scholarly journals Identifying outliers in asset pricing data with a new weighted forward search estimator

2020 ◽  
Vol 31 (84) ◽  
pp. 458-472
Author(s):  
Alexandre Aronne ◽  
Luigi Grossi ◽  
Aureliano Angel Bressan
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
The United States ◽  
Estimation Methods ◽  
Annual Data ◽  
Forward Search ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
The Impact ◽  
Three Factor

ABSTRACT The purpose of this work is to present the Weighted Forward Search (FSW) method for the detection of outliers in asset pricing data. This new estimator, which is based on an algorithm that downweights the most anomalous observations of the dataset, is tested using both simulated and empirical asset pricing data. The impact of outliers on the estimation of asset pricing models is assessed under different scenarios, and the results are evaluated with associated statistical tests based on this new approach. Our proposal generates an alternative procedure for robust estimation of portfolio betas, allowing for the comparison between concurrent asset pricing models. The algorithm, which is both efficient and robust to outliers, is used to provide robust estimates of the models’ parameters in a comparison with traditional econometric estimation methods usually used in the literature. In particular, the precision of the alphas is highly increased when the Forward Search (FS) method is used. We use Monte Carlo simulations, and also the well-known dataset of equity factor returns provided by Prof. Kenneth French, consisting of the 25 Fama-French portfolios on the United States of America equity market using single and three-factor models, on monthly and annual basis. Our results indicate that the marginal rejection of the Fama-French three-factor model is influenced by the presence of outliers in the portfolios, when using monthly returns. In annual data, the use of robust methods increases the rejection level of null alphas in the Capital Asset Pricing Model (CAPM) and the Fama-French three-factor model, with more efficient estimates in the absence of outliers and consistent alphas when outliers are present.

scholarly journals A Comparative Study between the Fama and French Three-Factor Model and the Fama and French Five-Factor Model: Evidence from the Egyptian Stock Market

2019 ◽  
Vol 12 (1) ◽  
pp. 52 ◽  
Author(s):  
Nada S. Ragab ◽  
Rabab K. Abdou ◽  
Ahmed M. Sakr
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Factor Model ◽  
Five Factor Model ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
Time Period ◽  
Model Evidence ◽  
Fama And French ◽  
Three Factor

The focus of this paper is to test whether the Fama and French three-factor and five factor models can capture the variations of returns in the Egyptian stock market as one of the growing emerging markets over the time-period July 2005 to June 2016. To achieve this aim, following Fama and French (2015), the authors construct the Fama and French factors and three sets of test portfolios which are: 10 portfolios double-sorted on size and the BE/ME ratio, 10 portfolios double-sorted on size and operating profitability, and 10 portfolios double-sorted on size and investment for the Egyptian stock market. Using time-series regressions and the GRS test, the results show that although both models cannot be rejected as valid asset pricing models when applied to portfolios double-sorted on size and the BE/ME ratio, they still leave substantial variations in returns unexplained given their low adjusted R2 values. Similarly, when the two models are applied to portfolios double-sorted on size and investment, the results of the GRS test show that both models cannot be rejected. However, when the two models are applied to portfolios double-sorted on size and operating profitability, the results of the GRS test show that both models are strongly rejected which imply that both models leave substantial variations in returns related to size and profitability unexplained. Specifically, the biggest challenge to the two models is the big portfolio with weak profitability which generate a significantly negative intercept implying that the models overestimate its return.

scholarly journals Modelos de Precificação de Ativos e o Efeito Liquidez: Evidências Empíricas no Mercado Acionário Brasileiro

2011 ◽  
Vol 9 (3) ◽  
pp. 383 ◽  
Author(s):  
Márcio André Veras Machado ◽  
Otávio Ribeiro de Medeiros
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Factor Model ◽  
Five Factor Model ◽  
Explanatory Power ◽  
Liquidity Premium ◽  
Pricing Models ◽  
Portfolio Returns ◽  
Asset Pricing Models ◽  
Three Factor

