Is the Value Premium Smaller Than We Thought?

The subject of the study is the values of the Capital Assets Pricing Model (CAPM) components required to calculate the required return (cost) equity capital of public and non-public resident companies of the Russian Federation operating in the system of the national economy of the Russian Federation. The calculations of the 5-year and 2-year bet have been performed for all companies related to the domestic stock market. The values of these betas and their statistical characteristics are given. The value of the risk premium of a public company of small capitalization (small capitalization premium, SCP) is justified. A model of accounting for the risk premium of an average (or small) small non-public company and the value of this premium is proposed. The value of the market risk premium is empirically justified.

The early exercise premium in American put option prices

The conditional CAPM suggests that the market beta and market risk premium should vary over time. In this paper, we provide evidence that the size and value premiums are also state dependent. We develop a joint Markov regime-switching model for the CAPM and the VIX index to study the regime variation of CAPM parameters and to investigate the regime-dependent size and value anomalies. Stock returns from a two-state regime-switching model exhibit the pattern of amplified size (or value) premium in the low VIX state and reversed premium in the high VIX state. A three-state regime-switching model further confirms that the value premiums might be driven by extreme market conditions. These findings have important implications for market timing and portfolio selection decisions.

This study aims to identify the effect of terrorism on size and value premium using value weighted monthly returns for non-financial firms from January 2001 to December 2010. In addition to independent size and BE/ME (book equity to market equity) sorted portfolios, two dimensional portfolio formation methodology of Dimson, Nagel, and Quigley is used. The results reveal that market, size, value premium and terrorism have a significant positive impact on stock returns. The study further suggests that value and size premiums are dependent on the psychological impact created by terrorist attack. Findings suggest that the return on small stocks is higher than the returns on large stocks and the size premium occurs mainly during the months of higher terrorism activities. In contrast, value premium is more profound during the months of low (high) terrorist activities for portfolios sorted on one (two) dimension. This indicates that both size and BE/ME premiums are affected by investor sentiment

PurposeThe purpose of this paper is to investigate the seasonal effect in the value premium puzzle. It studies whether the book‐to‐market effect is an outcome of the January effect observed among stock returns.Design/methodology/approachThe paper uses returns of portfolios based on size and BE/ME ratios as Fama and French suggest to define value premium and investigate the seasonality of the BE/ME effect. The paper tests whether the value premiums observed among large and small stocks are different in January and non‐January months. It examines the turn‐of‐the‐year effect on the value premium by analyzing the returns of BE/ME portfolios during the first and last ten trading days of a calendar year.FindingsEmpirical evidence supports the fact that value premium has different patterns in January and non‐January months for large and small capitalization firms. It was found that large stocks have a significant value premium only in January and this high January value premium among large stocks is mainly driven by loser stocks at the turn of the year. In contrast with large stocks, the value premium of small stocks occurs only in non‐January months.Originality/valueThis paper shows that value premium of large and small stocks are different in January and non‐January months. Furthermore, the past performance of stocks plays a key role in the observed January value premium among large stocks. Finally, this study provides evidence to show that the value premium among large stocks may be explained by investor trading behavior.

ABSTRACTThis study examines arbitrage costs and the persistence of the size, value and momentum premiums on the Johannesburg Stock Exchange (JSE). Two arbitrage costs are considered: transaction and holding costs. Transaction costs refer to indirect and direct costs of engaging in arbitrage. Holding costs relate to the level of idiosyncratic risk that arbitrageurs expose themselves to in pursuit of an individual strategy. We examine monthly price and accounting data of all JSE listed shares over the period 1 January 1992 to 30 November 2014. The effects of idiosyncratic risk are evaluated with asymmetric and GARCH-in-mean models using zero-cost portfolio return series. The results reveal significant and persistent value and momentum effects. The value premium is highly sensitive and negatively related to direct transaction costs. Conversely, momentum has greater sensitivity to indirect transaction costs and displays a negative relationship. An increase in idiosyncratic risk results in an increase in the value premium. However, the momentum premium does not react positively to an increase in idiosyncratic risk. The findings imply that the costs of arbitrage play a large role in the persistence and existence of the value premium, yet the same cannot be said for medium-term momentum in share prices.

