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Journal ArticleDOI

A comparison of investors’ sentiments and risk premium effects on valuing shares

TL;DR: In this paper, the authors investigated the extent deviations between market share prices and their fundamental values can be explained by risk premium and/or investors' sentiment effects, based on recent panel data econometric techniques controlling for the effects of unobserved common factors on our estimation and inference procedures.
About: This article is published in Finance Research Letters.The article was published on 2016-05-01 and is currently open access. It has received 9 citations till now. The article focuses on the topics: Liquidity premium & Risk premium.

Summary (2 min read)

1 Introduction

  • Ohlson s model has the following attractive features.
  • Identifying these factors and measuring their explanatory power on share prices can indicate at what extent compared to the observed ones can explain cross-sectional and time-series, total variation of share prices from their fundamental values.
  • Section 2 presents the share price valuation model, while Section 3 the empirical methodology of the paper and it discuss the estimation results.

2 Share valuation

  • These earnings constitute the di¤erence between rm s i earnings Eit+ and its opportunity cost of capital.
  • As it stands, model (1) does not allow for risk premium and/or investors sentiment e¤ects.
  • These e¤ects can explain deviations between the fundamental values of share prices, P it, and their market values, denoted as Pit.
  • On the other hand, investors sentiment e¤ects will tend to overvalue price.
  • Pit during periods of optimism of the market.

3 Empirical analysis

  • To investigate the relative importance of risk premium and/or sentiment e¤ects in explaining deviations of share prices from their fundamental values, i.e., Pit P it, the authors consider the following panel data model: (3) Model (2) considers three di¤erent groups of variables in explaining Pit P it.
  • The rst contains variables zijt, re ecting J-di¤erent rm speci c e¤ects, like the size of a rm i (denoted as SIZE), its earning-price, and its book-to-market and dividend-price ratios, denoted respectively as E=P , B=M and D=P .
  • These variables can capture the Fama-French risk premium factors.
  • These variables are common, for all shares i.
  • Panel data methods enable us to estimate the time series observations of factors fmt from the residuals of model (2), obtained in a rst step, by exploiting the cross-section dimension of the data.

3.1 Data

  • The authors data is expressed in nominal values and have annual frequency.
  • The stock market annual return (MARKET ) is calculated based on the FTSE100 UK price index.
  • The sentiment variable SENT is the percentage change of sentiment index, denoted as SI.
  • Earnings forecasts are based on combined estimates of the analysts about a company s earnings per share that concerns the next scal year.
  • Finally, the results of the table indicate that there is a very small degree of correlation between the rm speci c and macroeconomic variables of the model, which means that these two di¤erent groups of variables may be thought of as independent sources of risks.

3.2 Estimates

  • To estimate model (2), the authors will employ the mean group panel data estimator (see Pesaran and Smith (1995)).
  • Estimates of model (2), with and without unobserved factors fmt, based on the above estimation procedure are presented in Table 2.
  • Regarding the group of macroeconomic variables, their results indicate that TERM , EXCH and DF have a signi cant impact on Pit P it, at the 5% level, for all the speci - cations of the model considered.
  • They indicate that the e¤ects of investors sentiments on Pit P it become stronger than those based on the mean group estimator.
  • This is also true for the speci cation of the model including variable CRISIS into its RHS.

4 Conclusions

  • Based on a share valuation model which relies on analysts earnings forecasts and book values, this paper shows that deviations of the market share prices from their fundamental values can be explained both by risk premium an/or investors sentiment e¤ects.
  • The paper provides clear cut evidence that positive sentiment e¤ects (due, for instance, to investors optimism) lead to overvaluation of the current market share prices, compared to their fundamental values.
  • On the other hand, sentiment e¤ects occurring in periods of nancial crisis, often associated with collapsing bubbles, lead to share price corrections to their fundamental values.
  • Regarding the risk premium e¤ects, the results of the paper show that these can be captured by rm speci c variables, like the book-to-market and dividend-price ratios, and macroeconomic variables, like the spread between long and short term government yields, the change of the three month T-bill rate and the e¤ective real exchange rate.

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Citations
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Posted Content
TL;DR: This article showed that book-to-market, size, and momentum capture cross-sectional variation in exposures to a broad set of macroeconomic factors identified in the prior literature as potentially important for pricing equities.
Abstract: We show that book-to-market, size, and momentum capture cross-sectional variation in exposures to a broad set of macroeconomic factors identified in the prior literature as potentially important for pricing equities. The factors considered include innovations in economic growth expectations, inflation, the aggregate survival probability, the term structure of interest rates, and the exchange rate. Factor mimicking portfolios constructed on the basis of book-to-market, size, and momentum therefore serve as proxy composite macroeconomic risk factors. Conditional and unconditional cross-sectional asset pricing tests indicate that most of the macroeconomic factors are priced. The performance of an asset pricing model based on the macroeconomic factors is comparable to the performance of the Fama and French (1992, 1993) model. However, the momentum factor is found to contain incremental information for asset pricing.

