前景理论、波动不对称与资产定价
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摘要
实证研究表明波动不对称性现象普遍存在于全球金融市场,而对此现象的探究也一直都是理论和实践所关注的焦点。不对称波动不仅是资产定价、投资组合以及风险管理中的一个重要影响因素,而且还是反映一个国家证券市场发展水平的重要指标,集中体现了证券市场的质量和效率。因此,继续深入探究市场波动不对称现象的内在形成机理无疑是理解和把握金融市场运行规律的一条重要途径,并且具有重大的理论和实践意义。
具体地,本文的研究工作主要包括两部分:
首先,关于波动不对称现象目前存在两种经典解释:“波动反馈效应”和“杠杆效应”。但是随着对此现象的深入认识和大量研究,人们开始对这两种解释产生极大地质疑,同时开始尝试基于行为金融理论从投资者心理和行为角度探究市场波动不对称性的成因。本文正是沿此思路,引入前景理论对投资者的决策偏好加以刻画从而构造一类依据前景理论为决策框架的投资者,运用对此类研究具有天然优势的计算实验金融方法(ACF),以异质决策偏好投资者的微观交互为研究视角,自底向上地探究市场波动不对称现象的内在形成机理。
其次,从本文研究可知前景理论深刻影响着资产价格的形成过程,在市场中发挥着重要的作用。建立科学合理的前景理论资产定价模型对于资产定价效率的提高、投资组合策略的构造、风险管理能力的提升等又都具有重要的指导价值。但是,目前已有基于前景理论的相关资产定价模型并未脱离于传统资产定价研究框架,采用的价值函数也多以分段线性函数表示,无法切实体现投资者的真实决策偏好或投资行为,尤其缺乏在真实市场中的实践指导价值。因此,本文进一步在前述分析的基础上,以我国证券市场为背景,直接从前景理论出发,最终构建了适用于我国市场条件并且具有较高实践指导价值的前景理论资产定价模型,并得到了基于中国市场经验数据的实证支持。
总之,本文创新地运用计算实验金融方法从前景理论较好地解释了波动不对称现象,同时在此基础上构建了适用于我国市场条件并且更具实践指导价值的前景理论资产定价模型,从而进一步发展并完善了行为资产定价理论。
The phenomenon of asymmetric volatility is discovered widely in global financial markets by a number of empirical studies, and it has been the research focus in theory and practice. The asymmetric volatility which embodies the quality and efficiency of the stock market is not only an important factor which affects the asset pricing, the portfolio and the risk management but also an indicator which reflects the level of the stock market's development. Therefore, it is very important to study the intrinsic formation mechanism of the asymmetric volatility in order to understand and grasp the law of the financial markets.
Specially, there are two parts in this paper:
First, there are two classic explanations for the phenomenon of asymmetric volatility: "volatility feedback effect" and "leverage hypothesis". However, with further understanding this phenomenon, people began to question two explanations above by extensive researches. Meanwhile, a lot of researches tried to explore the causes of the volatility asymmetric from the perspective of investor psychology and behavior according to some theoretical work in behavioral finance. In the light of above-mentioned thinking, a kind of investor is specified with general decision preference characteristics on prospect theory. Then this paper applies the method of Agent-based Computational Finance (ACF) which has the natural advantage for this research, and explores the inherent formation mechanism of the volatility asymmetric adopting bottom-up modeling strategy from the scope of heterogeneous preferences investors’interaction. The obvious characteristic of this method is to model individual-orientedly, by which the wealth accumulation and decision-making preference of investors could be edited, so that it just provides us with a perfect technical foundation in order to bottom-up explore the phenomenon of volatility asymmetric conveniently from the perspective of investors’interaction with heterogeneous preferences .
In addition, it is known that prospect theory has a profound effect on formation process of asset price, and plays an important role in finance market. Establishing a scientific and rational asset pricing model under prospect theory is very important for enhancing asset pricing efficiency, constructing investment portfolio strategies, improving risk management power. However, there are some deficiencies among these asset pricing models basing on prospect theory. Especially, these models do not deviate from the traditional asset pricing framework, and mainly use the piecewise linear value function, lastly induce that these models could not effectively reflect the real decision preferences or activities of investors and particularly lack the practical guidance value in the real market. Therefore, according to the foregoing analysis, this paper directly from the prospect theory further constructs a prospect theory-based asset pricing model adaptive under the background of China Securities Market. Lastly it has gotten the empirical support basing on China market data.