In this paper, we revisit the value premium puzzle and hypothesize that the value premium is driven by the arrival of new information specifically the news in earnings announcements. Consistent with our hypothesis, we find that a portfolio that takes positions among stocks only 5% of the year (the earnings window) contains 13% of the value premium. Furthermore, we find that there is no differential premium between value stocks and growth stocks during the non-earnings announcement periods. In other words, the other 87% of the value premium is not statistically different from the return on a risk-free portfolio. We find that the earnings-value premium, surrounding the earnings announcement window, is 10.7 basis points per trading day (26.96% per year) between June 1987 and December 2010. To investigate the value premium further, we test whether the value premium primarily persists for neglected firms who are characterized by a weaker information environment. Using three different proxies for neglect, we document that the differential premium between value and growth stocks is more for neglected firms. This evidence indicates that the value premium is primarily driven by the markets incorporation of newly released information in earnings announcements.

We show that the magnitude of the value premium over 1968-2018 is conditional on states of aggregate market-wide misvaluation. The value premium is 3.42% per month following market-wide undervaluation and 1.70% per month following market-wide overvaluation. When the aggregate market is neither significantly over- or undervalued, there is no significant value premium at a monthly horizon and the value premium is 0.60% per month at an annual horizon. Going from normal valuation states to overvaluation (undervaluation), the increase in the value premium is due primarily to the poor (good) performance of growth (value) stocks. This paper sheds new light on the value premium and investigates a potential behavioral explanation based on return extrapolation.

In models of stock returns where investors with extrapolative beliefs on future stocks (e.g., Barberis and Shleifer (2003)), price momentum and the value premium both arise naturally. The key insight from these models is that, the strength and timing of these cross- sectional return anomalies will be conditional on the degree of extrapolative bias. More specifically, higher (lower) degree of over-extrapolation leading to stronger value premium (momentum). Using the time-series variation in the degree of over-extrapolation documented in Cassella and Gulen (2018), I first directly test the hypothesis that both value and momentum stem from over-extrapolation in financial markets. I find that the average momentum return is 1.00% (0.10%) per month when the degree of over-extrapolation is low (high), whereas the average value premium is 0.51% (1.29%) per month following low (high) levels of over- extrapolation. Furthermore, I extend the model in Barberis and Shleifer (2003) by having both within- equity extrapolators and across asset-class extrapolator. The extension is based on the idea that when extrapolators move capital in and out of the equity market, they disproportionately buy growth stocks in good times and sell value stocks in bad times. The model predicts that the cross-sectional value premium should be stronger following states of large market- wide over- or undervaluation due to additional extrapolative demand to buy or sell. This prediction is tested empirically and I find strong support for it. The value premium is 3.42% per month following market-wide undervaluation and 1.70% per month following market overvaluation. In the remainder 60% to 80% of the sample, when the market is neither significantly over or under-valued, there is no significant value premium in a monthly horizon and the value premium is only 0.54% per month in an annual horizon. I provide some suggestive evidence regarding portfolio return dynamics, investor expectation errors and fund flows that supports the extrapolative demand channel. Overall, this work examines more closely at the effect of extrapolative beliefs on the cross-section of asset prices and offers some support for extrapolation-based asset-pricing theories.

Consistent with mispricing explanations proposed in the literature to explain the value premium, the value premium is driven by stocks held by individual investors. Stocks held by institutional investors do not exhibit any significant value premium nor value effect while representing 93% of the market capitalization. In contrast, in stocks most held by individual investors the value premium, even value-weighted, reaches a staggering 2% per month. This shows that the value premium is likely to be due to mispricing and that arbitraging it entails substantive costs.

PurposeThe aim of this paper is twofold. First, it aims to provide better understanding for the main sources behind the value premium in the UK. Second, given that the value factor (HML) in the Fama‐French three‐factor model is itself a proxy for value premium, this paper seeks to illustrate the component of HML responsible for explaining UK portfolio returns.Design/methodology/approachFor the period July 1991 to June 2006, value premium is broken into two components: one is related to small stocks and the other to big stocks. Then monthly time‐series regressions are used to test which component of value premium provides better explanatory power for UK portfolio returns.FindingsThe empirical results indicate that the value premium in average returns is due to small market capitalization stocks. Moreover, value stocks do not seem riskier than growth stocks according to their market beta. Furthermore, the significance of the value factor (HML) in explaining UK portfolio returns is mainly due to its small stock component (HMLS). The paper suggests a revision for the Fama‐French three‐factor model that replaces HML by HMLS.Originality/valueAcademics are interested in understanding the main sources of value premium and the reasons behind the significance of the value factor in explaining UK portfolio returns. Investors and fund managers who wish to exploit the value premium will tilt their portfolios towards value stocks that have low‐market capitalization. Both academics and practitioners may consider altering the Fama‐French model, as suggested by the paper, when estimating the cost of capital.

