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|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|11185||2013||5 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Economic Modelling, Volume 35, September 2013, Pages 30–34
A large number of researches have shown that the negative return of risky asset exists and has the profound significance whether for actual investment or theory studies. This paper investigates the effect of sentiment by establishing the sentiment asset pricing model, and explores the negative expected return when the parameters change in different situations. We provide the necessary and sufficient conditions for the negative expected return.
The annual rate of return is assumed to be positive in the traditional financial theory, but the negative return of risky asset does exist in the reality financial market, and it has profound significance whether for actual investments or theory researches. For example, Ang et al., 2006 and Ang et al., 2009 found a idiosyncratic volatility puzzle, and constructed a zero-investment portfolio that is long the most volatile portfolio and short the least volatile portfolio yields about − 1% the following month. Bali et al. (2011) found a negative and significant relation between the maximum daily return over the past one month and expected stock returns, i.e., the expected return of stock is negative when the current biggest daily return of stock is higher. Eleswarapu and Thompson (2007) indicated that an unsustainably high price will cause price bubble, and the expected return premium is negative, which is different from the implicit assumption that the expected return premium is positive in traditional asset equilibrium price model (see, e.g., Breeden, 1979, Cox et al., 1985 and Merton, 1971). The different fluctuations of stock prices are caused by the investor cognitive biases and psychological factor of asset demand, but not fundamentals in the short term, so behavioral asset pricing model considering investor biases of psychology and behavior can better depict the fluctuations of asset prices compared to traditional asset pricing model based on rational expectations, even can more reasonably depict the characteristic of negative expected return. In the study of considering investor psychological factors, the asset pricing models based on the noise and biases are the most important and the most fruitful achievements. For example, the most famous study on the asset pricing model based on noise traders is DSSW model of De Long et al. (1990), which distinguished investors between sophisticated investors and noise traders, and explored the asset equilibrium price. And the asset pricing models based on biases mainly have the BSV model of Barberis et al. (1998), the DHS model of Daniel et al. (1998), the HS model of Hong and Stein (1999), the BHS model of Barberis et al. (2001). However, compared to the latest researches based on investor sentiment in behavioral finance, both the researches based on noise and the researches based on biases are facing the following shortcomings. Firstly, the abstractions of biases and noise are unfathomable, so these models can't do the empirical analysis and inspection. However, the existing empirical researches on investor sentiment have resolved the measurement of sentiment and a consensus has emerged among educational circles that the sentiment is easy to measure no matter what proxy variables we use to represent sentiment. Secondly, the researches on noise and biases lack the support of the corresponding behavior experiments and neural experiments, but these experiments based on investor sentiment have rich experimental results and strong experimental evidences. Therefore, the asset pricing researches based on investor sentiment can get more useful conclusions. Some asset pricing models have been developed to support the role of investor sentiment, such as Yang et al. (2012), Yang and Yan (2011), and Yang and Zhang, 2013a and Yang and Zhang, 2013b. Yang et al. (2012) presented a sentiment capital asset pricing model, and showed that investor sentiment is a nonlinear systematic factor for asset pricing. Yang and Zhang (2013a) presented a sentiment asset pricing model with consumption, and showed that the stock price has a wealth-weighted average structure and the investor's wealth proportion could amplify the sentiment shock on the asset price. Yang and Zhang (2013b) presented a dynamic asset pricing model with heterogeneous sentiment and found that the equilibrium stock price is the wealth-share-weighted average of the stock prices that would prevail in an economy with a sentiment investor only. Moreover, heterogeneous sentiments induce fluctuations in the wealth distribution, which increases the stock return volatility and induces mean reversion in stock returns. Therefore, this paper explores the effect of investor sentiment on risky asset price by constructing and analyzing the sentiment asset pricing model and investigates when the expected return of risky asset will be negative by analyzing the different changes of the parameters in the sentiment asset pricing model. The analysis of the sentiment asset pricing model provides evidence for that asset's future price declines when the market sentiment is down, so the expected return of risky asset is negative. The remainder of this paper is organized as follows. In Section 2, we construct and discuss the sentiment asset pricing model. Section 3 analyzes the expected negative returns by changing investor sentiment, the number of sentiment investors and the supply volume in the sentiment asset pricing model. Lastly, Section 4 presents our conclusion and future researches.
نتیجه گیری انگلیسی
The capital asset pricing problem is a kernel one in modern financial theory. However, many phenomena of abnormal investor behavior and financial anomalies which didn't satisfy the standard financial theory emerged in the security market since the end of 1970s. Henceforth, the academia began to introspect into the rationality of basic hypotheses for standard financial theories. On this basis, an analysis framework of behavioral finance was constructed gradually. For the capital asset pricing models based on behavioral finance, there are two main approaches nowadays, one is based on the noise, and the other one is based on the biases. However, both the researches based on noise and the researches on biases are facing two shortcomings. Firstly, the abstractions of biases and noise are unfathomable, so these models can't do the empirical analysis and inspection. Secondly, the researches on noise and biases are lack of the support of the corresponding behavior experiments and neural experiments. The research of investor sentiment, as a great branch of behavioral finance, solved these two problems. Investor sentiment is easy to be measured by using some proxy variables, and also is supported by some behavior experiments and neural experiments. On the other hand, most of the capital asset pricing models initially assume that the long-run expected return is positive and ignore the situation of negative expected return which exists and has profound significance whether for actual investments or theory researches. Therefore, this paper investigates the effect of sentiment on the price and return of risky asset, and explores the idea that expected return is negative when the parameters change in different situations. In this paper, we established the sentiment asset pricing model and obtained the analytical expression of asset price. Furthermore, we investigated when the expected return of risky asset will be negative by analyzing the different changes of the parameters. The conclusions from the analysis of sentiment asset pricing model are obvious and intuitionistic. The analysis of sentiment asset pricing model provides evidence for that asset's expected price declines when the overall market sentiment is down, so the expected return of risky asset is negative. And the risky asset prices and its supply decrease monotonically, while risky asset prices increase monotonically with the number of its investors. These conclusions are consistent with stock price behavior in actual stock market. For the further research, some conclusions in this paper should be validated by using the actual market data. Many other problems, just like excessive return, bubbles and inside information, could be analyzed based on the sentiment asset pricing model.