Single-factor Capital Asset Pricing Model Research Articles

An Extended Fama-French Multi-Factor Model in Direct Real Estate Investing

Understanding risk-adjusted returns in real estate investment are crucial, but little is known about the risk-adjusted returns for direct real estate. This paper examines risk-adjusted total returns by developing an extended capital asset pricing model (CAPM) to investigate whether direct real estate returns compensate for their risk levels. Based on a panel dataset of the residential property transaction in 62 Territorial Authorities of New Zealand from 2002Q1 to 2018Q4, a direct real estate portfolio performance in the single-factor CAPM model is compared with the national housing markets stock markets and REITs markets in New Zealand before the pandemic. The results demonstrate that the direct real estate returns outperform the market returns with a significant positive alpha and beta smaller than one but positive. The alpha is further evaluated by the five-factor CAPM model, which includes the factors of liquidity risk, value risk, time risk, credit-rating risk, and currency risk. The assessment shows that most of the excess return (alpha) can be attributed to direct real estate market risks.

Asset pricing in a multifactor setting

We mathematically show that, no matter how many factors are added to the capital asset pricing model (CAPM), beta will always matter. We also show that adding more factors to a single-factor CAPM requires market risk premiums to be modeled as time varying. In addition to allowing time-varying market risk premiums, our methodology can be extended to allow for time-varying systematic risk. Our approach offers a fairly simple way to estimate expected excess returns in a multifactor setting without the use of sorting methodologies. Our critique of multifactor models is mainly due to the fact that if at least one asset in the market portfolio is sensitive to a priced factor, then the market portfolio should also be sensitive to this factor.

Predictors of Excess Return in a Green Energy Equity Portfolio: Market Risk, Market Return, Value-at-Risk and or Expected Shortfall?

The rapid growth of electric vehicles, solar roofs, and wind power suggests that the potential growth in green equity investments is an emerging trend. Accordingly, this study measured the predictors of excess equity returns in a portfolio of global green energy producers, from 2010 to 2019. Fixed-effects panel data regressions of daily returns, followed by quantile regressions, were performed. There was some support for the explanation of green equity returns by market returns and market risk (beta), as indicated by the single-factor Capital Asset Pricing Model (CAPM), and the multifactor Fama–French Three-Factor and Fama–French Five-Factor Models. The most significant predictors of green equity returns were Value-at-Risk at a 95% confidence level, and Value-at-Risk at a 99% confidence level. Expected Shortfall was another extreme risk value measure. The importance of extreme value measures suggests the presence of fat-tailed leptokurtic distributions, whereby excess returns were explained by the risk of loss given adverse conditions, primarily at 95% confidence. We conclude that the proliferation of small firms and new entrants in the renewable energy sector has led to the explanation of returns by extreme values of risk.

Measuring risk exposure in the banking sectors: evidence from Gulf Cooperation countries

