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Dissecting Anomalies

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Abstract

The anomalous returns associated with net stock issues, accruals, and momentum are pervasive; they show up in all size groups (micro, small, and big) in cross-section regressions, and they are also strong in sorts, at least in the extremes. The asset growth and profitability anomalies are less robust. There is an asset growth anomaly in average returns on microcaps and small stocks, but it is absent for big stocks. Among profitable firms, higher profitability tends to be associated with abnormally high returns, but there is little evidence that unprofitable firms have unusually low returns. Copyright (c) 2008 The American Finance Association.

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... The empirical evidences of Stattman (1980), Chan, et.al (1991), Brav, et.al (2000), Daniel and Titman (2006) among others documented the book-to-market equity effects on stock returns; earnings-to-price effects by Basu (1977), earning effects by Jafee, et.al (1989), Fama and French (1995) and La Porta (1996) among others; Banz (1981), Vassalou and Xing (2004) and Fama and French (2008) depicted the size effects, similarly, cash flows effects by Berk, et.al (1999) and Vuolteenaho (2002) among others are the major studies that documented the firm specific accounting variables are the major sources of stock returns changes. Whereas in the later period, more focus was given towards the behavioral aspects like investors' characteristics and behavioral issues and market behavior, news effects, media effects, etc. ...
... Vassalou and Xing (2004) Both the size and book-to-market effects can be views as default effects which are in sum the case of size effect. Fama and French (2008) The anomalous returns associated with net stock issues, accruals, and momentum are pervasive; they show up in all size groups (micro, small, and big) in cross-section, and they are also strong in sorts, at least in the extremes. ...
... In a study of dissecting anomalies, Fama and French (2008) considered the patterns of average stock returns which do not explained by CAPM. Two approaches were used to identify anomalies: sorts of returns on anomaly variables, and regressions, in the spirit of Fama and MacBeth (1973) to explain the cross-section of average returns. ...
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The financial markets have been suffering from unforeseen and sudden economic turbulences that have been directly or indirectly influences the assets values. To analyze such these market influences, the separate discipline, investment management was formed in Finance and developed chronologically up to current professional and scientific phase. It is the fact that the market has been stimulated by the financial indicators which is in number as well as by the behavioral characteristics of the investment communities. Moreover, while considering the financial market as the mirror of economy it is equally important to note that the market moves on the sentiments and the trading behavior of the market participants. In the meantime, the trading behaviors depend upon the market information such as financial and non-financial - media, politics, hypes, etc. The study analyzes the market information and stock returns in Nepalese context in 2012. The study primarily focus on the usefulness of the historical database, the financial news coverage and its effects on stock returns, the political leadership effects on stock returns, and the study also determine the factors of investment decision.
... We therefore replicate the standard two-step procedure by using the five-factor Fama-French model that includes the profitability and investment factors. As in Pastor and Stambaugh (2003), we also measure characteristics at the firm-level (instead of the portfolio level), and compute decile returns by value weighting, which prevents microcaps from potentially dominating the returns (Hou et al. 2015(Hou et al. , 2020Fama and French 2008b). This approach is simple without great risk of generating false positives. ...
... We then create value-weighted portfolios based on these deciles and compute excess returns over the risk-free rate for the portfolios over the following 12 months, after which we repeat this procedure for each calendar year and rebalance the portfolios. Our use of value-weighted portfolios should alleviate any concern about microcaps dominating our results (Hou et al. 2020;Fama and French 2008b). 19 The average market capitalization in decile one is about $3.5 billion, whereas it is about $9.7 billion in decile four and $6.2 billion in decile ten. ...
... Note that our use of returns implies that our measure captures innovations in the aggregate weather factor, as required for pricing tests. Our use of value-weighted portfolios should alleviate any concern about microcaps dominating our results (Hou et al. 2020;Fama and French 2008b). Nonetheless, we recompute our factor after removing firms below the 20th percentile of the market value of available public firms for each year of our portfolio analysis. ...
Article
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The FASB and IFRS Foundation’s International Sustainability Standards Board have called for measuring individual firms’ exposure to weather, a fundamentally amorphous concept, as a first step toward quantifying the impact of environmental factors on financial reporting. This study builds a large-scale measure of individual firm exposure to weather using linguistic analysis of annual reports. Preliminary analyses suggest that weather is a determinant of our measure: e.g., the measure increases significantly after the firm gets hit by a severe storm. Despite being constructed from largely backward-looking mandated reports, our measure is forward looking in that it can predict variation in returns around future extreme weather events. Exposure to our measure is also priced as a risk factor, further establishing its forward-looking nature systematically in the cross-section. Our measure appears to reasonably capture a firm’s business exposure to weather, thus showcasing the power of accounting to measure the economic impact of environmental, social, and governance (ESG) factors.
... The accrual anomaly refers to the well-known negative relation between annual accruals and realized returns. First documented in Sloan (1996), the accrual anomaly is one of the most pervasive, robust return anomalies (Fama & French, 2008). We hypothesize a negative relation between stock liquidity and the magnitude of the accrual anomaly. ...
... In the main test, we adopt the broad definition of accruals proposed in Richardson, Sloan, Soliman, and Tuna (2005) to measure annual accruals, the high-low estimate of the effective bid-ask spread from Corwin and Schultz (2012) to compute stock liquidity, and the characteristic-based portfolio matching procedure proposed in Daniel, Grinblatt, Titman, and Wermers (1997) to compute abnormal returns. Following Fama and French (2008), we adopt three approaches (the regression approach, the sorts approach and the Jensen alpha approach) to test the hypothesis. We use non-financial firms from years 1970-2011. ...
... The accrual anomaly refers to the predictable negative relation between the accrual component of reported earnings and realized returns. The accrual anomaly is first documented in Sloan (1996), and it is considered one of the most pervasive return anomalies (Fama & French, 2008). Considerable empirical evidence suggests that mispricing, at least to a great extent, drives the accrual anomaly (Richardson et al., 2010;Dechow et al., 2011; Stock liquidity and accrual anomaly Hirshleifer et al., 2012). ...
Article
Purpose This study examines the effect of stock liquidity on the magnitude of the accrual anomaly. Design/methodology/approach This paper examines the relation—both time-series and cross-sectional—between stock liquidity and the magnitude of the accrual anomaly and use the 2001 minimum tick size decimalization as a quasi-experiment to establish causality. Findings There is both cross-sectional and time-series evidence that stock liquidity is negatively related to the magnitude of the accrual anomaly. Moreover, the extent to which investors overestimate the persistence of accruals decreases with stock liquidity. Results from a difference-in-differences analysis conducted using the 2001 minimum tick size decimalization as a quasi-experiment suggest that the effect of stock liquidity on the accrual anomaly is causal. The findings of this study are consistent with the enhancing effect of stock liquidity on pricing efficiency. Originality/value The study's findings are well aligned with the mispricing-based explanation for the accrual anomaly, suggesting that the improvement in market-wide stock liquidity drives the contemporaneous decline in the magnitude of the accrual anomaly, at least to a great extent.
... (x) Value (RatioBM): the book to market ratio of Fama and French (2008). ...
... (xi) Profitability (Profit): the profitability calculated as the ratio of equity income to book equity as in Fama and French (2008). Equity income is defined as income before extraordinary expenses, minus dividends on preferred stock, plus income statement deferred taxes. ...
... If a higher credit score forecasts improved firm fundamentals, it can lead to predictably lower future credit spreads according to the delayed rational response hypothesis, as long as this change in fundamentals takes place over a long time period. We now rerun the specification in (8) but where the dependent variable is the change in one of the following fundamental measures: profitability as defined in Fama and French (2008), the book-leverage ratio (LEV), and the logarithm of firm's total assets. We calculate the changes in these variables over the next eight quarters to allow for the rational delayed response to play out, starting with the first post-call quarterly observation of each dependent variable and ending with the eighth. ...
Preprint
We develop a novel technique to extract credit-relevant information from the text of quarterly earnings calls. This information is not spanned by fundamental or market variables and forecasts future credit spread changes. One reason for such forecastability is that our text-based measure predicts future credit spread risk and firm profitability. More firm- and call-level complexity increase the forecasting power of our measure for spread changes. Out-of-sample portfolio tests show the information in our measure is valuable for investors. Both results suggest that investors do not fully internalize the credit-relevant information contained in earnings calls.
