Liquidity and Expected Returns in a Multi-Factor Asset Pricing Model PDF Download

Author: Jan Schneider
Publisher:
ISBN:
Category :
Languages : en
Pages : 55

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Book Description
Several empirical studies find that illiquid firms have higher expected returns than liquid firms. I argue that this result is a puzzle that has not been resolved yet. The liquidity premium is puzzling since investors can circumvent low liquidity by trading diversified funds of illiquid firms. I develop a model that shows how a combination of cross-sectional differences in liquidity and short sale constraints generates a risk premium for illiquid firms despite the ability of investors to trade illiquid firms in large liquid baskets.

Author: Yakov Amihud
Publisher: Now Publishers Inc
ISBN: 1933019123
Category : Business & Economics
Languages : en
Pages : 109

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Book Description
Liquidity and Asset Prices reviews the literature that studies the relationship between liquidity and asset prices. The authors review the theoretical literature that predicts how liquidity affects a security's required return and discuss the empirical connection between the two. Liquidity and Asset Prices surveys the theory of liquidity-based asset pricing followed by the empirical evidence. The theory section proceeds from basic models with exogenous holding periods to those that incorporate additional elements of risk and endogenous holding periods. The empirical section reviews the evidence on the liquidity premium for stocks, bonds, and other financial assets.

Author: Shabir Ahmad Hakim
Publisher:
ISBN:
Category : Capital assets pricing model
Languages : en
Pages : 678

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Book Description
Emerging markets are associated with developing economies and are structurally different from the developed markets. They offer higher expected returns as they are experiencing higher growth rates and potential for diversifying the risk in global portfolios as they are partially integrated with the developed markets. However, the structural differences coupled with partial integration limit the capability of the asset pricing models, originally designed for the developed markets, to capture risk and return dynamics of the assets in these markets and necessitate customization of the models to the local settings. Many asset pricing studies undertaken in this direction supplement the factors in developed market models with the factors that are unique to the emerging markets. However, the models have limited scope in explaining asset returns due to limited explanatory power of the factors included. This study proposes a multifactor asset pricing model with nine explanatory factors, which include returns on the local and global market portfolios, exchange rate, and returns on six mimicking portfolios that proxy for the common sources of risks associated with size, book to market value of equity, market liquidity, leverage, quality of earnings, and asset liquidity of firms. The last three factors in the model have not been tested in the emerging markets; among these, asset liquidity is introduced as an explanatory factor in asset pricing in this study. The model is tested in seven emerging markets, namely China, India, Indonesia, Malaysia, Thailand, South Africa, and Brazil using ten-year monthly data on non-financial firms over period of January 2004 to December 2013. Generalized method of moments (GMM) is applied for data analysis and model testing. The findings of the study reveal that the local market portfolio is the most dominant factor in all the markets. It subsumes the effects of the global market portfolio and the exchange rate in most of the markets. In addition, consistent cross-country behaviour of size related factor is observed in explaining returns on small and medium portfolios, and of book to market value of equity related factor in explaining returns on high book to market value portfolios. Other factors in the model exhibit different behaviours in different markets indicating presence of idiosyncrasies in the common sources of risks that drive returns in these markets. The newly introduced asset liquidity factor has strong impact on stock returns in four markets: India, Indonesia, Malaysia and South Africa. Furthermore, the new to emerging markets factors leverage and quality of earnings have noticeable influence on stock returns in two markets each; leverage in India and Malaysia, and quality of earnings in China and Brazil. The observed behaviour of the model in the markets studied mirrors the behaviour expected of asset pricing models in emerging markets, which are partially integrated with one another and are in different stages of economic lifecycle.

Author: Yakov Amihud
Publisher: Cambridge University Press
ISBN: 1139560158
Category : Business & Economics
Languages : en
Pages : 293

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Book Description
This book presents the theory and evidence on the effect of market liquidity and liquidity risk on asset prices and on overall securities market performance. Illiquidity means incurring a high transaction cost, which includes a large price impact when trading and facing a long time to unload a large position. Liquidity risk is higher if a security becomes more illiquid when it needs to be traded in the future, which will raise trading cost. The book shows that higher illiquidity and greater liquidity risk reduce securities prices and raise the expected return that investors require as compensation. Aggregate market liquidity is linked to funding liquidity, which affects the provision of liquidity services. When these become constrained, there is a liquidity crisis which leads to downward price and liquidity spiral. Overall, the volume demonstrates the important role of liquidity in asset pricing.

Author: Khushboo Sagar
Publisher:
ISBN:
Category :
Languages : en
Pages : 20

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Book Description
Generous consideration has been pursued to the empirical testing of multi factor assets pricing models. However, literature provides mixed kind of evidences in the support of multi factor assets pricing model. This study reviews 20 research articles based on multi factor assets pricing model and examines 25 research papers based on the empirically testing of multi factor assets pricing model published during 2001 and 2018 to study the multi factor assets pricing model in the Indian context as well as foreign context. CAPM is a popular normative model used by researchers to explain the relationship between risk and expected return of a risky asset which was developed by Sharpe (1964) and Lintner (1965). This model takes only one risk factor which is the excess market portfolio return (Market premium). Because of poor performance of CAPM in explaining realized returns, the Fama and French three factor asset pricing model (1993) was developed. Fama and French (1993) documented the size effect and the value effect that were not included in the CAPM, generally known as CAPM anomalies. Mark M. Carhart (1997) developed the Carhart four factor model. It is an extension of the FF three factor model with one another factor i.e. momentum factor effect for asset pricing of stocks. In view of the limitations of the earlier three-factor model, Fama and French five-factor asset pricing model (2014) was developed. Fama and French (2014) came with profitability pattern and investment pattern in average stock return along with the market premium, size premium and value premium. This paper may be an expedient source of information to the academics, financial analyst and researchers to understand the asset pricing model.