PurposeUsing capital asset pricing model (CAPM) and the Z-risk index based on weekly data, this study aims to estimate yearly unsystematic, total, three systematic and insolvency risks in the Gulf Cooperation Council (GCC) countries for the period 2010–2018. The findings of CAPM show positive systematic market risk exposure in all GCC countries for all years, which support the contribution of stock markets to bank prices and returns. The mixed signs of systematic interest rate and exchange rate risks in GCC countries provide hedging opportunities, diversification strategies and regional cooperation, which help risk managers to hedge and stabilize their portfolios against interest rate and exchange rate fluctuations. Therefore, it is necessary that managers and policymakers develop a monitoring system on factors affecting bank insolvency risks to avoid bankruptcies and insolvencies.Design/methodology/approachThis study uses the three-factor CAPM and Z-risk index to measure six types of risks. The CAPM uses market information to estimate the sensitivity of banks to the fluctuations of equity markets, debt markets and foreign exchange markets. Sharpe (1964), Lintner (1965) and Treynor (1965) developed a single-factor CAPM and the coefficient of the model was called systematic market risk. The single-factor CAPM highlights stock markets as the only non-diversifiable source of systematic risks, whereas Stone (1974) and Jorion (1990) highlighted interest rate and exchange rate fluctuations as the other types of non-diversifiable systematic risks. The following functional form in equation (1) estimates five types of risks using CAPM.FindingsThe findings of CAPM show positive systematic market risk exposure in all GCC countries for all years, which support the contribution of stock markets to bank prices and returns based on CAPM theory. The mixed signs of systematic interest rate and exchange rate risks in GCC countries support hedging opportunities and diversification strategies which may help risk managers to hedge and stabilize their portfolios against the fluctuations of interest rate and exchange rate. Although, this policy may decrease the profits of banking sectors but at the same time it would stabilize the portfolios and prevent bankruptcies and big losses because of the fluctuations of interest rate. Moreover, a bank has a better chance to have more liquidity position during financial crises because of the diversifications into different regional markets.Research limitations/implicationsTherefore, this study contributes to the existing literature by using risk measurement by a three-factor CAPM and the Z-risk index as discussed further in methodology.Originality/valueIt is necessary that managers and policymakers develop a monitoring system on factors affecting bank insolvency risks to avoid bankruptcies and insolvencies.

Quality minus junk factor: A study on asset pricing dynamics in the equity market of Pakistan

This study examines the role of quality minus junk factor in explaining cross-sectional differences in stock returns for the equity market of Pakistan. A new factor quality minus junk has been added to the existing Fama & French three factor model (1993) as a fourth factor to check whether it is priced as a risk factor. The study also compares the explanatory power of the newly proposed model with the existing single-factor Capital Asset Pricing Model (CAPM) and Fama & French three factor model (1993). A high quality data set of 70 non-financial firms listed on the PSX is employed as a sample for the period 2008- 2016. Results show that quality minus junk factor is priced in the equity market of Pakistan and this newly proposed four factor model has significantly higher explanatory power than the existing three factor model.

Asset pricing in a multi-factor setting

We mathematically show that no matter how many factors are augmented to Capital Asset Pricing Model (CAPM), beta will always matter. We also show that augmenting additional factors to single-factor CAPM requires market risk premia to be modeled as time-varying. In addition to allowing a time-varying market risk premia, our methodology may be extended to allow for time-varying systemic risk. Our approach offers a fairly simple way of estimating expected excess returns in a multi-factor setting without calling upon the sorting methodologies.

ZASTOSOWANIE TRÓJCZYNNIKOWEGO MODELU FAMY-FRENCHA I CAPM DLA WYBRANYCH SPÓŁEK NOTOWANYCH NA GPW W WARSZAWIE W LATACH 2007-2017

Celem prezentowanego badania jest próba oceny czy na polskim rynku kapitałowym trójczynnikowy model Famy-Frencha lepiej opisuje stopy zwrotu spółek niż klasyczny model wyceny aktywów kapitałowych. Analizy przeprowadzono dla 30 spółek notowanych na GPW w Warszawie w latach 2007-2017, dzieląc okres badania na siedem podokresów, reprezentujących odmienną sytuację na giełdzie. W badaniu wykorzystano dane dzienne, a analizy porównawcze przeprowadzono dla trzech portfeli składających się ze spółek należących do indeksów giełdowych WIG20, mWIG40 i sWIG80.

Prospect theory and stock returns: A seven factor pricing model

The single-factor Capital Asset Pricing Model (CAPM), and its multi-factor extensions, are models that seek to explain investor's expectations for returns on risky assets. Empirical studies however, show that these factor models do not fully explain variations in expected returns. We show that a simple two factor model, based on the Peak-end rule (Fredrickson & Kahneman, 1993) from Prospect Theory (Kahneman & Tversky, 1979, 1992) explains variations in asset returns more thoroughly than the CAPM or it's extensions. Our results are derived from an extensive study on all US listed securities over the time period of 1927–2014. Based on our findings, we propose a Seven-Factor asset pricing model merging the insights of Expected Utility Theory, and Prospect Theory. Our new model explains variations in asset returns more comprehensively than the CAPM and its extensions including the recently established five factor CAPM by Fama and French (2015).