... The OLS benchmark represents the typical approach in one of two basic strands of the empirical literature on stock return prediction. Specifically, cross-sectional stock return predictability research (e.g., Fama and French 2008;Lewellen 2015;Gu et al. 2020) runs cross-sectional regressions of future stock returns on a handful of lagged stock characteristics. The second strand of literature, i.e., time-series stock return predictability research, does not forecast the cross-section but the time-series of returns. ...
... Studies in this vein attempt to shed light on the variables that affect the equity risk premium." • Gu et al. (2020): "The first strand models differences in expected returns across stocks as a function of stock-level characteristics, and is exemplified by Fama and French (2008) and Lewellen (2015). The typical approach in this literature runs cross-sectional regressions of future stock returns on a few lagged stock charac-Content courtesy of Springer Nature, terms of use apply. ...
... 7 In this paper, we are interested in predicting the cross-sectional dispersion in stock returns. However, in terms of cross-sectional predictability, Gu et al. (2020) is the first paper to comprehensively use ML methods and compare them against the standard OLS benchmark in this line of research (e.g., Fama and French 2008;Lewellen 2015;Gu et al. 2020). Against this background, we also rely on OLS as our "natural" benchmark. ...
Article
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We compare the performance of the linear regression model, which is the current standard in science and practice for cross-sectional stock return forecasting, with that of machine learning methods, i.e., penalized linear models, support vector regression, random forests, gradient boosted trees and neural networks. Our analysis is based on monthly data on nearly 12,000 individual stocks from 16 European economies over almost 30 years from 1990 to 2019. We find that the prediction of stock returns can be decisively improved through machine learning methods. The outperformance of individual (combined) machine learning models over the benchmark model is approximately 0.6% (0.7%) per month for the full cross-section of stocks. Furthermore, we find no model breakdowns, which suggests that investors do not incur additional risk from using machine learning methods compared to the traditional benchmark approach. Additionally, the superior performance of machine learning models is not due to substantially higher portfolio turnover. Further analyses suggest that machine learning models generate their added value particularly in bear markets when the average investor tends to lose money. Our results indicate that future research and practice should make more intensive use of machine learning techniques with respect to stock return prediction.
... However, several inquiries also specify that these models do not deliver accurate outcomes for average return and entirely ignore the cross-sectional returns. Therefore, this abnormal pattern of average stock return where each asset class or security perform differently and which is not explained by traditional financial theories and outmoded capital asset pricing models is termed as Anomaly (Jebran & Khan, 2014;Fama and French, 2008). Later, one of the specific anomalies is identified in the capital markets which is termed as investment growth anomaly (Qi Su, 2016;. ...
... Evidently, several academic investigations have also analyzed various factors that are tested in view of Q-Theory and reported the negative relation between the investment growth and the expected average return. For instance, investment-to-assets was used by Lyandres, Sun and Zhang (2008), Investment growth is analyzed by Xing (2008), Asset growth is used as a factor by Cooper, Gulen and Schill (2008), Net stock issue is used by Fama and French (2008), Net operating assets by Hirshleifer et al. (2004) and Abnormal corporate investment is explored by Titman, Wei and Xei (2004). Likewise, these studies have not provided any evidences that Q-Theory delivers any clear explanation for existing anomalies in capital market. ...
Article
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This study is an attempt to discover the presence of investment growth anomaly in Pakistan Stock Exchange (PSX) by using data of all firms during the period of 2000 to 2019. The mined data is ordered in decile portfolios which are arranged in ascending order, from the lowest portfolio to the highest one. Assessment of the portfolio returns is executed on monthly basis and returns of both sorts of portfolios i.e. equally and value weighted are measured. Subsequently, built portfolios are evaluated by using Capital Asset Pricing Model, Fama and French three and five factor CAPM models by engaging Generalized Method of Moments. The result postulates that investment growth anomaly does exist in PSX and the firms which are involved in lower investment deliver better return. These results may assist the investors by measuring the verdicts gained from evaluated portfolios to generate abnormal return in PSX.
... Sorting into portfolios can be considered as a nonparametric alternative to imposing linearity on the relationship between returns and stock characteristics, (see, e.g. Fama and French 2008, Cochrane 2011). Freyberger et al. (2020 formalize this idea and show the equivalence between portfolio sorting based on stock characteristics and a linear regression model in which the regressors are indicator functions of the stock characteristics. ...
... To do this, we need to select a size of our fund or assets under management (AUM). We use a notional value of $500 ‡ Consistent with the figures of 60% in Fama and French (2008) and 60.7% in Hou et al. (2020) (we note that the percentage is trending downward in the latter part of our sample). Note: FF SMB is the Fama and French size factor; MV NP is an optimal characteristic portfolio defined using the non-parametric estimator (8); OLS is the OLS-implied weight factor: ...
Article
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Characteristic-sorted portfolios are the workhorses of modern empirical finance, deployed widely to evaluate anomalies and construct asset pricing models. We propose a new method for their estimation that is simple to compute, makes no ex-ante assumption on the nature of the relationship between the characteristic and returns, and does not require ad hoc selections of percentile breakpoints or portfolio weighting schemes. Characteristic portfolio weights are implied directly from data, through maximizing a Mean–Variance objective function with mean and variance estimated non-parametrically from the cross-section of assets. To illustrate the method, we evaluate the size, value and momentum anomalies and find overwhelming empirical evidence of the outperformance of our methodology compared to standard methods for constructing characteristic-sorted portfolios. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
... In other words, anomalies strongly depend on the choice of the asset pricing model. Fama and French (2008) provide evidence against some of the conclusions found by the literature about the ability of several firms' characteristics in explaining stock returns. In particular, they show that the sample of firms analyzed matters, and that several anomalies arise because of a specific type of companies, namely the micro-cap firms. ...
... Hou, Xue, and Zhang (2020), instead, show that, after controlling for the impact of micro-caps stocks (as suggested by Fama and French, 2008), 64% of all the firms' variables analyzed are not significant at the conventional 5% level. Moreover, by raising the t-stat cutoff to 3, the number of non-significant variables further increases to 85%. ...
Article
In this paper we provide a literature review of the main factors-based asset pricing models, focusing in particular on factors related to firm characteristics. After presenting the Capital Asset Pricing Model, we describe first the most important empirical evidence that led to the well-known Fama-French three-factors model. Next, we highlight the most widely used multi-factors pricing models based on momentum, liquidity, investment and profitability, also outside the U.S. Finally, we discuss the ability of firm characteristics to predict the behavior of future stock returns.
... Our results are in contrast with the evidence provided by of Fama and French (2008), as the portfolios imply that there is a robust low F-Score to high F-Score return difference among small and large European companies. Our findings are consistent with those of Cooper et al. (2008), who accordingly provided sufficient evidence to prove that all market segments have significant F-Score effects. ...
... Moreover, we estimate that new equity financing activities have generated huge and very significant size adjustment jedgine returns across all size segments. (Fama French, 2008). ...
Article
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Research Question: Can the F-Score predict the stock market returns in the cross section of international stock markets? Motivation: The majority of the literature, in the area of the F-Score metric, has examined whether it can be used to predict future financial profitability, the relationship of F-Score with book-to-value metrics and the momentum premium and whether it can be used as a successful investment strategy tool. There only three studies that examine the relationship between the F-Score and future stock returns, without the use of complementary variables, and in other countries except Europe. This paper seeks to fill this gap. Data: The dataset of the present research consists of listed European companies from 21 countries (in random order: Finland, United Kingdom, Switzerland, Turkey, Hungary, Portugal, Spain, Poland, Norway, Luxembourg, Italy, Netherlands, Ireland, Greece, Belgium, Germany, Denmark, France Czech Republic, Sweden, Austria), from 1989 to 2016. We collect firm-level accounting information as provided by Worldscope, as well as the monthly total returns for common stocks from Datastream. Tools: With the use of a dataset consisting of European companies from 21 countries, portfolio analysis and time series regressions are performed using abnormal monthly returns (monthly returns minus risk-free interest rates). Findings: We find that the F-Score is a statistically significant predictor as well as an economically meaningful index. Its performance forecasting ability is visible in developed Europe, both in small and large companies, and remains stable after controlling for established cross-sectional determinants (such as book market, investment, and company size). Contribution: This study seeks to fill the gap in the stock return and F-Score relationship in a European setting controlling for the other financial variables. Our empirical models are tested across a number of different economic and stock market backgrounds and the implications of our results are of particular interest for academics, for investors (retail and institutional) and for policy makers.