100 citations

Journal ArticleDOI

9 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the effect of investor sentiment on share price deviations from their intrinsic values across two sentiment regimes of shares market: the low-to-normal and the excess one.
Abstract: We investigate the existence of evidence of investor sentiment on share price deviations from their intrinsic values across two sentiment regimes of shares market: the low-to-normal and the excess one. We use the residual income valuation model to calculate the intrinsic values of shares based on accounting fundamentals and we suggest a panel data threshold model to capture the sentiment regimes of the market, using as threshold variable alternative investor sentiment indices. The suggested model enables us, first, to endogenously identify from the data the threshold value of a sentiment index triggering market sentiment regime shifts and, based on it, to examine if the effects of investor sentiment on share prices across the above two sentiment regimes are in accordance to the theory. Application of the model to UK data shows that investor sentiment influences positively share prices in the low-to-normal and negatively in the excess one. We also show that investor sentiment dominates risk premium effects on shares characterized by low book-to-market, and dividend- and earnings-to-price ratios. The above results are consistent with the predictions of the sentiment hypothesis.

2 citations

Posted Content
01 Jan 2018
TL;DR: In this paper, a quasi-rational multifactor asset pricing determinants model with fundamental and behavioural risk factors is introduced, and the risk and return analysis is performed in a factors and style investing framework.
Abstract: This paper offers an alternative perspective on determinants of equity risk using behavioural asset pricing ideology in a factor and style investing framework. First, a quasi-rational multifactor asset pricing determinants model with fundamental and behavioural risk factors is introduced. Then, the risk and return analysis is performed in a factors and style investing framework. The empirical tests are performed on a sample of 238 Malaysian firm stock returns and multifactor risk proxies with monthly frequency using the panel regression method. The baseline and robustness analyses provide evidence to support the dynamic of risk and returns relationships due to quasi-rational risk determinants and given different characteristics of sub-samples analysed. As a potential industry application, this research suggested the behavioural style quadrant as a diversification strategy. In specific, the risk and return analysis is organized in the multistyle sub-samples (i.e. firm, industry, and market states) to examine equity groups that are resilient on the influence of behavioural risks. Briefly, this paper offers valuable applications in investment practice on how to measure and manage behavioural risks.

1 citations

References
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Journal ArticleDOI
TL;DR: In this article, the generalized method of moments (GMM) estimator optimally exploits all the linear moment restrictions that follow from the assumption of no serial correlation in the errors, in an equation which contains individual effects, lagged dependent variables and no strictly exogenous variables.
Abstract: This paper presents specification tests that are applicable after estimating a dynamic model from panel data by the generalized method of moments (GMM), and studies the practical performance of these procedures using both generated and real data. Our GMM estimator optimally exploits all the linear moment restrictions that follow from the assumption of no serial correlation in the errors, in an equation which contains individual effects, lagged dependent variables and no strictly exogenous variables. We propose a test of serial correlation based on the GMM residuals and compare this with Sargan tests of over-identifying restrictions and Hausman specification tests.

26,580 citations

Journal ArticleDOI
TL;DR: In this article, the authors identify five common risk factors in the returns on stocks and bonds, including three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity.

24,874 citations


"A comparison of investors’ sentimen..." refers background in this paper

  • ...…the other hand, the fundamental prices P it are calculated based on data for earnings and book values on the date of the yearly nancial statement announcements.1 The variable of SIZE is calculated as the market share price Pit times the number of shares in circulation (see Fama and French (1993))....

    [...]

  • ...…model, this paper examines if deviations of share prices from their fundamental values can be explained by missing risk premium e¤ects (see, Fama and French (1993,2014)) and/or investors behavioral biases (e.g., excessive optimism or other psychological characteristics referred to as…...

    [...]