Testing a Multi-Factor Capital Asset Pricing Model in the Jordanian Stock Market

A valid and accurate capital asset pricing model (CAPM) may help investors and mutual funds managers in determining expected returns which may lead to increase their profits and community resources. The problem is that the traditional CAPM does not accurately predict the expected rate of return. A more accurate model is needed to help investors in determining the intrinsic price of the financial asset they want to sell or buy. The purpose of this study was to examine the validity of the single-factor CAPM and then develop and test a multifactor CAPM in the Jordanian stock market. The study was informed by the modern portfolio theory and specifically by the single-factor CAPM developed by Sharpe, Lintner, and Mossin. The research questions for the study examined the factors that may explain the variation in the expected rate of return on stocks in the Jordanian stock market and the relationship between the expected rate of return and factors of market return, company size, financial leverage, and operating leverage. A causal-comparative quantitative research design was employed to achieve the purpose of the study by testing the listed companies on the Amman stock exchange (ASE) for the period from 2000 to 2015. Data were collected from the ASE database and analyzed using the multiple regression model and t test. The results revealed that market return, company size, and financial leverage are not predictors of the expected rate of return while operating leverage is a predictor.

Testing a Multi-factor Capital Asset Pricing Model in the Jordanian Stock Market

A valid and accurate capital asset pricing model (CAPM) may help investors and mutual funds managers in determining expected returns which may lead to increase their profits and community resources. The problem is that the traditional CAPM does not accurately predict the expected rate of return. A more accurate model is needed to help investors in determining the intrinsic price of the financial asset they want to sell or buy. The purpose of this study was to examine the validity of the single-factor CAPM and then develop and test a multifactor CAPM in the Jordanian stock market. The study was informed by the modern portfolio theory and specifically by the single-factor CAPM developed by Sharpe, Lintner, and Mossin. The research questions for the study examined the factors that may explain the variation in the expected rate of return on stocks in the Jordanian stock market and the relationship between the expected rate of return and factors of market return, company size, financial leverage, and operating leverage. A causal-comparative quantitative research design was employed to achieve the purpose of the study by testing the listed companies on the Amman stock exchange (ASE) for the period from 2000 to 2015. Data were collected from the ASE database and analyzed using the multiple regression model and t test. The results revealed that market return, company size, and financial leverage are not predictors of the expected rate of return while operating leverage is a predictor.

Risk and returns in Shari’ah-compliant cross-section stocks: evidence from an emerging market

PurposeThis study aims to understand and document the impact of market-based – market returns and momentum – as well as firm-specific – size, book-to-market (B/M) ratio, price-to-earnings ratio (PER) and cash flow (CF) – factors on pricing of Shari’ah-compliant securities as explanation of variations in stock returns in an emerging market – Pakistan’s Karachi Stock Exchange.Design/methodology/approachInitially, the authors test Fama and French (FF) three-factor model – market risk premium, size and B/M – followed by modified FF model by including additional risk factors (PER, CF and momentum) over a 10-year period (2001-2010).FindingsOur results support superiority of FF three-factor model over single-factor capital asset pricing model. However, addition of further risk factors – including PER, CF and momentum – improves explanatory power of the model, as well as refines the selection of risk factors. In this study, CF, B/M and momentum factors remain insignificant. Traditional B/M factor in FF model is replaced by PER.Practical implicationsBased on the modified FF model, the authors propose a stock valuation model for Shari’ah-compliant securities consisting of three factors: market returns, size and earnings, which explains 76per cent variations in cross sectional stock returns.Originality/valueTo the best of the authors’ knowledge, this is the first study (which combines market-based as well as fundamental factors) on pricing of Islamic securities and identification of risk factors in an emerging market – Karachi Stock Exchange.

