

This study empirically investigates the profitability of contrarian and momentum investment strategies in the Japanese stock market, using returns and financial statement data of all stocks listed on the first section of the Tokyo Stock Exchange. Contrarian (momentum) strategies buy low-(high-)performing stocks and sell high-(low) performing stocks, based on past returns over various measurement periods. The results for the pricing of the Japanese individual stock prices are at least partially consistent with the predictions of rational asset pricing models, although some of them suggest the possibility of irrational asset pricing expounded by the behavioral finance theory.

本研究利用东京证券交易所第一部上市的所有股票的回报率和财务报表数据，实证研究了日本股票市场逆向投资和动量投资策略的盈利能力。逆势（动量）策略根据不同衡量时期的过去回报，买入低（高）表现股票并卖出高（低）表现股票。日本个股价格的定价结果至少部分符合理性资产定价模型的预测，尽管其中一些暗示了行为金融理论阐述的非理性资产定价的可能性。

项目成果

Forecasting the Nikkei 225 Futures Realized Volatility : Jumps, Leverage, and Spillover Effects from the US Equity Futures Market

预测日经 225 期货实际波动率：美国股指期货市场的跳跃、杠杆和溢出效应

• 发表时间: 2009
• 作者: 石田功

Isao Ishida, Estimating the Leverage Parameter of Continuous-time Stochastic Volatility Models Using High Frequency S & P500 and VIX, Center for the Study of Finance and Insurance Discussion Paper Series 2010-6 (2011)

Isao Ishida，使用高频 S 估计连续时间随机波动率模型的杠杆参数

Testing for Neglected Nonlinearity in Autoregressive Models of Volatility Indices

波动率指数自回归模型中被忽略的非线性测试

• 发表时间: 2011
• 作者: 石田功

Estimating Continuous-Time Stochastic Volatility Models for the S & P 500 Index Using High-Frequency S & P 500 and VIX Data

估计 S 的连续时间随机波动率模型

• 发表时间: 2010
• 作者: 石田功

Estimating Continuous-Time Stochastic Volatility Models for the S & P 500 Index Using High-Frequency S & P 500 and VIX Data

估计 S 的连续时间随机波动率模型

• 发表时间: 2010
• 作者: 石田功