Author: Geert Bekaert
Publisher:
ISBN:
Category : International liquidity
Languages : en
Pages : 0

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Book Description
"Given the cross-sectional and temporal variation in their liquidity, emerging equity markets provide an ideal setting to examine the impact of liquidity on expected returns. Our main liquidity measure is a transformation of the proportion of zero daily firm returns, averaged over the month. We find that our liquidity measures significantly predict future returns, whereas alternative measures such as turnover do not. Consistent with liquidity being a priced factor, unexpected liquidity shocks are positively correlated with contemporaneous return shocks and negatively correlated with shocks to the dividend yield. We consider a simple asset pricing model with liquidity and the market portfolio as risk factors and transaction costs that are proportional to liquidity. The model differentiates between integrated and segmented countries and periods. Our results suggest that local market liquidity is an important driver of expected returns in emerging markets, and that the liberalization process has not eliminated its impact"--National Bureau of Economic Research web.

Author: François-Serge Lhabitant
Publisher: John Wiley & Sons
ISBN: 0470181699
Category : Business & Economics
Languages : en
Pages : 502

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Book Description
Brings together today's best financial minds across the world to discuss the issue of liquidity in today's markets. It is often proxied by trade-based measures (such as trading volume, frequency of trading, dollar value of shares trade, etc), order based measures and price impact measures.

Author: N. Cakici
Publisher: Springer
ISBN: 1137359072
Category : Business & Economics
Languages : en
Pages : 347

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Book Description
Risk and Return in Asian Emerging Markets offers readers a firm insight into the risk and return characteristics of leading Asian emerging market participants by comparing and contrasting behavioral model variables with predictive forecasting methods.

Author: Geert Bekaert
Publisher:
ISBN:
Category :
Languages : en
Pages : 56

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Book Description
Given the cross-sectional and temporal variation in their liquidity, emerging equity markets provide an ideal setting to examine the impact of liquidity on expected returns. Our main liquidity measure is a transformation of the proportion of zero daily firm returns, averaged over the month. We find that our liquidity measures significantly predict future returns, whereas alternative measures such as turnover do not.Consistent with liquidity being a priced factor, unexpected liquidity shocks are positively correlated with contemporaneous return shocks and negatively correlated with shocks to the dividend yield. We consider a simple asset pricing model with liquidity and the market portfolio as risk factors and transaction costs that are proportional to liquidity. The model differentiates between integrated and segmented countries and time periods. Our results suggest that local market liquidity is an important driver of expected returns in emerging markets, and that the liberalization process has not fully eliminated its impact.

Author: Ying Wu
Publisher:
ISBN:
Category :
Languages : en
Pages : 249

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Book Description
The empirical research focuses on the common risk factors in stock returns and trading activities. The first essay is titled "Asset Pricing with Extreme Liquidity Risk". Defining extreme liquidity as the tails of illiquidity for all stocks, I propose a direct measure of market-wide extreme liquidity risk and find that extreme liquidity risk is priced cross-sectionally in the U.S. equity market. From 1973 through 2011, stocks in the highest quintile of extreme liquidity risk loadings earned value-weighted average returns 6.6% per year higher than stocks in the lowest quintile. The extreme liquidity risk premium is robust to common risk factors related to size, value and momentum. The premium is different from that on aggregate liquidity risk documented in Pástor and Stambaugh (2003) as well as that based on tail risk of Kelly (2011). Extreme liquidity estimates can offer a warning sign of extreme liquidity events. Predictive regressions show that extreme liquidity measure reliably outperforms aggregate liquidity measures in predicting future market returns. Finally, I incorporate the extreme liquidity risk into Acharya and Pedersen's (2005) framework and find new supporting evidence for their liquidity-adjusted capital asset pricing model. The second essay is co-authored with Prof. Andrew Karolyi. We have developed a multi-factor returns-generating model for an international setting that captures how restrictions on investability or accessibility can matter. The model works reasonably well in a wide variety of settings. More specifically, using monthly returns for over 37,000 stocks from 46 developed and emerging market countries over a two-decade period, we propose and test a multi-factor model that includes factor portfolios based on firm characteristics and that builds separate factors comprised of globally-accessible stocks, which we call "global factors," and of locally-accessible stocks, which we call "local factors." Our new "hybrid" multi-factor model with both global and local factors not only captures strong common variation in global stock returns, but also achieves low pricing errors and rejection rates using conventional testing procedures for a variety of regional and global test asset portfolios formed on size, value, and momentum. In the third essay, I examine the implications of the Lo and Wang (2000, 2006) mutual fund separation model in the cross-sectional behavior of global trading activity. It demonstrates that return-based factors work poorly around the world. On average across countries, market-wide turnover captures 37% of all systematic turnover components in individual stock trading, and two additional Fama and French (1993) factor turnovers increase the explanatory power by 23%. Similarly Lo and Wang's (2000) turnovers only capture on average 64% of all systematic turnover components. Using this multi-factor asset pricing-trading framework, a horserace is further performed to explore other factors in return by examining the turnover behavior of different factor mimicking portfolios. All the return-based factors capture at most 67% of the common variation in trading, suggesting that stock pricing and trading volume may not be compatible around the world. In cross-country analysis, the explanatory power of the returnbased factor model varies substantially across countries and markets, with better performance for European developed markets and China. Surprisingly, in North America, Japan and most emerging markets there are larger amounts of commonality in trading, mostly higher than 47 %, for reasons other than return motive.