... 2 From an empirical point of view, it can be checked with data and P . 3 With P (V ; ") de…ned by (3), a realized return is ...
... Fama and French (2008) document that the size anomaly is concentrated in "microcaps" (…rms with very small V ). Note that (8) applied to abnormal returns predicts that if positive abnormal returns exist for very small V , they should quickly disappear as V increases. ...
Preprint
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Firms are heterogenous in their pre-investment values, so are the investment costs and the realized returns. What is the relationship between pre-investment firm values, the investment costs they pay, and the realized returns? We derive a formula that decomposes the marginal impact of pre-investment values on returns into an economic effect and a mechanical effect, taking into account the endogeneity of investment. It reveals that regressing realized returns on pre-investment values leads to a biased estimate of the economic effect, with the bias direction and magnitude depending on relative investment size and realized returns. Correcting bias is straightforward for data with only positive returns. For data in which returns take both sings, such as takeovers, stronger assumptions are necessary to make a meaningful inference. We conclude with suggestions for circumventing this issue. (JEL G11, G14, G34)
... P/E là một trong các căn cứ của nhà đầu tư về tốc độ tăng trưởng trung bình của công ty và tình hình chi trả cổ tức. Theo Fama và French [14], các cổ phiếu có rủi ro cao sẽ có lợi nhuận kỳ vọng cao, và các cổ phiếu này sẽ có giá thấp so với thu nhập của các cổ phiếu đó. Tương tự, GauTam [15] tìm thấy tác động tiêu cực giữa tỷ lệ giá trên thu nhập và lợi nhuận cổ phiếu. ...
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The article studies the impact of bank liquidity and bank stock liquidity on the stock price volatility of 17 The article studies the impact of bank liquidity and bank stock liquidity on the stock price volatility of 17 commercial banks listed on the Vietnamese Stock Exchange. The study uses the Random Effect Model with unbalanced table data and quarterly frequency from the first quarter of 2006 to the fourth quarter of 2020. The results show that the financial gap (FGAP) has a positive impact on the stock price volatility of banks, meaning the higher the financial gaps, the lower the bank liquidity, and the larger the stock price volatility of banks. In addition, the study also shows that the size of total assets and the change of exchange rate for the two factors have opposite effects on changes in the share prices of banks. The study has not yet found any evidence to conclude that stock liquidity has an impact on the stock price volatility of the commercial banks listed on the Vietnamese Stock Exchange.
... Then, define p jt (β) = 1{β ∈ P jt }, 7 Cattaneo, Crump, Farrell, and Schaumburg (2020) provide a detailed discussion of how sorted portfolios represent a nonparametric estimate of a conditional expectation. See also, Fama and French (2008), Cochrane (2011), andFreyberger, Neuhierl, andWeber (2020). ...
Preprint
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Beta-sorted portfolios -- portfolios comprised of assets with similar covariation to selected risk factors -- are a popular tool in empirical finance to analyze models of (conditional) expected returns. Despite their widespread use, little is known of their statistical properties in contrast to comparable procedures such as two-pass regressions. We formally investigate the properties of beta-sorted portfolio returns by casting the procedure as a two-step nonparametric estimator with a nonparametric first step and a beta-adaptive portfolios construction. Our framework rationalize the well-known estimation algorithm with precise economic and statistical assumptions on the general data generating process and characterize its key features. We study beta-sorted portfolios for both a single cross-section as well as for aggregation over time (e.g., the grand mean), offering conditions that ensure consistency and asymptotic normality along with new uniform inference procedures allowing for uncertainty quantification and testing of various relevant hypotheses in financial applications. We also highlight some limitations of current empirical practices and discuss what inferences can and cannot be drawn from returns to beta-sorted portfolios for either a single cross-section or across the whole sample. Finally, we illustrate the functionality of our new procedures in an empirical application.
... is methodology was proposed by financial experts Fama, Fisher, Jensen, and Roll (FFJR) (1969), while it has been widely used in other areas, such as accounting [22,23], management [24,25], and economics [26,27]. Concerning the literature about the impact factors of abnormal stock returns in the context of ESM, Fama and French [28] empirically explore the items that can affect the abnormal returns of stocks, which are the factors grouped according to the ratio of market capital and book market value of stocks. Renmin [29] proposed the capital asset pricing model to obtain abnormal returns on M&A and studied the market value of listed companies, net asset and operating cash flow of listed companies, and the impact of net profits on abnormal returns. ...
Article
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The sudden global pandemic of COVID-19 occurred in Malaysia at the beginning of new 2020, which increased the uncertainty of the economy. As a highly demanded industry during diseases, COVID-19-related news had a mixed influence on investors’ confidence in the healthcare industry, so the short-term market reaction of the Malaysian healthcare industry is investigated during this unfolding event. This paper examines whether the “lockdown” suppressed the influence of COVID-19 pandemic on stock performance in 12 listed healthcare companies in Malaysia. We consider the “lockdown” order has different impacts on samples. The hardest hit among the four events is the first announcement of lockdown, whose cumulative average abnormal return (CAAR) is negative (CAAR<0), for its strict movement control. However, the impacts of the following three lockdown events are positive and less severe as the market gradually digest these kinds of news and the deregulation of movement control. Previous studies have justified the influence of disease outbreaks on the stock market; however, this study compensates for other studies by employing the event study methodology (ESM) approach to provide the first empirical evidence of the unprecedented influence of “lockdown” on Malaysian healthcare stock market. This study has practical implications for Malaysian financial markets that the lockdown orders matter for the Malaysian healthcare industry. The empirical results show that the stock market has positively affected the lockdown announcement after the first event. In turn, the policymakers could draw on these results related to stock performance to modify the regulations in the healthcare industry.
... This section presents evidence that the conclusions based on portfolio sorts are robust to several variations to the way we construct the portfolios. First, as suggested in Fama and French (2008), we construct value-weighted instead of equally-weighted portfolios to check that our conclusions are not sensitive to volatile returns that characterize small firms. As shown in A.1, consistent with our evidence based on equally-weighted portfolios, the return on a portfolio comprised of A-rated firms does not perform any better that of a portfolio with firms that have a score C & below. ...
Article
It is difficult to assess the effectiveness of investment strategies that screen companies based on environmental criteria to hedge climate change risk because physical risks have not yet fully materialized and policies to combat climate change are usually widely anticipated. This paper sidesteps these limitations by analyzing the stock market response to plausibly exogenous changes in expectations about the level of a carbon tax in Germany. The risk-adjusted return on two sustainable investment approaches---screening companies based on environmental scores and on firms' carbon footprint---around the carbon tax news reveals that firms with a high environmental score did not perform any better than those with a low environmental score. In contrast, the stock price of firms with low carbon emissions increased in value relative to those with a high carbon footprint. Carbon intensity explains the cross-sectional reaction to the carbon tax news because it predicts revisions in expected profitability.
... Moreover, the three-factor model cannot explain the relationship between a corporation's investment style and cross-sectional returns. That is, the higher the investment expenditures, the lower the future stock returns (Titman et al., 2004;Fama and French, 2008;Aharoni et al., 2013). Moreover, the literature implies that the three-factor model fails to capture the negative relationship between corporate operating profits and stock prices (Cohen and Gompers, 2002;Novy-Marx, 2013). ...
Article
This paper proposes a long short-term memory (LSTM) neural network model to predict daily stock price movements based on asset pricing factors (i.e., the five factors proposed by Fama and French, and the short-term momentum factor). Based on three independent experiments, we systematically evaluate the explanatory power and the predictive power of the LSTM model by employing 3316 A-share listed companies in the Shanghai and Shenzhen stock exchanges from the in-sample period January 1, 2008 to December 31, 2019. Furthermore, we propose a four-step approach to dynamically update the underlying stocks in different portfolios based on the empirical findings. All portfolios are simulated using out-of-sample data (i.e., from January 1, 2020, to May 31, 2021) to avoid look-ahead bias. The trading results suggest that our dynamic investment strategies are superior to the benchmark index and are able to generate significant returns with relatively low risks.
... Thus, they may lower the robustness of the overall model when they interact with the other three factors. According to Fama and French (2008), the asset growth (CMA) and profitability (RMW) anomalies are less robust. There is an asset growth anomaly in average returns on microcaps and small stocks, but it is absent for big stocks. ...