Journal ArticleDOI
TL;DR: In this article, a study of market efficiency investigates whether people tend to "overreact" to unexpected and dramatic news events and whether such behavior affects stock prices, based on CRSP monthly return data, is consistent with the overreaction hypothesis.
Abstract: Research in experimental psychology suggests that, in violation of Bayes' rule, most people tend to "overreact" to unexpected and dramatic news events. This study of market efficiency investigates whether such behavior affects stock prices. The empirical evidence, based on CRSP monthly return data, is consistent with the overreaction hypothesis. Substantial weak form market inefficiencies are discovered. The results also shed new light on the January returns earned by prior "winners" and "losers." Portfolios of losers experience exceptionally large January returns as late as five years after portfolio formation. As ECONOMISTS INTERESTED IN both market behavior and the psychology of individual decision making, we have been struck by the similarity of two sets of empirical findings. Both classes of behavior can be characterized as displaying overreaction. This study was undertaken to investigate the possibility that these phenomena are related by more than just appearance. We begin by describing briefly the individual and market behavior that piqued our interest. The term overreaction carries with it an implicit comparison to some degree of reaction that is considered to be appropriate. What is an appropriate reaction? One class,,of tasks which have a well-established norm are probability revision problems for which Bayes' rule prescribes the correct reaction to new information. It has now been well-established that Bayes' rule is not an apt characterization of how individuals actually respond to new data (Kahneman et al. [14]). In revising their beliefs, individuals tend to overweight recent information and underweight prior (or base rate) data. People seem to make predictions according to a simple matching rule: "The predicted value is selected so that the standing of the case in the distribution of outcomes matches its standing in the distribution of impressions" (Kahneman and Tversky [14, p. 416]). This rule-of-thumb, an instance of what Kahneman and Tversky call the representativeness heuristic, violates the basic statistical principal that the extremeness of predictions must be moderated by considerations of predictability. Grether [12] has replicated this finding under incentive compatible conditions. There is also considerable evidence that the actual expectations of professional security analysts and economic forecasters display the same overreaction bias (for a review, see De Bondt [7]). One of the earliest observations about overreaction in markets was made by J. M. Keynes:"... day-to-day fluctuations in the profits of existing investments,

7,032 citations

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TL;DR: In this article, the authors show that many of the CAPM average-return anomalies are related, and they are captured by the three-factor model in Fama and French (FF 1993).
Abstract: Previous work shows that average returns on common stocks are related to firm characteristics like size, earnings/price, cash flow/price, book-to-market equity, past sales growth, long-term past return, and short-term past return. Because these patterns in average returns apparently are not explained by the CAPM, they are called anomalies. We find that, except for the continuation of short-term returns, the anomalies largely disappear in a three-factor model. Our results are consistent with rational ICAPM or APT asset pricing, but we also consider irrational pricing and data problems as possible explanations. RESEARCHERS HAVE IDENTIFIED MANY patterns in average stock returns. For example, DeBondt and Thaler (1985) find a reversal in long-term returns; stocks with low long-term past returns tend to have higher future returns. In contrast, Jegadeesh and Titman (1993) find that short-term returns tend to continue; stocks with higher returns in the previous twelve months tend to have higher future returns. Others show that a firm's average stock return is related to its size (ME, stock price times number of shares), book-to-marketequity (BE/ME, the ratio of the book value of common equity to its market value), earnings/price (E/P), cash flow/price (C/P), and past sales growth. (Banz (1981), Basu (1983), Rosenberg, Reid, and Lanstein (1985), and Lakonishok, Shleifer and Vishny (1994).) Because these patterns in average stock returns are not explained by the capital asset pricing model (CAPM) of Sharpe (1964) and Lintner (1965), they are typically called anomalies. This paper argues that many of the CAPM average-return anomalies are related, and they are captured by the three-factor model in Fama and French (FF 1993). The model says that the expected return on a portfolio in excess of the risk-free rate [E(Ri) - Rf] is explained by the sensitivity of its return to three factors: (i) the excess return on a broad market portfolio (RM - Rf); (ii) the difference between the return on a portfolio of small stocks and the return on a portfolio of large stocks (SMB, small minus big); and (iii) the difference between the return on a portfolio of high-book-to-market stocks and the return on a portfolio of low-book-to-market stocks (HML, high minus low). Specifically, the expected excess return on portfolio i is,

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TL;DR: In this paper, the authors test whether innovations in macroeconomic variables are risks that are rewarded in the stock market, and they find that these sources of risk are significantly priced and neither the market portfolio nor aggregate consumption are priced separately.
Abstract: This paper tests whether innovations in macroeconomic variables are risks that are rewarded in the stock market. Financial theory suggests that the following macroeconomic variables should systematically affect stock market returns: the spread between long and short interest rates, expected and unexpected inflation, industrial production, and the spread between high- and low-grade bonds. We find that these sources of risk are significantly priced. Furthermore, neither the market portfolio nor aggregate consumption are priced separately. We also find that oil price risk is not separately rewarded in the stock market.

5,266 citations

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Q1. What are the contributions mentioned in the paper "University of birmingham a comparison of investors’' sentiments and risk premium effects on valuing shares" ?

This paper investigates at what extent deviations between market share prices and their fundamental values can be explained by risk premium and/or investors’sentiment e¤ects. To calculate the fundamental values of the shares, the paper relies on book value and yearly earnings forecasts of the listed companies, over period 1987-2012. The results of the paper indicate that share price deviations from their fundamental values can be explained by both risk premium and sentiment e¤ects. The authors would like to thank the editor Douglas Cumming and an anonymous referee for very constructive comments on the previous version of the paper.