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Article
Publication date: 11 October 2021

Asgar Ali and Hajam Abid Bashir

This study aims to provide a comprehensive overview of asset pricing research and identifies the general research trends in the area. The study also aims to provide future…

Abstract

Purpose

This study aims to provide a comprehensive overview of asset pricing research and identifies the general research trends in the area. The study also aims to provide future direction to the researchers in the area of asset pricing.

Design/methodology/approach

The study uses bibliometric analysis techniques to achieve the stated purpose. The study covers 3,007 articles published in the top 50 finance and economics journals, accessed from the Scopus database for a period of 47 years (1973–2020). After initial searching for “asset pricing” as the main keyword in “title, abstract, keywords”, the database yields 6,583 articles. This number further reduces to 3,007 articles when the search is restricted to research and review articles published in the top 50 peer-reviewed journals.

Findings

The tabular and pictorial representation obtained from the analysis exhibit that asset pricing is an extensively researched area; however, a sudden rise in the number of publications (242) observed for 2019 demonstrates a growing interest amongst researchers. Further, affiliation statistics indicate that the volume of research is mainly concentrated in the USA and other developed nations; hence it opens vistas for the exploration of risk-return dynamics in the context of emerging markets.

Originality/value

The work presents an exhaustive and comprehensive review along with potential research implications. The present study reconciles various contradictory views of the prior studies under asset pricing such as risk-return trade-off, low-risk anomaly and provides the researchers with potential research gaps.

Details

Qualitative Research in Financial Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1755-4179

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Article
Publication date: 4 May 2020

Rahul Roy and Santhakumar Shijin

The purpose of the study is to examine the dynamics in the troika of asset pricing, volatility, and the business cycle in the US and Japan.

Abstract

Purpose

The purpose of the study is to examine the dynamics in the troika of asset pricing, volatility, and the business cycle in the US and Japan.

Design/methodology/approach

The study uses a six-factor asset pricing model to derive the realized volatility measure for the GARCH-type models.

Findings

The comprehensive empirical investigation led to the following conclusion. First, the results infer that the market portfolio and human capital are the primary discounting factors in asset return predictability during various phases of the subprime crisis phenomenon for the US and Japan. Second, the empirical estimates neither show any significant impact of past conditional volatility on the current conditional volatility nor any significant effect of subprime crisis episodes on the current conditional volatility in the US and Japan. Third, there is no asymmetric volatility effect during the subprime crisis phenomenon in the US and Japan except the asymmetric volatility effect during the post-subprime crisis period in the US and full period in Japan. Fourth, the volatility persistence is relatively higher during the subprime crisis period in the US, whereas during the subprime crisis transition period in Japan than the rest of the phases of the subprime crisis phenomenon.

Originality/value

The study argues that the empirical investigations that employed the autoregressive method to derive the realized volatility measure for the parameter estimation of GARCH-type models may result in incurring spurious estimates. Further, the empirical results of the study show that using the six-factor asset pricing model in an intertemporal framework to derive the realized volatility measure yields better estimation results while estimating the parameters of GARCH-type models.

Details

Journal of Economic Studies, vol. 48 no. 1
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 1 March 2006

Philip Gharghori, Howard Chan and Robert Faff

Daniel and Titman (1997) contend that the Fama‐French three‐factor model’s ability to explain cross‐sectional variation in expected returns is a result of characteristics…

Abstract

Daniel and Titman (1997) contend that the Fama‐French three‐factor model’s ability to explain cross‐sectional variation in expected returns is a result of characteristics that firms have in common rather than any risk‐based explanation. The primary aim of the current paper is to provide out‐of‐sample tests of the characteristics versus risk factor argument. The main focus of our tests is to examine the intercept terms in Fama‐French regressions, wherein test portfolios are formed by a three‐way sorting procedure on book‐to‐market, size and factor loadings. Our main test focuses on ‘characteristic‐balanced’ portfolio returns of high minus low factor loading portfolios, for different size and book‐to‐market groups. The Fama‐French model predicts that these regression intercepts should be zero while the characteristics model predicts that they should be negative. Generally, despite the short sample period employed, our findings support a risk‐factor interpretation as opposed to a characteristics interpretation. This is particularly so for the HML loading‐based test portfolios. More specifically, we find that: the majority of test portfolios tend to reveal higher returns for higher loadings (while controlling for book‐to‐market and size characteristics); the majority of the Fama‐French regression intercepts are statistically insignificant; for the characteristic‐balanced portfolios, very few of the Fama‐French regression intercepts are significant.