Article
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This research investigates the impact of the three earnings management methods according to Dechow and Skinner (2000) and Gunny (2005), i.e., accrual earnings management (AEM), real earnings management (REM), and fraudulent accounting (FRA), on idiosyncratic risk. This research also examines the moderating effect of corporate social responsibility (CSR) disclosure on these associations. This research employs balance panel data consisting of 492 observations from 2016 to 2019. This research obtains 123 companies listed under the manufacturing industry of the Indonesia Stock Exchange (IDX) through purposive sampling. To test the hypotheses, this research uses multiple linear regression models. This research finds that all three earnings management methods are positively associated with idiosyncratic risk. Furthermore, CSR disclosure is proven to weaken the effect of accrual earnings management and fraudulent accounting on idiosyncratic risk, but this does not apply to real earnings management. These results are robust after a sensitivity test. This research fills the existing gap within idiosyncratic risk study. Among similar studies, this research is the first to investigate the effect of fraudulent accounting on idiosyncratic risk and the moderating effect of CSR disclosure. This research also raises awareness of the cost of idiosyncratic risk, especially in emerging markets with relatively smaller stock markets, which makes diversification more challenging. It provides insights to market regulators on how investors can benefit from more disclosures
... Regarding the predictability and efficiency of financial markets, a contradictory body of information exists [13,14]. Regression analysis of probable signals with the aim of explaining asset returns is a well-established method of analyzing return-predictive signals and it has been used for many years [15,16]. Various characteristics may be included in linear regressions, but they are not flexible in their incorporation and they impose strict assumptions on the functional form of how signals suggest market movements. ...
Article
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Digital currencies such as Ethereum and XRP allow for all transactions to be carried out online. To emphasize the decentralized nature of fiat currency, we can refer, for example, to the fact that all virtual currency users may access services without third-party involvement. Cryptocurrency price swings are non-stationary and highly erratic, similarly to the price changes of conventional stocks. Owing to the appeal of cryptocurrencies, both investors and researchers have paid more attention to cryptocurrency price forecasts. With the rise of deep learning, cryptocurrency forecasting has gained great importance. In this study, we present a long short-term memory (LSTM) algorithm that can be used to forecast the values of four types of cryptocurrencies: AMP, Ethereum, Electro-Optical System, and XRP. Mean square error (MSE), root mean square error (RMSE), and normalize root mean square error (NRMSE) analyses were used to evaluate the LSTM model. The findings obtained from these models showed that the LSTM algorithm had superior performance in predicting all forms of cryptocurrencies. Thus, it can be regarded as the most effective algorithm. The LSTM model provided promising and accurate forecasts for all cryptocurrencies. The model was applied to forecast the future closing prices of cryptocurrencies over a period of 180 days. The Pearson correlation metric was applied to assess the correlation between the prediction and target values in the training and testing processes. The LSTM algorithm achieved the highest correlation values in training (R = 96.73%) and in testing (96.09%) in predicting XRP currency prices. Cryptocurrency prices could be accurately predicted using the established LSTM model, which displayed highly efficient performance. The relevance of applying these models is that they may have huge repercussions for the economy by assisting investors and traders in identifying trends in the sales and purchases of different types of cryptocurrencies. The results of the LSTM model were compared with those of existing systems. The results of this study demonstrate that the proposed model showed superior accuracy based on the low prediction errors of the proposed system.
Chapter
Individual investors must be compensated for bearing risk. It seems intuitive to the reader that there should be a direct linkage between the risk of a security and its rate of return. We are interested in securing the maximum return for a given level of risk, or the minimum risk for a given level of return. The concept of such risk-return analysis is the efficient frontier of Harry Markowitz (1952, 1959). If an investor can invest in a government security, which is backed by the taxing power of the federal government, then that government security is relatively risk-free. The 90-day Treasury bill rate is used as the basic risk-free rate. Supposedly, the taxing power of the federal government eliminates default risk of government debt issues. A liquidity premium is paid for longer-term maturities, due to the increasing level of interest rate risk. Investors are paid interest payments, as determined by the bond’s coupon rate, and may earn market price appreciation on longer bonds if market rates fall or losses if market rates rise. During the period from 1928 to 2017, Treasury bills returned 3.44%, longer-term (10-year Treasury) government bonds earned 5.15%, and corporate stocks, as measured by the stock of the S&P 500 index, earned 11.53% annually, as measured by the mean annual return. The annualized standard deviations are 3.06%, 7.72%, and 19.66%, respectively, for Treasury bills, Treasury bonds, and S&P stocks. The risk-return trade-off has been relevant for the 1928–2017 period. The correlation coefficient between annual returns for Treasury bills and the S&P 500 stock returns were −0.030 for the 1928–2017 time period. This was essentially no correlation between Treasury bills and large stocks, as measured by the S&P 500 stock. The correlation coefficient between annual returns for Treasury bonds and the S&P 500 stock returns was 0.30 for the 1928–2017 time period. Why do corporate stocks offer investors higher returns for stocks than bonds?
Chapter
The previous chapter introduced the reader to Markowitz mean-variance analysis and the Capital Asset Pricing Model. The cost of capital calculated in Chap. 10 assumes that the cost of equity is derived from the Capital Asset Pricing Model and its corresponding beta or measure of systematic risk. The Gordon Model, used for equity valuation in Chap. 8, assumes that the stock price will fluctuate randomly about its fair market value. The cost of equity is dependent upon the security beta. In this chapter, we address the issues inherent in a multi-beta or multiple factor risk model. The purpose of this chapter is to introduce the reader to multifactor risk models. There are academic multifactor risk models, such as those of Cohen and Pogue (1967), Farrell (1974), Stone (1974), Ross (1976), Roll and Ross (1980), Dhrymes et al. (1984, 1985), and Fama and French (1992, 1995, 2008). There are practitioner multifactor risk models, such as Barra, created during the 1973–1979 time period, Advanced Portfolio Technologies (APT), created in 1987, and Axioma, created in the late 1990s, which gained practitioner acceptance in the 2000–2019 time period. The former academicians who created these practitioner models are Barr Rosenberg, Andrew Rudd, John Blin, Steve Bender, and Sebastian Ceria. We will introduce the reader to the practitioner models and their academician creators in this chapter. Which models are best? We, at McKinley Capital Management, MCM, have tested these models. None of the models are perfect, but the models are generally statistically significant when the statistically significant tilt variables of Chap. 14 are used for portfolio construction. In this chapter, we discuss the MCM Horse Races of the 2010–2019 time period to test stock selection within the commercially available multifactor risk models. We trace the development of the Barra, APT, and Axioma commercially available risk models. We conclude with an update of US and non-US portfolios for the 1996–2020 time period. Long-term portfolio strategies have worked for the past 24 years, not just out-of-sample, but post publication of Bloch et al. (1993) with the Axioma Statistical Risk Model.
Article
This study examines the betting against beta (BAB) anomaly and its drivers for five major Asian markets, using data from January 1999 to January 2020. We find positive raw returns-based BAB premiums for India, China, and South Korea, while they are negative in Japan and Indonesia. Cross-sectional differences in BAB premiums seem to be positively associated with the level of information uncertainty and financial market development. Decomposition of the BAB phenomenon shows that BAB premiums are driven by betting against correlation (BAC) premiums in India while betting against volatility (BAV) premiums drive it in China and S.Korea. Funding liquidity risk and margin constraints drive positive BAC in India and Indonesia. Positive BAV in China is driven by MAX (lottery behavior), while idiosyncratic volatility (IVOL) and MAX together drive them in S.Korea. Negative BAB in Japan and Indonesia is mainly due to negative BAV premiums caused by MAX in Japan and both IVOL and MAX in Indonesia. CAPM-based risk-adjusted BAB premiums are not significant for S.Korea, Japan, and Indonesia, while in India and China, they are significant but get explained by the profitability factor. We conclude that the BAB strategy is not universally applicable, and its drivers vary across sample markets.
Article
We document that the changes in profitability predict the firm's stock returns and future profitability. We construct three horizon-based profitability changes, including short-term, medium-term, and long-term changes. We find that the predictive information of the short-term change in profitability is not subsumed by the profitability level in the Chinese stock market. We also find that the short-term profitability change generates an asymmetrical premium in different market states. Furthermore, we find that the beta anomaly is embedded in the premium generated by the short-term change in profitability. In addition, we explore the underlying mechanisms of profitability premium and propose a heterogeneous investor belief channel to explain the profitability premium. We find that risk-based q-theory also helps to explain profitability premium. Therefore, the source of profitability premium is mixed and could not be explained entirely by either theory.