This paper is aims to analyze whether a liquidity premium exists in the Brazilian stock market. As a second goal, we include liquidity as an extra risk factor in asset pricing models and test whether this factor is priced and whether stock returns were explained not only by systematic risk, as proposed by the CAPM, by Fama and French’s (1993) three-factor model, and by Carhart’s (1997) momentum-factor model, but also by liquidity, as suggested by Amihud and Mendelson (1986). To achieve this, we used stock portfolios and five measures of liquidity. Among the asset pricing models tested, the CAPM was the least capable of explaining returns. We found that the inclusion of size and book-to-market factors in the CAPM, a momentum factor in the three-factor model, and a liquidity factor in the four-factor model improve their explanatory power of portfolio returns. In addition, we found that the five-factor model is marginally superior to the other asset pricing models tested.

scholarly journals Examining asset pricing models in emerging markets: Evidence from Egypt

2018 ◽  
Vol 16 (1) ◽  
pp. 50-57 ◽  
Author(s):  
Mohamed A. Shaker ◽  
Marwan M. Abdeldayem
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Stock Exchange ◽  
Research Effort ◽  
Five Factor Model ◽  
Pricing Models ◽  
Time Series Regression ◽  
Asset Pricing Models ◽  
Time Period ◽  
Three Factor

The study aims at executing five tantamount asset pricing models in Egypt, in particular: 1) “the CAPM”, 2) “the Fama-French three-factor model (1993)”, 3) “the Carhart model (1997)”, 4) “the four-factor model of Chan and Faff (2005)”, and 5) “the five-factor model (Liquidity and Momentum-Augmented Fama-French three factor model)”. This research effort pursues Fama-French arranging approach in view of the size and Book-to-Market proportion (B-M ratio) for 55 securities out of the most 100 stocks in the Egyptian Stock Exchange (EGX) over a five years’ time period. We utilized “the time series regression of Black, Jensen and Scholes (1972)”. The findings of the study revealed that in terms of predictability, FF three-factor model prompts a significant improvement over the CAPM, while alternate models do not demonstrate a noteworthy increment over the FF three factor model.

scholarly journals Role of leverage and liquidity risk in asset pricing: evidence from Indian stock market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mehak Jain ◽  
Ravi Singla
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Five Factor Model ◽  
Explanatory Power ◽  
Liquidity Risk ◽  
Pricing Models ◽  
Content Type ◽  
Asset Pricing Models ◽  
Three Factor ◽  
Better Than

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.

scholarly journals Evaluating the Conditional CAPM using Consumption-based State Variables: Evidence from the Korean Stock Market

2021 ◽  
Vol 50 (3) ◽  
pp. 339-367
Author(s):  
Dojoon Park ◽  
Young Ho Eom ◽  
Jaehoon Hahn
Keyword(s):  
Human Capital ◽  
Asset Pricing ◽  
Risk Premium ◽  
Factor Model ◽  
State Variables ◽  
Pricing Models ◽  
Conditional Capm ◽  
Consumption Ratio ◽  
Asset Pricing Models ◽  
Three Factor

In this study, we evaluate the empirical performance of conditional asset pricing models using consumption-based measures as state variables. We incorporate three consumption variables known to forecast the equity risk premium as conditioning variables to capture time variations in the risk premium. These three variables are the consumption-aggregate wealth ratio, the surplus consumption ratio, and the labor income to consumption ratio. The asset pricing models evaluated in this study are the CAPM, the CAPM with human capital, the consumption CAPM, and the Fama-French three-factor model. We compare the unconditional and conditional specifications of these four asset pricing models using the two-pass cross-sectional regression methodology, using the size, book-to-market, turnover, and idiosyncratic risk sorted portfolios and sector portfolios as test assets. We demonstrate that the conditional CAPM with human capital performs far better than the unconditional specifications and about as well as the Fama and French three-factor model in explaining the crosssection of average stock returns in Korea.

Augmenting the intertemporal CAPM with inflation: Further evidence from alternative models

2017 ◽  
Vol 42 (4) ◽  
pp. 653-672 ◽  
Author(s):  
Qi Shi ◽  
Bin Li ◽  
Adrian (Wai Kong) Cheung ◽  
Richard Chung
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Model Fit ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
Intertemporal Capm ◽  
Three Factor ◽  
Fitting Problem

Studies consistently find that inflation is an important augmented factor for intertemporal capital asset pricing models (ICAPMs) when pricing the Fama–French 25 size and book-to-market portfolios. We extend this line of research by investigating two alternative ICAPM models (from Michel; Hahn and Lee) and the three-factor model from Hou et al. We find significant evidence that both ICAPMs and Hou et al.’s three-factor model perform better when augmented with inflation than the original models. The augmented models achieve a good model fit with the fewest factors, thus avoiding or alleviating the over-fitting problem.