Details

Pacific Accounting Review, vol. 18 no. 1
Type: Research Article
ISSN: 0114-0582

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Article
Publication date: 31 December 2019

Vaibhav Lalwani and Madhumita Chakraborty

The purpose of this paper is to compare the performance of various multifactor asset pricing models across ten emerging and developed markets.

Abstract

Purpose

The purpose of this paper is to compare the performance of various multifactor asset pricing models across ten emerging and developed markets.

Design/methodology/approach

The general methodology to test asset pricing models involves regressing test asset returns (left-hand side assets) on pricing factors (right-hand side assets). Then the performance of different models is evaluated based on how well they price multiple test assets together. The parameters used to compare relative performance of different models are their pricing errors (GRS statistic and average absolute intercepts) and explained variation (average adjusted R2).

Findings

The Fama-French five-factor model improves the pricing performance for stocks in Australia, Canada, China and the USA. The pricing in these countries appears to be more integrated. However, the superior performance in these four countries is not consistent across a variety of test assets and the magnitude of reduction in pricing errors vis-à-vis three- or four-factor models is often economically insignificant. For other markets, the parsimonious three-factor model or its four-factor variants appear to be more suitable.

Originality/value

Unlike most asset pricing studies that use test assets based on variables that are already used to construct RHS factors, this study uses test assets that are generally different from RHS sorts. This makes the tests more robust and less biased to be in favour of any multifactor model. Also, most international studies of asset pricing tests use data for different markets and combine them into regions. This study provides the evidence from ten countries separately because prior research has shown that locally constructed factors are more suitable to explain asset prices. Further, this study also tests for the usefulness of adding a quality factor in the existing asset pricing models.

Details

Managerial Finance, vol. 46 no. 3
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 8 June 2021

Huong Le and Andros Gregoriou

This paper aims to empirically examine the relationship between stock liquidity and asset pricing, using a new price impact ratio adjusted for free float as the…

Abstract

Purpose

This paper aims to empirically examine the relationship between stock liquidity and asset pricing, using a new price impact ratio adjusted for free float as the approximation of liquidity. The free-float-adjusted ratio is free from size bias and encapsulates the impact of trading frequency. It is more comprehensive than alternative price impact ratios because it incorporates the shares available to the public for trading.

Design/methodology/approach

The authors are using univariate and multivariate econometric methods to test the significance of a newly created price impact ratio. The authors are using secondary data and asset pricing models in their analysis. The authors use a data sample of all US listed companies over the period of 1997–2017.

Findings

The authors provide evidence that the free-float-adjusted price impact ratio is superior to all price impact ratios used in the previous academic literature. The authors also discover that their findings are robust to the financial crises between 2007 and 2009.

Originality/value

This is the first comprehensive study on a newly established price impact ratio. The authors show the significance of this ratio and explain why it is superior to all previous price impact ratios, established in prior research.

Details

Journal of Economic Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3585

Keywords

Content available
Article
Publication date: 18 June 2021

Mehak Jain and Ravi Singla

Asset pricing revolves around the core aspects of risk and expected return. The main objective of the study is to test different asset pricing models for the Indian…

Abstract

Purpose

Asset pricing revolves around the core aspects of risk and expected return. The main objective of the study is to test different asset pricing models for the Indian securities market. This paper aims to analyse whether leverage and liquidity augmented five-factor model performs better than Capital Asset Pricing Model (CAPM), Fama and French three-factor model, leverage augmented four-factor model and liquidity augmented four-factor model.

Design/methodology/approach

The data for the current study comprises records on prices of securities that are part of the Nifty 500 index for a time frame of 14 years, that is, from October 2004 to September 2017 consisting of 183 companies using time series regression.

Findings

The results indicate that the five-factor model performs better than CAPM and the three-factor model. The model outperforms leverage augmented and liquidity augmented four-factor models. The empirical evidence shows that the five-factor model has the highest explanatory power among the entire asset pricing models considered.

Practical implications

The present study bears certain useful implications for various stakeholders including fund managers, investors and academicians.

Originality/value

This study presents a five-factor model containing two additional factors, that is, leverage and liquidity risk along with the Fama-French three-factor model. These factors are expected to give more value to the model in comparison to the Fama-French three-factor model.