The Fama-French Three Factor Model and the Capital Asset Pricing Model : Evidence from the Indian Stock Market

The study aimed to provide empirical evidence on the validity of various asset pricing models for India. Specifically, it examined the behaviour of stock returns in relation to market beta, firm size (market equity), and book-to-market equity factors. I tested for the capital asset pricing model (CAPM), introduced by Sharpe (1964), Lintner (1965), Mossin (1966), and Black (1972) and then for a well-known extension to CAPM provided by Fama and French (1992), that is, the three factor model which moves away from the oversimplified relation between excess portfolio returns and excess market returns as prophesized by CAPM. I differed from the previous studies on this topic, in the Indian market, in three significant ways. First, I constructed a higher number of portfolios to minimize variability within a portfolio. Second, I considered post-2008 stock market data, so as to exclude any impact of the economic crisis. Third, I also carried out a joint test on the constant term in the portfolio regressions using the GRS test statistic. Given the time period in consideration, the empirical tests conducted support the Fama-French three-factor model in explaining the variation of stock returns better than the single factor CAPM for the Indian stock market.

Frontier Stock Markets: Local vs Global Factors

We study the returns of stocks from twenty-one frontier markets divided into the four regions of Europe, Africa, Middle East and Asia from January 2006 to June 2016. Factor mimicking portfolios based on market capitalization (SMB), book-to-market equity (HML), and momentum (WML) are constructed and reveal large and significant returns associated with value and momentum in frontier markets. Different from the developed markets, value and momentum effects are observed in both large and small market cap stocks. Empirical asset pricing models are not able to explain the observed value and momentum return patterns. Local asset pricing models, which use factors constructed from frontier market returns, and global asset pricing models, which use factors derived from developed market returns, are rejected in nearly all cases; however, the local four-factor model strongly outperforms the local single-factor capital asset pricing model (CAPM) for all regions, and the local four-factor model is found to be vastly superior to all global models. Surprisingly, there is no difference in performance between the global one-factor CAPM and the global four-factor model in explaining frontier stock market returns. This evidence strongly suggests that frontier and developed markets are segmented.

A Comparative Returns Performance Review of Islamic Equity Funds with Socially Responsible Equity Funds and the Broader Market Indices

Islamic mutual funds and socially responsible mutual funds are two similar asset classes that incorporate negative screens in their portfolio selection process to filter out stocks that fail to meet certain ethical, social, environmental, and/or religious standards. This study uses a single-factor capital asset pricing model and an adjusted sample consisting of 224 Islamic funds and 573 socially responsible funds to examine their excess risk-adjusted returns, market volatility, and systematic risk. It also gauges the market-timing abilities of the fund managers concerned in relation to both Islamic/socially responsible and conventional market indices. While there are some differences in the risk factors of Islamic funds and socially responsible funds, both are associated with lower risks and have the same market-timing ability.

Socially responsible investing returns: Evidence from South Africa, 2004-2012

A number of researchers have sought to test the theoretical prediction of Modern Portfolio Theory that asserts that Socially Responsible Investing (SRI) under-performs conventional investing. In contrast to the majority of literature, which focuses on comparing SRI funds’ performance to conventional funds, this study compares the performance of South Africa’s JSE SRI Index to the performance of local conventional market indices in the period 2004-2012. Using Sharpe ratios, the results of the study indicate that in comparison to conventional indices, the JSE SRI Index generally exhibits an inferior risk-return trade-off in both bull and bear market conditions. Furthermore, spanning tests based on the single-factor Capital Asset Pricing Model provide evidence that the JSE SRI Index is only likely to earn similar risk-adjusted returns to the Synthetic Conventional Index (a self-constructed index tracking non-overlapping conventional stocks). However, if the assumption of a non-restricted investment universe for a non-socially conscious investor is considered, there is a risk-adjusted return penalty for investing in the JSE SRI Index.