Chapter
So long as a company is closely held, the control group and the stockholders are identical, and seldom is there a conflict of interest between them. However, once a company goes public, it acquires a group of shareholders who depend on the management for the safety and profitability of their investment. In short, an agency principal relation is established where the management is the agent and the shareholder is the principal. This relation implies a commitment by management that the outside shareholders will be treated fairly in such matters as cash payouts, expansion policies, accounting probity, and the level of executive compensation, and that in general, the company affairs will be directed vigorously and conscientiously.
Article
Purpose This paper investigates the role of economic disagreement in the cross-sectional pricing of individual stocks. Economic disagreement is quantified with ex ante measures of cross-sectional dispersion in economic forecasts from the Survey of Professional Forecasters (SPF), determining the degree of disagreement among professional forecasters over changes in economic fundamentals. Design/methodology/approach The authors introduce a broad index of economic disagreement based on the innovations in the cross-sectional dispersion of economic forecasts for output, inflation and unemployment so that the index is a shock measure that captures different aspects of disagreement over economic fundamentals and also reflects unexpected news or surprise about the state of the aggregate economy. After building the broad index of economic disagreement, the authors test out-of-sample performance of the index in predicting the cross-sectional variation in future stock returns. Findings Univariate portfolio analyses indicate that decile portfolios that are long in stocks with the lowest disagreement beta and short in stocks with the highest disagreement beta yield a risk-adjusted annual return of 7.2%. The results remain robust after controlling for well-known pricing effects. The results are consistent with a preference-based explanation that ambiguity-averse investors demand extra compensation to hold stocks with high disagreement risk and the investors are willing to pay high prices for stocks with large hedging benefits. The results also support the mispricing hypothesis that the high disagreement beta provides an indirect way to measure dispersed opinion and overpricing. Originality/value Most literature measures disagreement about individual stocks with the standard deviation of earnings forecasts made by financial analysts and examines the cross-sectional relation between this measure and individual stock returns. Unlike prior studies, the authors focus on disagreement about the economy instead of disagreement about earnings growth. The authors' argument is that disagreement about the economy is a major factor that would explain disagreement about stock fundamentals. The authors find that disagreement in economic forecasts does indeed have a significant impact on the cross-sectional pricing of individual stocks.
Article
Asset pricing predictions from the investment CAPM depend on the cross-sectional relation between investment and profitability. In samples of U.S. stocks featuring high cross-sectional investment-profitability correlation, both investment and profitability premiums are weak. Consistent with the conditional predictions from the investment CAPM, triple sorts on size, investment, and profitability as in Hou et al. (2015)’s q-factors resurrect the premiums in the high-correlation samples. We find similar results using cash-based profitability, consistent with the dynamic investment CAPM. Our work has important implications for constructing asset pricing factors and interpreting out-of-sample asset pricing test results, in particular the insignificance of historical investment and profitability premiums.
Chapter
The purpose of this study is to document the existence and effectiveness of variables reported as financial anomalies in portfolio selection during 1976 through 2020.
Chapter
This chapter highlights the existing research works carried out in India and abroad by the scholars exploring the microeconomic, macroeconomic and industry-specific factors affecting the firm-level performance. Comprehensive review of the existing literature on the effect of these factors on the efficiency, profitability and stock prices was accomplished. The research gap in the existing literature was identified in this chapter by using Evidence Gap Map. The chapter also outlines the objectives of the study in the perspective of such research gap.KeywordsManufacturingMicroeconomic factorsMacroeconomic factorsIndustry-specific factorsEfficiencyProfitabilityStock priceEvidence gap map
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Earlier studies have linked equity market liberalization to growth in emerging markets. Some conclude liberalization causes growth, whereas others contend contemporaneous economic policies and conditions play important roles. The causal argument contends that foreigner investability in public firms leads to lower discount rates and greater share issuance, investment, and efficiency. Using three separate measures of foreign investability, we do not find these effects. Moreover, common de jure foreigner-investability measures are poor de facto measures. Economic indicators, not directly influenced by equity market liberalization, also grow faster in countries with more investable firms. Our findings suggest foreigner investability cannot fully explain the equity-market-liberalization-growth relation. (JEL F30, F38, G30, G24, G15) Received: February 17, 2019; Editorial decision: March 29, 2022 by Editor: Andrew Ellul. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
Thesis
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في العقود الأخيرة، شهد الاقتصاد تغيرات عالية السرعة وتقنيات جديدة جد متطورة، الأمر الذي استوجب على المحاسبة مواكبة هذه التغيرات، إذ أصبح الفكر المحاسبي يهتم بتسجيل الظواهر التي تتطلب التقييمات، التفسيرات، التقديرات والتوقعات، ويعتبر اتخاذ القرارات بناء على المعلومات المالية أحد التحديات الرئيسة التي تواجه الأفراد والمؤسسات والمنظمات والدول ذات العلاقة، وتفاقم الأمر حيث مر الاقتصاد العالمي بأزمة ثقة نتيجة الدور المتزايد لأساليب إدارة العديد من المؤسسات لبياناتها، باستعمال المستحقات المحاسبية بالدرجة الأولى. من هذا المنطلق، هدفت هذه الدراسة إلى إبراز دور هذه المستحقات في تفسير التدفقات النقدية والتنبؤ بها في المؤسسات الاقتصادية الجزائرية، اعتمادا على البيانات المالية للمؤسسات محل الدراسة والتي شملت 132 مؤسسة للفترة الممتدة من 2010-2020م، واستنادا على نموذج انحدار خطي مطبق على بيانات سلسلة زمنية مقطعية غير متوازنة بالاعتماد على برنامجي"10 EViews" و"SPSS 25" لإجراء الاختبارات الإحصائية. حسب نتائج الدراسة، فإن المستحقات المحاسبية تمثل مؤشر أفضل من التدفقات النقدية الجارية والأرباح المحاسبية في تفسير التدفقات النقدية والتنبؤ بها، وأن تقسيم المستحقات المحاسبية يساهم في زيادة القدرة على ذلك، إذ تعتبر المستحقات المحاسبية قصيرة الأجل أفضل من المستحقات المحاسبية طويلة الأجل، والمستحقات المحاسبية غير الاختيارية أكثر قدرة على تفسير التدفقات النقدية المستقبلية من المستحقات الاختيارية، كما أن لكل نوع من المستحقات المحاسبية محتوى إعلامي يختلف عن الأخر، وأن تغير المدينين وتغير الدائنين الأكثر قدرة على تفسير التدفقات النقدية والتنبؤ بها إلى جانب مخصصات الإهتلاك والمؤونات وتدني القيم، في حين أن كل من تغير الضرائب المؤجلة أصول، تغير الضرائب المؤجلة خصوم، وتغير المخزونات ليس لها دلالة إحصائية، ولا تساهم في تفسير التدفقات النقدية والتنبؤ بها للمؤسسات الاقتصادية الجزائرية.
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Economic theory predicts that (in the absence of mispricing) the excess return to socially responsible businesses is negative in equilibrium. In contrast, using the state-of-art empirical models and a sample spanning four decades (1984–2020), an equal-weighted portfolio of companies that treat their employees the best earns an excess return of 2% to 2.7% per year. The estimated alphas are positive in most periods within the sample (with no upward or downward trend) and are particularly large during crisis periods. Overall, the results suggest that the stock market (still) undervalues employee satisfaction.
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Prior research documents that asset growth is negatively associated with future firm performance. In contrast, we show that growth financed by product market stakeholders (i.e., “operating growth”) is positively associated with future firm performance. Investors and security analysts underestimate the positive effects of operating growth on future performance, resulting in return predictability and overly pessimistic earnings forecasts for firms with high operating growth. Future stock returns largely concentrate around subsequent earnings announcements with declining magnitudes, consistent with the error-in-expectation explanation. Results from cross-sectional tests further support the hypothesis that operating growth signals high future performance but investors underreact to it.
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We examine prominent market anomalies and evaluate the efficacy of alternative asset pricing models under different financial integration settings. A financial integration index is developed for classifying 25 sample markets into high-, medium- and low integration groups. Size is found to be the strongest anomaly in world markets, followed by value and liquidity. Value and profitability effects are larger for low-integrated markets. Highly integrated markets experience short-term momentum while many low-integrated markets exhibit mild reversals. Fama and French five-factor model outperforms capita l asset pricing model (CAPM) and Fama and French three-factor model in explaining returns. International factors augment the role of local factors for more integrated markets. Our study has implications for global investors to design anomaly based investment strategies.