ABSTRACTAsset pricing is a widely explored theme in the financial literature. Nevertheless, the value premium phenomenon remains controversial because although it is easily detected in developed and emerging markets, little is actually known about the economic forces that explain its existence. In this context, this article aims to identify the value premium in major Latin American markets, as well as to determine whether the country risk could be considered an additional risk factor for conditional returns in the region that is not yet captured by the value premium. To this end, a model containing five factors, developed by adding the country risk factor to the model presented by Carhart (1997), was proposed. The statistical procedure adopted was that of Fama and French (1993) for the period between 1994 and 2012, and the data used were those from nonfinancial companies listed on the stock exchanges of Argentina, Brazil, Chile, and Mexico. We confirmed the existence of the value premium in three of the four markets analyzed: Argentina, Brazil, and Chile. The country risk and the value premium were significant factors in explaining conditional returns in only one of these countries, Brazil.

PurposeThis paper is an attempt to explore the fact that whether the literature-promised value premium has any sector orientation. The paper tests the relationship between the value premium and Indian sectors: fast-moving consumer goods (FMCG), financials, healthcare, information technology (IT), manufacturing and miscellaneous.Design/methodology/approachThe paper analyses around 210–480 companies listed on BSE-500 for the period of the recent 18 years ranging from March 1999 to March 2017. The paper employed Welch's ANOVA to examine whether the price-to-book market ratio is significantly different across sectors. Two prominent asset pricing models – single factor market model and Fama–French three-factor model – were used to examine the existence of value premium within sectors for full period and two sub-periods.FindingsThe empirical results of the paper suggest that the difference in the P/B ratio both between sectors and within sectors is statistically significant. The results further suggest that the value premium exists within the sectors irrespective of their value-growth orientation.Research limitations/implicationsThe paper is not free from certain limitations. Firstly, due to the non-availability of data in the public domain, the time period before 1999 could not be considered. Secondly, the study has used data pertaining to the Indian stock market only. To add to it, our study has concentrated on BSE-500 companies only; however, the future researchers can include both NSE and BSE companies.Practical implicationsThe paper has important implications for portfolio managers and retail investors following a top-down approach of investing. The portfolio manager can strategically build up the portfolios to concentrate more on the companies belonging to sectors like healthcare, manufacturing and FMCG. Investors following the top-down approach should avoid the underperforming growth stocks belonging to the growth sectors and allocate their funds to value stocks in the growth sector.Originality/valueThe paper is first of its kind to study the relationship between the value premium and Indian sectors. The paper contributes to portfolio management and asset pricing literature for an emerging market.

This paper studies the out-of-sample predictability of the monthly market as well as size, value, and momentum premiums. We use a sample from each the US and the Swiss stock market between 1989 and 2007. Our Swiss sample provides an important new perspective as the repeated evaluation of the same (US-) dataset leads to the problem of data mining. To exclude data mining in our predictability study, we test both statistical significance and robustness in the two samples. Our key results are as follows: We find no robust indication that the market premium is predictable. The same is true for the momentum and the value premiums: Our statistically significant results from the US sample look like data mining in light of the results from the Swiss sample. However, the size premium seems to be predictable to some extent, due to the credit spread. We assume three reasons for this - in comparison to the literature - rare evidence for predictability: first, predictability could have evaporated in the last decade as academic research made the respective information public. Second, predictability is, as we demonstrate, not robust to the choice of the methodology. Third, robustness tests unveil many statistically significant interrelations as random data structures, known as data mining. Therefore, we think that the future discussion of predictability should address the issue of data mining by applying robustness tests.

In the last decade, empirical research has found strong evidence that value stocks provide higher returns than growth stocks (value premium). Firms with a high ratio of book value of equity to market value of equity are regarded as value stocks; a low ratio identifies growth stocks. Most research is tailored to the market in the United States of America. Only a few studies consider country-specific distinctions. This research analyses the value premium for the South African market and compares its magnitude to the findings for the US market. Moreover, the effects of the introduction of International Financial Reporting Standards (IFRS) for companies listed at the JSE Limited are examined. The adoption of IFRS is used to demonstrate that investors award an accounting premium for voluntary compliance with this new accounting standard.