股票特质波动率、股票收益与投资者情绪

摘要

Systematic risk is priced only in the cross-sectional stock returns based on the traditional asset pricing models.Howev-er, idiosyncratic risk may not be fully diversified as market is imperfect and idiosyncratic risk is positively related to stock returns (Merton, 1987).Ang, Hodrick, Xing and Zhang (2006, 2009) suggest a negative relationship between idiosyncratic risk and stock returns, which makes idiosyncratic volatility one of the most popular asset pricing puzzles, called the“idiosyncratic volatili-ty puzzle”.Recent studies have re-examined the relationship between idiosyncratic volatility and stock returns, and reached con-tradictory conclusions.In emerging economies, like China, the capital markets are dominated by individual investors, where the stock prices are more likely to be affected by investor sentiment and noise trading.This paper investigates the dynamic relation-ship between the idiosyncratic volatility, the stock returns and the investor sentiment from both theoretical and empirical perspec-tives.First, this paper incorporates the noise traders affected by investor sentiment into the capital market equilibrium model with incomplete information of Merton (1987).The theoretical results indicate that the idiosyncratic volatility and the stock return are positively correlated, and the elasticity of expected excessive returns with respect to the idiosyncratic volatility is an increasing function of investor sentiment and noise traders.And then, we investigate the role of idiosyncratic risk as a systematic factor in the asset pricing process.Particularly, we present the idiosyncratic risk premium as a source of systematic risk factor capturing the returns of buying stocks with the highest idiosyncratic risk and selling stocks with the lowest idiosyncratic risk.The mid-term HaoDan Index, which is released by Stock Market Trend Analysis Weekly in China, is used as investor sentiment indicator.By employing the data from Shanghai Stock Exchange from 2007 to 2012 and utilizing the directed acyclic graphs ( DAG) to identify the structural VAR model, we find that the investor sentiment and market liquidity play an important role in indicating the differ-ence in returns between stocks with high idiosyncratic volatility and stocks with low idiosyncratic volatility.We find that the cross-sectional differences in returns between stocks with high idiosyncratic volatility and stocks with low idiosyncratic volatility ( IVF) in China′s stock market will be higher when the investors are more optimistic and the market is more liquid.This study is of great help to a better understanding of investor behaviour and the relation between idiosyncratic volatility and stock return in China.%从理论和实证两个角度分析股票特质波动率、股票收益与投资者情绪之间的动态关系。将受投资者情绪影响的噪声投资者引入 Merton 基于不完全信息的市场均衡模型，以2007年至2012年沪、深两市A股上市公司数据为样本，运用有向无环图（ DAG ）技术识别SVAR模型，实证检验股票特质波动率与股票收益和投资者情绪的相关性。研究结果表明，股票特质波动率与股票收益正相关；股票收益率对股票特质波动率的弹性，随着投资者情绪的增加和噪声投资者比例的上升而增大。投资者情绪和股市流动性是影响中国股票市场高特质波动股票与低特质波动股票截面收益差异大小的重要原因。投资者越乐观、市场上流动性越强，高特质波动组合收益率与低特质波动组合收益率的截面差异就越大。研究结果有利于加深对投资者行为的认识，从更符合中国资本市场情况的角度分析股票特质波动率与股票收益的关系。