Achieving superior performance with the Morningstar’s Tortoise and Hare portfolios

Morningstar offers two stock portfolios known as the Tortoise and the Hare portfolios with the stocks included in each portfolio published and updated in the Morningstar StockInvestor monthly newsletter. This study examines the performance of these two portfolios using the Sharpe, Treynor and Sortino ratios along with the single-factor capital asset pricing model (CAPM) and the four-factor Fama–French–Carhart (FFC) model. Results examining the Tortoise and Hare portfolios indicate both portfolios outperform the market when using the Sharpe, Treynor and Sortino ratios; however, neither portfolio shows statistically significant abnormal returns when evaluated using the CAPM and FFC model. A third portfolio is created by using equal weights of the Tortoise and Hare portfolios. This combined portfolio exhibits a significant abnormal return of 3.6% per year even after accounting for systematic risk, small-firm effect, book-to-market effect and the momentum effect.

Empirical Testing of the CAPM on the Johannesburg Stock Exchange

Fama’s (1970) efficient market hypothesis (EMH) and the capital asset pricing model (CAPM) jointly ascribed to Markowitz (1952), Treynor (1961), Sharpe (1964), Lintner (1965) and Mossin (1966) remain the foundation of most finance and investment courses. This is surprising, given the sustained criticism of the model and its assumptions, and is a reflection of the elegance and parsimony of the theory over the empirical evidence.On the Johannesburg Stock Exchange (JSE), several authors have examined and noted significant inadequacies relating to the single factor CAPM, particularly with regard to the dual nature (resources versus industrial shares) which characterises this bourse. Van Rensburg and Slaney (1997) advocate the use of a two factor arbitrage pricing theory (APT) model, but show that (at least for industrial shares) additional parameters are required (van Rensburg, 2001).We revisit this ground using an improved methodology and data set over the period 31 December 1986 to 31 December 2011. We find that portfolios constructed on the basis of ranked beta exhibit a monotonic, inverse relationship to what the CAPM prescribes, for most of the time-series. The use of the single beta CAPM is therefore inappropriate in the context of asset pricing.

Empirical testing of the CAPM on the JSE

ABSTRACTFama's (1970) efficient market hypothesis (EMH) and the capital asset pricing model (CAPM), jointly ascribed to Markowitz (1952), Treynor (1961), Sharpe (1964), Lintner (1965) and Mossin (1966), remain the foundation of most finance and investment courses. This is surprising, given the sustained criticism of the model and its assumptions, and is a reflection of the elegance and parsimony of the theory over the empirical evidence.On the Johannesburg Stock Exchange (JSE), several authors have examined and noted significant inadequacies relating to the single factor CAPM, particularly with regard to the dual nature (resources versus industrial shares) which characterise this bourse. Van Rensburg and Slaney (1997) advocate the use of a two factor arbitrage pricing theory (APT) model, but show that (at least for industrial shares), additional parameters are required (Van Rensburg, 2001).We revisit this ground using an improved methodology and data set over the period 31 December 1986 to 31 December 2011. We find that portfolios constructed on the basis of ranked beta exhibit a monotonic, inverse relationship to what the CAPM prescribes for most of the time-series. The use of the single beta CAPM is therefore inappropriate.

Portfolio efficiency of APT and CAPM in two Scandinavian stock exchanges

In the paper we apply a Markowian Super Criterion for testing the Portfolio Efficiency of the Arbitrage Pricing Theory (APT) and the Capital Asset Pricing Model (CAPM). The competing Capital Market Theories are tested with Finnish and Swedish weekly price index data over the 1970–1987 time frame. We demonstrate that the APT dominates the CAPM in both countries. The multifactor APT is more powerful in predicting Finnish than Swedish stock returns, whereas the contrary holds for the single factor CAPM. A considerable deviation between the expected Pareto frontier and the best expectational frontier of the APT is observed in both markets.