Nonrevealing Equilibria and Consumption-Based Asset Pricing Models

2006 ◽  
Vol 6 (1) ◽  
Author(s):  
James E Gunderson
Keyword(s):  
Asset Pricing ◽  
Private Information ◽  
Rational Expectations ◽  
Investment Risk ◽  
Conditional Distributions ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
Empirical Tests ◽  
The Impact ◽  
Investment Choices

In the rational expectations equilibrium of this paper, agents have private information and differing information partitions and therefore assign differing conditional distributions to asset payoffs and other economic variables relevant to their investment choices. Standard asset pricing models typically do not recognize the impact of these differing information partitions, and empirical tests based on these models thus measure asset riskiness in a way that may not be relevant to any of the agents' decisions. I show how this can lead to distorted estimates of investment risk and how it can make the equity premium appear difficult to explain.

The Bias in Two-Pass Regression Tests of Asset-Pricing Models in Presence of Idiosyncratic Errors with Cross-Sectional Dependence

2019 ◽  
Vol 22 (02) ◽  
pp. 1950012
Author(s):  
Thomas Gramespacher ◽  
Armin Bänziger
Keyword(s):  
Asset Pricing ◽  
Risk Premium ◽  
Measurement Errors ◽  
Factor Model ◽  
Pricing Models ◽  
Time Series Regression ◽  
Cross Sectional ◽  
Asset Pricing Models ◽  
Slope Estimator ◽  
Regression Tests

In two-pass regression-tests of asset-pricing models, cross-sectional correlations in the errors of the first-pass time-series regression lead to correlated measurement errors in the betas used as explanatory variables in the second-pass cross-sectional regression. The slope estimator of the second-pass regression is an estimate for the factor risk-premium and its significance is decisive for the validity of the pricing model. While it is well known that the slope estimator is downward biased in presence of uncorrelated measurement errors, we show in this paper that the correlations seen in empirical return data substantially suppress this bias. For the case of a single-factor model, we calculate the bias of the OLS slope estimator in the presence of correlated measurement errors with a first-order Taylor-approximation in the size of the errors. We show that the bias increases with the size of the errors, but decreases the more the errors are correlated. We illustrate and validate our result using a simulation approach based on empirical data commonly used in asset-pricing tests.

scholarly journals Profitability in Asset Pricing Models for Chinese Equities 1996-2016

2018 ◽  
Vol 4 (2) ◽  
pp. 118
Author(s):  
Dong Liu
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Economic Value ◽  
Equity Returns ◽  
Chinese Market ◽  
Pricing Models ◽  
Size Premium ◽  
Asset Pricing Models ◽  
Operating Leverage ◽  
Multiple Factor

<p><em>I follow Novy Marx (2011, 2013) to investigate and compare firms’ gross profit, operating leverage as predictors of returns for a cross-section of traded Chinese equities spanning from1996-2016. I use portfolio tests and Fama-MacBeth regressions, find that gross-profit-to-market-capitalization ratios significantly predict returns on sampled stocks. I also find that sorting portfolios by gross profitability and size outperforms in the Chinese market. Hence, I create a Market-Profitability-Size model that captures profitability and size premium among returns of sampled stocks. Based on Gibbons-Ross-Shanken test and economic value, I demonstrate that my enhanced model outperforms Fama-French multiple-factor model in isolating influences on equity returns.</em></p>

Multi-factor asset pricing models in emerging and developed markets

2019 ◽  
Vol 46 (3) ◽  
pp. 360-380
Author(s):  
Vaibhav Lalwani ◽  
Madhumita Chakraborty
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Five Factor Model ◽  
Superior Performance ◽  
International Studies ◽  
Pricing Models ◽  
Content Type ◽  
Developed Markets ◽  
Asset Pricing Models ◽  
Pricing Errors

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.

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