Details

Vilakshan - XIMB Journal of Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0973-1954

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Book part
Publication date: 30 November 2011

Massimo Guidolin

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models

Abstract

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

Details

Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

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Article
Publication date: 6 July 2010

Keiichi Kubota and Hitoshi Takehara

The purpose of this paper is to determine the best conditional asset pricing model for the Tokyo Stock Exchange sample by utilizing long‐run daily data. It aims to…

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Abstract

Purpose

The purpose of this paper is to determine the best conditional asset pricing model for the Tokyo Stock Exchange sample by utilizing long‐run daily data. It aims to investigate whether there are any other firm‐specific variables that can explain abnormal returns of the estimated asset pricing model.

Design/methodology/approach

The individual firm sample was used to conduct various cross‐sectional tests of conditional asset pricing models, at the same time as using test portfolios in order to confirm the mean variance efficiency of basic unconditional models.

Findings

The paper's multifactor models in unconditional forms are rejected, with the exception of the five‐factor model. Further, the five‐factor model is better overall than the Fama and French model and other alternative models, according to both the Gibbons, Ross, and Shanken test and the Hansen and Jagannathan distance measure test. Next, using the final conditional five‐factor model as the de facto model, it was determined that the turnover ratio and the size can consistently predict Jensen's alphas. The book‐to‐market ratio (BM) and the past one‐year returns can also significantly predict the alpha, albeit to a lesser extent.

Originality/value

In the literature related to Japanese data, there has never been a comprehensive test of conditional asset pricing models using the long‐run data of individual firms. The conditional asset pricing model derived for this study has led to new findings about the predictability of past one‐year returns and the turnover ratio.

Details

Managerial Finance, vol. 36 no. 8
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 1 February 1994

RayBall

The nature and extent of our knowledge of stock market efficiency are examined. The development of “efficiency”, as a way of thinking about stock markets, is traced from…