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Under rational asset pricing theory, and in efficient, frictionless market, risk should be priced contemporaneously and, thus, the market meltdown during the COVID‐19 pandemic must have been a contingent valuation of newly created risk. In contrast, we find that the reduction in equity value during the pandemic was stronger for stocks with higher pre‐pandemic accrued risk. This lends support to the discrete pricing proposition, which is a form of behavioural bias where investors price accrued risk during significant corporate or macroeconomic events. Furthermore, we compare the pricing of accrued risk during the pandemic with the pricing of accrued risk during non‐pandemic events and during past financial crises. We report evidence that pricing of accrued risk results in a premium in normal times and a discount during financial turmoil. Finally, we report evidence that investors price accrued stocks discriminately, that is, they are more likely to price accrued risk of stocks of larger firms, smaller B/M, and weaker momentum. Several theoretical and practical implications are discussed inside the paper.
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Recent studies show that lottery strategies, buying non-lottery type stocks and shorting lottery-type stocks, earn positive returns on average. This study examines whether the profitability of lottery strategies is predictable, and, more importantly, whether such predictability is exploited to enhance their performance. As a predictor, we employ the speculation sentiment index recently developed by Davies (forthcoming) based on observable trading activity in the leveraged Exchange Traded Funds market. We find that the profitability of lottery strategies is predictable by the lagged speculation sentiment index both in sample and out of sample. We propose active trading rules that are implementable in real time and dynamically switch the long and short legs on the lottery strategies exploiting the predictive power of speculation sentiment. The proposed dynamic strategies significantly outperform the passive strategies, yielding significant economic gains for investors with certainty equivalent return gains of 7.41%–26.35% and increases in annualized Sharpe ratios of 0.37–1.15.
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While recent theoretical and empirical work suggests that the physical skewness of a stock’s future discrete return distribution prices stocks, it does not tell us over which return horizon(s) that physical skewness is priced. Developing a novel block bootstrap estimator that allows us to calculate realized return skewness over arbitrary horizons, we aim to identify those return horizons. In doing so, we first show that our block bootstrap estimator produces more accurate realized skewness estimates than other recent estimators do. Next, we report that the existing skewness proxies used in the empirical asset pricing literature differ in how well they predict skewness over short or long return horizons. Finally, we reveal that the skewness pricing evidence documented in the empirical asset pricing literature is mostly driven by skewness over short (and not long) return horizons.
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We introduce a real-time measure of conditional biases to firms’ earnings forecasts. The measure is defined as the difference between analysts’ expectations and a statistically optimal unbiased machine-learning benchmark. Analysts’ conditional expectations are, on average, biased upward, a bias that increases in the forecast horizon. These biases are associated with negative cross-sectional return predictability, and the short legs of many anomalies contain firms with excessively optimistic earnings forecasts. Further, managers of companies with the greatest upward-biased earnings forecasts are more likely to issue stocks. Commonly used linear earnings models do not work out-of-sample and are inferior to those analysts provide.
Book
By providing a solid theoretical basis, this book introduces modern finance to readers, including students in science and technology, who already have a good foundation in quantitative skills. It combines the classical, decision-oriented approach and the traditional organization of corporate finance books with a quantitative approach that is particularly well suited to students with backgrounds in engineering and the natural sciences. This combination makes finance much more transparent and accessible than the definition-theorem-proof pattern that is common in mathematics and financial economics. The book's main emphasis is on investments in real assets and the real options attached to them, but it also includes extensive discussion of topics such as portfolio theory, market efficiency, capital structure and derivatives pricing. Finance equips readers as future managers with the financial literacy necessary either to evaluate investment projects themselves or to engage critically with the analysis of financial managers. Supplementary material is available at www.cambridge.org/wijst.
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Purpose China's stock market, which serves as an example of emerging markets, is steadily maturing in the context of globalization. In order to analyze the pricing mechanism of China's stock market, this paper builds a six-factor model to address the market features that are structurally efficient but not entirely efficient. Design/methodology/approach This study updates the Fama–French factor model's construction process to account for the unique features of China's stock market before creating a model that incorporates size, volume, value, profitability, and profit-income factors based on institutional investors' trading behavior and research preferences. The SWS three-tier sector stock index's monthly and quarterly data for the years 2016–2021 are used as samples for this study. Findings The results imply that China's stock market is structurally efficient and exhibits high levels of rationality in the region dominated by institutional investors. Specifically, big-size and high-volume portfolios that perform well in terms of liquidity can receive trading premiums. Growth-style sectors prevail at present, and investing in sectors with strong profitability and reliable financial reporting data can produce better returns. Practical implications The research on China's stock market can be extended to improve the understanding of the development process of similar emerging markets, thereby promoting their improvement. To enhance the development of emerging markets, the regulators should attach great importance to the role of local institutional investors in driving the market to maturity. It is crucial to adopt a structured approach to examine the market pricing mechanism throughout the middle stage of the transition from developing to mature markets. Originality/value This study offers a structured viewpoint on asset pricing in growing emerging markets by combining the multi-factor pricing model approach with behavioral finance theories.
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In this paper, we infer how the estimates of firm value by “optimists” and “pessimists” evolve in response to information shocks. Specifically, we examine returns and disagreement measures for portfolios of short-sale-constrained stocks that have experienced large gains or large losses. Our analysis suggests the presence of two groups, one of which overreacts to new information and remains biased over about 5 years, and a second group, which underreacts and whose expectations are unbiased after about 1 year. Our results have implications for the belief dynamics that underlie the momentum and long-term reversal effect.
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Purpose In order to provide an updated view on the drivers of German stock returns, the authors evaluate the relative performance of nine competing neoclassical asset pricing models in the German stock market between November 1991 and December 2021. Design/methodology/approach The authors conduct asymptotically valid tests of model comparison when the extent of model mispricing is gauged by the squared Sharpe ratio improvement measure of Barillas et al. (2020). Findings The study finds that the Fama and French six-factor model with both traditional and updated value factors emerges as the dominant model. Originality/value The authors shed new light on the drivers of German stock returns through an updated and extended period of analysis, wider range of potential models and utilization of valid asymptotic tests of model comparison when models are nonnested (Barillas et al. , 2020).
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The Capital Asset Pricing Model (CAPM) measures only a linear relationship between the Risk and the Return. However, market dynamics and anomalies calls for understanding the relationship in between risk and return from non-linear perspective. Thus, current study explores an opportunity to study asset value anomalies by Constructing Decile Portfolio for the period starting from 2001 to 2018 with 900 firms listed. GMM (Generalized method of moment and Wald test are applied to see the robustness of results. For further analysis, Risk Adjusted CAPM, Fama French 3 Factor (FF3) and 5 Factor (FF5) are applied. Empirical results indicate that value effect and debt to equity ratio are essential factors and genuinely explain what CAPM fails to explain. The findings from the study recommend that investing in High value and high leverage firm will generate abnormal returns to investors. Taking long position in high value firm and short position in low value firms and same with debt to equity anomaly. The results will help financial analyst develop investment strategies for well diversified and efficient portfolios. These results can also be helpful to financial firm and security analyst in the financial market where they can take appropriate capital budget decisions while investing.