In a word, this paper innovatively applied the method of Agent-based Computational Finance (ACF) to explain the phenomenon of volatility asymmetric from the scope of prospect theory, and constructed the prospect theory-based asset pricing model adaptive for the condition of China Securities Market, improving the behavioral asset pricing theory further.
具体地,本文的研究工作主要包括两部分:
首先,关于波动不对称现象目前存在两种经典解释:“波动反馈效应”和“杠杆效应”。但是随着对此现象的深入认识和大量研究,人们开始对这两种解释产生极大地质疑,同时开始尝试基于行为金融理论从投资者心理和行为角度探究市场波动不对称性的成因。本文正是沿此思路,引入前景理论对投资者的决策偏好加以刻画从而构造一类依据前景理论为决策框架的投资者,运用对此类研究具有天然优势的计算实验金融方法(ACF),以异质决策偏好投资者的微观交互为研究视角,自底向上地探究市场波动不对称现象的内在形成机理。
其次,从本文研究可知前景理论深刻影响着资产价格的形成过程,在市场中发挥着重要的作用。建立科学合理的前景理论资产定价模型对于资产定价效率的提高、投资组合策略的构造、风险管理能力的提升等又都具有重要的指导价值。但是,目前已有基于前景理论的相关资产定价模型并未脱离于传统资产定价研究框架,采用的价值函数也多以分段线性函数表示,无法切实体现投资者的真实决策偏好或投资行为,尤其缺乏在真实市场中的实践指导价值。因此,本文进一步在前述分析的基础上,以我国证券市场为背景,直接从前景理论出发,最终构建了适用于我国市场条件并且具有较高实践指导价值的前景理论资产定价模型,并得到了基于中国市场经验数据的实证支持。
总之,本文创新地运用计算实验金融方法从前景理论较好地解释了波动不对称现象,同时在此基础上构建了适用于我国市场条件并且更具实践指导价值的前景理论资产定价模型,从而进一步发展并完善了行为资产定价理论。
The phenomenon of asymmetric volatility is discovered widely in global financial markets by a number of empirical studies, and it has been the research focus in theory and practice. The asymmetric volatility which embodies the quality and efficiency of the stock market is not only an important factor which affects the asset pricing, the portfolio and the risk management but also an indicator which reflects the level of the stock market's development. Therefore, it is very important to study the intrinsic formation mechanism of the asymmetric volatility in order to understand and grasp the law of the financial markets.
Specially, there are two parts in this paper:
First, there are two classic explanations for the phenomenon of asymmetric volatility: "volatility feedback effect" and "leverage hypothesis". However, with further understanding this phenomenon, people began to question two explanations above by extensive researches. Meanwhile, a lot of researches tried to explore the causes of the volatility asymmetric from the perspective of investor psychology and behavior according to some theoretical work in behavioral finance. In the light of above-mentioned thinking, a kind of investor is specified with general decision preference characteristics on prospect theory. Then this paper applies the method of Agent-based Computational Finance (ACF) which has the natural advantage for this research, and explores the inherent formation mechanism of the volatility asymmetric adopting bottom-up modeling strategy from the scope of heterogeneous preferences investors’interaction. The obvious characteristic of this method is to model individual-orientedly, by which the wealth accumulation and decision-making preference of investors could be edited, so that it just provides us with a perfect technical foundation in order to bottom-up explore the phenomenon of volatility asymmetric conveniently from the perspective of investors’interaction with heterogeneous preferences .
In addition, it is known that prospect theory has a profound effect on formation process of asset price, and plays an important role in finance market. Establishing a scientific and rational asset pricing model under prospect theory is very important for enhancing asset pricing efficiency, constructing investment portfolio strategies, improving risk management power. However, there are some deficiencies among these asset pricing models basing on prospect theory. Especially, these models do not deviate from the traditional asset pricing framework, and mainly use the piecewise linear value function, lastly induce that these models could not effectively reflect the real decision preferences or activities of investors and particularly lack the practical guidance value in the real market. Therefore, according to the foregoing analysis, this paper directly from the prospect theory further constructs a prospect theory-based asset pricing model adaptive under the background of China Securities Market. Lastly it has gotten the empirical support basing on China market data.
In a word, this paper innovatively applied the method of Agent-based Computational Finance (ACF) to explain the phenomenon of volatility asymmetric from the scope of prospect theory, and constructed the prospect theory-based asset pricing model adaptive for the condition of China Securities Market, improving the behavioral asset pricing theory further.
引文
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