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1624

Abstract

The nature and extent of our knowledge of stock market efficiency are examined. The development of “efficiency”, as a way of thinking about stock markets, is traced from Roberts (1959) and Fama (1965) onward. The early work successfully introduced competitive economic theory to the study of stock markets and paved the way for a flood of empirical research on the relation between information and stock prices. This literature irreversibly altered our views on stock market behavior. The theory and evidence of seemingly‐rational use of information lay in sharp contrast to prior beliefs. It was associated with a widespread increase in respect for stock markets, financial markets, and markets in general, at the time. Researchers began developing and using a variety of formal models of security prices. Nevertheless, “efficiency” has its limitations, both theoretically (as a way of characterizing markets) and empirically (by stretching the quality of the data, the estimation techniques used, and our knowledge of price behavior in competitive markets). Extensive evidence of anomalies suggests either that the market systematically misprices securities or that the theoretical or empirical limitations are binding, or both. The less interesting research question now is whether markets are efficient, and the more interesting question is how we can learn more about price and transactions behavior in competitive stock markets. The concept of an “efficient stock market” has stimulated both insight and controversy since Fama (1965) introduced it to the financial economics literature. As a construct, “efficiency” models the stock market in terms of the reaction of prices to the flow of information. Like all theory choices, modelling the market in this fashion involved tradeoffs. The benefits included opening the literature to an abundance of high‐quality researchable data, covering a variety of information, and the resulting insights obtained on the role of information in setting prices. The opportunity costs included temporarily closing the literature to alternative ways of viewing stock markets, for example by modelling public information as a homogenous good and thus ignoring factors such as differences in beliefs among investors, differences in information processing costs, and the “animal spirits” that might drive group behavior. The costs also included reliance on particular asset‐pricing models of how an “efficient” market would set prices. Not surprisingly, the ensuing deluge of research has produced some startling evidence, for and against the proposition that financial markets are “efficient”. Strongly‐conflicting views and puzzling anomalies remain. The early evidence seemed unexpectedly consistent with the theory. The theory, and its implications, also seemed clear at the time. After a period that seems short in retrospect, the growing body of evidence in favor of the efficient market hypothesis emerged as one of the most influential empirical areas of economics. Fama's (1970) review described a flourishing, coherent and confident literature. This research had an irreversible effect on our knowledge of and attitude toward stock markets, and financial markets generally. It coincided with an emergence of interest in, and respect for, all markets among economists and politicians, and influenced the worldwide trend toward “liberalizing” financial and other markets. The research consistently appeared to show an unbiased reaction of stock prices to public information. The property of “unbiased reaction” to public information, which formed the basis of the early definitions of “efficiency”, was seen to be an implication of rational, maximizing investor behavior in competitive securities markets (Fama 1965, p.4). Reduced to a basic level, the reasoning was that any systematicallybiased reaction to public information is costlessly publicly observable, and thus provides pure profit opportunities to be competed away. Characterizing the market in terms of its reaction to information is only one of many feasible ways of modelling stock price behavior, but it introduced economic theoryto the empirical studyof stock prices, which had received little serious attention from economists prior to that point. Despite the subsequent spate of anomalies, the early efficiency literature not only adapted standard economic theoryto provide the first formal economic insights into how stock prices behave, but it helped pave the way for an outporing of theoretical and empirical work on stock markets and capital markets in general. Subsequent empirical research was not as consistent with the theory. Evidence of “anomalous” return behavior now is widespread and well‐known. It generallytakes the form of variables (for example, size, day‐of‐the‐week, P/E ratio, market/book value ratio, rank of scaled earnings change, dividend yield) that are significantly but inexplicablyrelated to subsequent abnormal stock returns. Much of this evidence has defied rational economic explanation to date and appears to have caused many researchers to strongly qualify their views on market efficiency. Disagreement has not been not confined to the evidence. The literature has produced a variety of research designs, ranging from the “market model” of Fama, Fisher, Jensen and Roll (FFJR, 1969) to Shiller's (1981a,b) variance‐bounds tests. The very term “efficiency” has engendered controversy: there is a modest literature on precisely what efficiency means, on the role of transaction costs, and on whether efficient markets are logically feasible. Making sense of this literature requires careful definition of “efficiency” in this context and careful analysis of the type of evidence that has been offered in relation to it. This involves an assessment of the strengths and weaknesses of both the theory of efficient markets, as a way of characterizing stock markets, and of the data and research designs used in testing it. Not surprisingly, a mixed conclusion emerges. While the concept of efficient markets was an audacious departure from the comparative ignorance and suspicion among economists of stock markets that preceded it, and provides valuable insights into their behavior, the concept has its limitations, in terms of both its internal logical coherence and its fit with the data. Section 1 ofthis survey sketches the development of the efficient market theory, reviewing the principal contributions in terms of their usefulness in guiding and evaluating empirical research. Section 2 addresses the limitations inherent in what is knowable about stock market efficiency, given the present state of theory about how security prices might behave in an “efficient” market. It argues that there are binding limitations in the theoryof asset pricing, some of which are known and others of which are unknown or even unknowable. These limitations must be borne in mind when choosing whether to interpret the data as evidence of: (1) market efficiency, under the maintained hypothesis that a specific research design, including a specific model of asset pricing used to benchmark price behavior, correctly describes pricing in an efficient market; or (2) the ability of our models and research designs to encapsulate how prices behave in an efficient market, under the maintained hypothesis of efficiency. Against this background, section 3 then provides an assessment of the accomplishments of the theory of stock market efficiency, including an interpretation of the evidence. It focuses on the nature and influence of the evidence and does not attempt to provide a comprehensive literature taxonomy. The final section offers conclusions. The principal conclusion is that the theory of efficient markets has irreversibly enhanced our knowledge of and respect for stock markets (and perhaps for all financial market or even for markets in general) but that, like all theories, it is fundamentally flawed.

Details

Managerial Finance, vol. 20 no. 2
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 1 February 2000

Robert Hibbard

This paper examines the implications of standard barter models of market equilibrium for financial security returns in New Zealand. The key question addressed is: does the…

Abstract

This paper examines the implications of standard barter models of market equilibrium for financial security returns in New Zealand. The key question addressed is: does the ‘equity premium puzzle’ of Mehra and Prescott (1985) found in the U.S. also hold in ?ew Zealand? To examine the existence of the equity premium puzzle, quarterly financial security returns and consumption data are examined from 1965 to 1997 to calibrate parameters in the Consumption Based Asset Pricing Model. Unlike much of the existing international evidence, this paper corrects for durable goods consumption following the assumptions of the model that all consumption be consumed in a given period. Numerical analyses indicate that the class of models examined are unable to generate equity premia consistent with historical estimates of the equity premium in New Zealand. Due to small sample variability however, while this discrepancy is material in size, the result is not statistically significant.

Details

Pacific Accounting Review, vol. 12 no. 2
Type: Research Article
ISSN: 0114-0582

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