Chapter
Ingeniously Simple to Survive the Pandemic with Portfolio Management – More Value, Revenues and Resilience in Life, for Companies and Assets How do we succeed in life? That was already the core question of classical philosophy? How can we remain resilient in today’s pandemic? Portfolio theory provides us with guiding thoughts on how we can optimally structure assets individually according to the criteria of safeguarding values or risk-return ratios and seizing opportunities, even under the effects of the Corona virus. Their findings can be transferred to the efficient configuration of business models in enterprises. Portfolio-analytically set up business models prove to be robust and even antifragile in the pandemic – they become even more successful. Finally, the narrative of portfolio analysis has also proven itself for the design of an efficiently diversified life in pandemic times. Those who position their lives broadly and deeply, and thus balance between opportunities and risks, defy the current epochal challenges with resilience. Schlüsselwörter/Keywords Asset Allocation Portfolio-Optimierung Rebalancing Diversifikation versus Spekulation Glück und Gestaltung der Lebenszeit Lifetime Asset Allocation Resilience robuste Geschäftsmodelle effiziente Konfiguration Strategischer GeschäftsfelderRisikotragfähigkeitRisikotoleranzAnlagehorizontZeitpräferenzAntifragilitätPerformanceRealrenditeAsset allocationportfolio-optimisationrebalancingdiversification versus speculationhappiness and shaping the time of lifelifetime asset allocationresilience of business modelsefficient configuration of strategic business areasrisk-bearing capacityrisk toleranceinvestment horizontime preferenceantifragileperformance
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We survey recent methodological contributions in asset pricing using factor models and machine learning. We organize these results based on their primary objectives: estimating expected returns, factors, risk exposures, risk premia, and the stochastic discount factor as well as model comparison and alpha testing. We also discuss a variety of asymptotic schemes for inference. Our survey is a guide for financial economists interested in harnessing modern tools with rigor, robustness, and power to make new asset pricing discoveries, and it highlights directions for future research and methodological advances. Expected final online publication date for the Annual Review of Financial Economics, Volume 13 is November 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Chapter
Ingeniously Simple to Survive the Pandemic With Portfolio Management – More Value, Revenues and Resilience in Life, for Companies and Assets How do we succeed in life? That was already the core question of classical philosophy? How can we remain resilient in today’s pandemic? Portfolio theory provides us with guiding thoughts on how we can optimally structure assets individually according to the criteria of safeguarding values or risk-return ratios and seizing opportunities, even under the effects of the Corona virus. Their findings can be transferred to the efficient configuration of business models in enterprises. Portfolio-analytically set up business models prove to be robust and even antifragile in the pandemic – they become even more successful. Finally, the narrative of portfolio analysis has also proven itself for the design of an efficiently diversified life in pandemic times. Those who position their lives broadly and deeply, and thus balance between opportunities and risks, defy the current epochal challenges with resilience. Ключевые слова/Keywordsраспределение активовоптимизация портфеляребалансировкадиверсификация и спекуляциисчастье и устройство жизненного путиструктура долгосрочного портфеля активовустойчивостьустойчивые бизнес-моделиэффективное структурированиестратегические направления деятельностиприемлемый рисктолерантность к рискугоризонт инвестированияпредпочтение времениантихрупкостьдоходностьреальная доходностьAsset allocationportfolio-optimisationrebalancingdiversification versus speculationhappiness and shaping the time of lifelifetime asset allocationresilience of business modelsefficient configuration of strategic business areasrisk-bearing capacityrisk toleranceinvestment horizontime preferenceantifragileperformance
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I examine a large set of 124 cross-sectional anomalies in international equity markets. Many of the significant U.S. anomalies replicate in equal-weighted portfolios. However, international equal-weighted portfolios are dominated by microcaps with very limited investment capacity. Only few anomalies survive when mitigating the impact of tiny stocks, accounting for multiple testing, and using factor models to adjust for expected returns. Accounting for the former two, only 15 anomalies yield significant long–short returns in the ex-U.S. world cross-section. Across regions, value anomalies are strongest. In all international markets, except for Asia Pacific, the best U.S. factor models help to further shrink the cross-sections significantly.
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This paper shows that investments based on deep learning signals extract profitability from difficult-to-arbitrage stocks and during high limits-to-arbitrage market states. In particular, excluding microcaps, distressed stocks, or episodes of high market volatility considerably attenuates profitability. Machine learning-based performance further deteriorates in the presence of reasonable trading costs because of high turnover and extreme positions in the tangency portfolio implied by the pricing kernel. Despite their opaque nature, machine learning methods successfully identify mispriced stocks consistent with most anomalies. Beyond economic restrictions, deep learning signals are profitable in long positions and recent years and command low downside risk. This paper was accepted by Kay Giesecke, finance.
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The momentum strategy seeks to profit from established price trends in the market. Many studies provide empirical evidence that investing in momentum stocks can achieve superior returns. The momentum effect is primarily attributed to behavioural biases in investing. This chapter discusses the characteristics and performance of the momentum factor as well as its place in multifactor investing. It explains the relevance of time window in the construction of momentum strategies. The chapter provides a model to evaluate the quality of price trends. It shows the potential of trend quality to enhance the momentum effect.
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We examine long-run firm performance following open market share repurchase announcements, 1980–1990. We find that the average abnormal four-year buy-and-hold return measured after the initial announcement is 12.1%. For ‘value’ stocks, companies more likely to be repurchasing shares because of undervaluation, the average abnormal return is 45.3%. For repurchases announced by ‘glamour’ stocks, where undervaluation is less likely to be an important motive, no positive drift in abnormal returns is observed. Thus, at least with respect to value stocks, the market errs in its initial response and appears to ignore much of the information conveyed through repurchase announcements.
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We find that the determinants of the cross-section of expected stock returns are stable in their identity and influence from period to period and from country to country. Out-of-sample predictions of expected return are strongly and consistently accurate. Two findings distinguish this paper from others in the contemporary literature: First, stocks with higher expected and realized rates of return are unambiguously lower in risk than stocks with lower returns. Second, the important determinants of expected stock returns are strikingly common to the major equity markets of the world. Overall, the results seem to reveal a major failure in the Efficient Markets Hypothesis.
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This paper relates cross-sectional differences in returns on Japanese stocks to the underlying behavior of four variables: earnings yield, size, book to market ratio, and cash flow yield. Alternative statistical specifications and various estimation methods are applied to a comprehensive, high-quality data set that extends from 1971 to 1988. The sample includes both manufacturing and nonmanufacturing firms, companies from both sections of the Tokyo Stock Exchange, and also delisted securities. The authors' findings reveal a significant relationship between these variables and expected returns in the Japanese market. Of the four variables considered, the book to market ratio and cash flow yield have the most significant positive impact on expected returns. Copyright 1991 by American Finance Association.
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Companies issuing stock during 1970 to 1990, whether an initial public offering or a seasoned equity offering, have been poor long-run investments for investors. During the five years after the issue, investors have received average returns of only 5 percent per year for companies going public and only 7 percent per year for companies conducting a seasoned equity offer. Book-to-market effects account for only a modest portion of the low returns. An investor would have had to invest 44 percent more money in the issuers than in nonissuers of the same size to have the same wealth five years after the offering date. Copyright 1995 by American Finance Association.
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We examine (1) how value premiums vary with firm size, (2) whether the CAPM explains value premiums, and (3) whether, in general, average returns compensate β in the way predicted by the CAPM. Loughran's (1997) evidence for a weak value premium among large firms is special to 1963 to 1995, U.S. stocks, and the book-to-market value-growth indicator. Ang and Chen's (2005) evidence that the CAPM can explain U.S. value premiums is special to 1926 to 1963. The CAPM's more general problem is that variation in β unrelated to size and the value-growth characteristic goes unrewarded throughout 1926 to 2004.
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We study whether the behavior of stock prices, in relation to size and book-to-market-equity (BE/ME), reflects the behavior of earnings. Consistent with rational pricing, high BE/ME signals persistent poor earnings and low BE/ME signals strong earnings. Moreover, stock prices forecast the reversion of earnings growth observed after firms are ranked on size and BE/ME. Finally, there are market, size, and BE/ME factors in earnings like those in returns. The market and size factors in earnings help explain those in returns, but we find no link between BE/ME factors in earnings and returns.
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A great many people provided comments on early versions of this paper which led to major improvements in the exposition. In addition to the referees, who were most helpful, the author wishes to express his appreciation to Dr. Harry Markowitz of the RAND Corporation, Professor Jack Hirshleifer of the University of California at Los Angeles, and to Professors Yoram Barzel, George Brabb, Bruce Johnson, Walter Oi and R. Haney Scott of the University of Washington.
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Prior research reveals that the accrual component of profitability is less persistent than the cash flow component, and that investors fail to fully appreciate their differing implications for future profitability (Sloan 1996). However, accruals are a component of growth in net operating assets as well as a component of profitability. Just as we can disaggregate profitability into accruals and cash flows from operations, we can disaggregate growth in net operating assets into accruals and growth in long-term net operating assets. We find, after controlling for current profitability, that both components of growth in net operating assets - accruals and growth in long-term net operating assets - have equivalent negative associations with one-year-ahead return on assets. This result is consistent with conservative accounting and diminishing marginal returns on investments. We also find, after controlling for current profitability, that the market appears to equivalently overvalue accruals and growth in long-term net operating assets relative to their association with one-year-ahead ROA. Our evidence suggests that the accrual anomaly documented in Sloan (1996) is a special case of what could be viewed as a more general growth anomaly.
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The value premium in U.S. stock returns is robust. The positive relation between average return and book-to-market equity is as strong for 1929 to 1963 as for the subsequent period studied in previous papers. A three-factor risk model explains the value premium better than the hypothesis that the book-to-market characteristic is compensated irrespective of risk loadings.
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This paper identifies five common risk factors in the returns on stocks and bonds. There are three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity. There are two bond-market factors, related to maturity and default risks. Stock returns have shared variation due to the stock-market factors, and they are linked to bond returns through shared variation in the bond-market factors. Except for low-grade corporates, the bond-market factors capture the common variation in bond returns. Most important, the five factors seem to explain average returns on stocks and bonds.
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Estimates of the cost of equity for industries are imprecise. Standard errors of more than 3.0% per year are typical for both the CAPM and the three-factor model of Fama and French (1993). These large standard errors are the result of(i) uncertainty about true factor risk premiums and (ii) imp ecise estimates of the loadings of industries on the risk factors. Estimates of the cost of equity for firms and projects are surely even less precise.
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Valuation theory says that expected stock returns are related to three variables: the book-to-market equity ratio (B-t/M-t), expected profitability, and expected investment. Given B-t/M-t and expected profitability, higher expected rates of investment imply lower expected returns. But controlling for the other two variables, more profitable firms have higher expected returns, as do firms with higher B-t/M-t. These predictions are confirmed in our tests. (c) 2006 Elsevier B.V. All rights reserved.
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Firms that substantially increase capital investments subsequently achieve negative benchmark-adjusted returns. The negative abnormal capital investment/return relation is shown to be stronger for firms that have greater investment discretion, i.e., firms with higher cash flows and lower debt ratios, and is shown to be significant only in time periods when hostile takeovers were less prevalent. These observations are consistent with the hypothesis that investors tend to underreact to the empire building implications of increased investment expenditures. Although firms that increase capital investments tend to have high past returns and often issue equity, the negative abnormal capital investment/return relation is independent of the previously documented long-term return reversal and secondary equity issue anomalies.
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The value premium in U.S. stocks returns is robust. The positive relation between average return and book-to-market equity (BE/ME) is as strong for 1929-63 as for the subsequent period studied in previous papers. Like others, we also find a size premium in stock returns. Small stocks have higher average returns than big stocks. The size premium is, however, weaker and less reliable than the value premium. The relations between average return and firm characteristics (size and BE/ME) are better explained by a three-factor risk model than by the behavioral hypothesis that investor overreaction causes characteristics to be compensated irrespective of risk loadings.
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The book-to-market ratio (B/M) is a noisy measure of expected stock returns because it also varies with expected cashflows. Our hypothesis is that the evolution of B/M, in terms of past changes in book equity and price, contains independent information about expected cashflows that can be used to improve estimates of expected returns. The tests support this hypothesis, with results that are largely but not entirely similar for Microcap stocks (below the 20-super-th NYSE market capitalization percentile) and All but Micro stocks (ABM). Copyright (c) 2008 The American Finance Association.
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This paper documents that strategies that buy stocks that have performed well in the past and sell stocks that hav e performed poorly in the past generate significant positive returns o ver three- to twelve-month holding periods. The authors find that the profitability of these strategies are not due to their systematic risk or to delay ed stock price reactions to common factors. However, part of the abnorm al returns generated in the first year after portfolio formation dissipates in the following two years. A similar pattern of returns around the earnings announcements of past winners and losers is also documented. Copyright 1993 by American Finance Association.
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A large body of literature suggests that firm-level stock prices "underreact" to news about future cash flows. We estimate a vector autoregession to examine the joint behavior of returns, cash-flow news, and trading between individuals and institutions. Our main finding is that institutions buy shares from individuals in response to good cash-flow news, thus exploiting the underreaction phenomenon. Institutions are not simply following price momentum strategies: When price goes up in the absence of positive cash-flow news, institutions sell shares to individuals. The response of institutional ownership to cash-flow news is weaker for small stocks. Since small stocks also exhibit the strongest underreaction patterns, this finding is consistent with institutions facing exogenous constraints in trading small stocks.
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We examine (1) how value premiums vary with firm size, (2) whether the CAPM explains value premiums, and (3) whether, in general, average returns compensate β in the way predicted by the CAPM. Loughran's (1997) evidence for a weak value premium among large firms is special to 1963 to 1995, U.S. stocks, and the book-to-market value-growth indicator. Ang and Chen's (2005) evidence that the CAPM can explain U.S. value premiums is special to 1926 to 1963. The CAPM's more general problem is that variation in β unrelated to size and the value-growth characteristic goes unrewarded throughout 1926 to 2004. Copyright 2006 by The American Finance Association.
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This study examines the empirical relationship between the return and the total market value of NYSE common stocks. It is found that smaller firms have had higher risk adjusted returns, on average, than larger firms. This ‘size effect’ has been in existence for at least forty years and is evidence that the capital asset pricing model is misspecified. The size effect is not linear in the market value; the main effect occurs for very small firms while there is little difference in return between average sized and large firms. It is not known whether size per se is responsible for the effect or whether size is just a proxy for one or more true unknown factors correlated with size.
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Financing decisions seem to violate the central predictions of the pecking order model about how often and under what circumstances firms issue equity. Specifically, most firms issue or retire equity each year, and the issues are on average large and not typically done by firms under duress. We estimate that during 1973–2002, the year-by-year equity decisions of more than half of our sample firms violate the pecking order.
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Post-1970, share issuance exhibits a strong cross-sectional ability to predict stock returns. This predictive ability is more statistically significant than the individual predictive ability of size, book-to-market, or momentum. Our finding is related to research that finds that long-run returns are associated with share repurchase announcements, seasoned equity offerings, and stock mergers, although our results remain strong even after exclusion of the data used in these studies. We estimate the issuance relation pre-1970 and find no statistically significant predictive ability for most holding periods. Copyright 2008 by The American Finance Association.
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The book-to-market effect is often interpreted as evidence of high expected returns on stocks of "distressed" firms with poor past performance. We dispute this interpretation. We find that while a stock's future return is unrelated to the firm's past accounting-based performance, it is strongly negatively related to the "intangible" return, the component of its past return that is orthogonal to the firm's past performance. Indeed, the book-to-market ratio forecasts returns because it is a good proxy for the intangible return. Also, a composite equity issuance measure, which is related to intangible returns, independently forecasts returns. Copyright 2006 by The American Finance Association.
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The authors study whether the behavior of stock prices, in relation to size and book-to-market equity (BE/ME), reflects the behavior of earnings. Consistent with rational pricing, high BE/ME signals persistent poor earnings and low BE/ME signals strong earnings. Moreover, stock prices forecast the reversion of earnings growth observed after firms are ranked on size and BE/ME. Finally, there are market, size, and BE/ME factors in earnings like those in returns. The market and size factors in earnings help explain those in returns but the authors find no link between BE/ME factors in earnings and returns. Copyright 1995 by American Finance Association.
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Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market "beta", size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in "beta" that is unrelated to size, t he relation between market "beta" and average return is flat, even when "beta" is the only explanatory variable. Copyright 1992 by American Finance Association.
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: Various theories have been proposed to explain momentum in stock returns. We test the gradual-information-diffusion modelofHong and Stein (1999) and establish three key results. First, once one moves past the very smallest stocks, the profitability of momentum strategies declines sharply with firm size. Second, holding size fixed, momentum strategies work better among stocks with low analyst coverage. Finally, the effect of analyst coverage is greater for stocks that are past losers than for past winners. These findings are consistent with the hypothesis that firm-specific information, especially negative information, diffuses only gradually across the investing public. * Hong is from the Stanford Business School, Lim is from the AmosTuck School, Dartmouth College, and Stein is from the MIT Sloan School of Management and the National Bureau of Economic Research. This research is supported by the National Science Foundation and the Finance Research Center at MIT. We are grateful to J...
Returnstobuyingwinnersandsellinglosers: Implications for stock market efficiency
  • Jegadeesh
  • Narasimhan
Jegadeesh,Narasimhan,andSheridanTitman,1993,Returnstobuyingwinnersandsellinglosers: Implications for stock market efficiency, Journal of Finance 48, 65–91
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