scholarly journals Open issues in testing liquidity in frontier financial markets: The case of Serbia

2010 ◽  
Vol 55 (185) ◽  
pp. 33-62 ◽  
Author(s):  
Jelena Minovic ◽  
Bosko Zivkovic
Keyword(s):  
Liquidity Risk ◽  
Asset Returns ◽  
Price Formation ◽  
Capital Asset Pricing ◽  
Good Tool ◽  
Asset Pricing Model ◽  
Daily Data ◽  
Realistic Assessment ◽  
The Impact ◽  
Open Issues

This paper examines the impact of illiquidity and liquidity risk on expected asset returns in the Serbian stock market. For this market we estimate the conditional Liquidity-adjusted Capital Asset Pricing Model (LCAPM) of Acharya and Pedersen (2005). We use daily data for the period from 2005-2009. While the method developed is applicable in other markets this is the first paper that tests the LCAPM model in the case of Serbia. Liquidity risks are allowed to be timevarying. We find that for the Serbian market as a frontier market illiquidity and liquidity risk significantly impact price formation. For such a market the LCAPM may indeed be a good tool for realistic assessment of the expected asset returns.

scholarly journals The impact of liquidity and size premium on equity price formation in Serbia

2012 ◽  
Vol 57 (195) ◽  
pp. 43-78 ◽  
Author(s):  
Jelena Minovic ◽  
Bosko Zivkovic
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Firm Size ◽  
Market Value ◽  
Asset Returns ◽  
Factor Models ◽  
Price Formation ◽  
Good Tool ◽  
Equity Price ◽  
The Impact

The goal of this paper is to examine the impact of an overall market factor, the factor related to the firm size, the factor related to the ratio of book to market value of companies, and the factor of liquidity risk on expected asset returns in the Serbian market. For this market we estimated different factor models: Capital Asset Pricing Model (CAPM by Sharpe, 1964), Fama-French (FF) model (1992, 1993), Liquidity-augmented CAPM (LCAPM) by Liu (2006), and combination LCAPM with FF factors. We used daily data for the period from 2005 to 2009. Using a demanding methodology and complex dataset, we found that liquidity and firm size had a significant impact on equity price formation in Serbia. On the other hand, our results suggest that the factor related to the ratio of book to market value of companies does not have an important role in asset pricing in Serbia. We found that Liu?s two factor LCAPM model performs better in explaining stock returns than the standard CAPM and the Fama-French three factor model. Additionally, Liu?s LCAPM may indeed be a good tool for realistic assessment of the expected asset returns. The combination of the Fama-French model and the LCAPM could improve the understanding of equilibrium in the Serbian equity market. Even though previous papers have mostly dealt with examining different factor models of developed or emerging markets worldwide, none of them has tested factor models on the countries of former Yugoslavia. This paper is the first to test the FF model and LCAPM with FF factors in the case of Serbia and the area of ex-Yugoslavia.

scholarly journals The time-varying effects of oil prices on oil–gas stock returns of the fragile five countries

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Begüm Yurteri Kösedağlı ◽  
Gül Huyugüzel Kışla ◽  
A. Nazif Çatık
Keyword(s):  
Stock Returns ◽  
Positive Impact ◽  
Structural Break ◽  
Oil Prices ◽  
Time Varying ◽  
Asset Pricing Model ◽  
Daily Data ◽  
Structural Break Test ◽  
The Impact ◽  
Oil Gas

AbstractThis study analyzes oil price exposure of the oil–gas sector stock returns for the fragile five countries based on a multi-factor asset pricing model using daily data from 29 May 1996 to 27 January 2020. The endogenous structural break test suggests the presence of serious parameter instabilities due to fluctuations in the oil and stock markets over the period under study. Moreover, the time-varying estimates indicate that the oil–gas sectors of these countries are riskier than the overall stock market. The results further suggest that, except for Indonesia, oil prices have a positive impact on the sectoral returns of all markets, whereas the impact of the exchange rates on the oil–gas sector returns varies across time and countries.

scholarly journals Pricing Liquidity Risk with Heterogeneous Investment Horizons

2020 ◽  
pp. 1-36 ◽  
Author(s):  
Alessandro Beber ◽  
Joost Driessen ◽  
Anthony Neuberger ◽  
Patrick Tuijp
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Liquidity Risk ◽  
Asset Returns ◽  
Spillover Effects ◽  
Expected Returns ◽  
Pricing Model ◽  
Liquidity Premium ◽  
Asset Pricing Model ◽  
Illiquid Asset

We develop an asset pricing model with stochastic transaction costs and investors with heterogeneous horizons. Depending on their horizon, investors hold different sets of assets in equilibrium. This generates segmentation and spillover effects for expected returns, where the liquidity (risk) premium of illiquid assets is determined by investor horizons and the correlation between liquid and illiquid asset returns. We estimate our model for the cross-section of U.S. stock returns and find that it generates a good fit, mainly due to a combination of a substantial expected liquidity premium and segmentation effects, while the liquidity risk premium is small.

Four-moment CAPM Model: Evidence from the Indian Stock Market

2019 ◽  
Vol 18 (1_suppl) ◽  
pp. S137-S166
Author(s):  
Dheeraj Misra ◽  
Sushma Vishnani ◽  
Ankit Mehrotra
Keyword(s):  
Factor Model ◽  
Jel Classification ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Asset Pricing Model ◽  
Model Evidence ◽  
Fama And French ◽  
Capm Model ◽  
Indian Stock Market ◽  
The Impact

This study aims at analysing the impact of co-skewness and co-kurtosis on the returns of the Indian stocks by incorporating co-skewness and co-kurtosis in the traditional capital asset pricing model (CAPM) of Sharpe, in a three-factor model of Fama and French and in a four-factor model of Carhart. The results of the study show that co-skewness and co-kurtosis have significant impact on the returns of the Indian stock. However, the impact of co-skewness is higher than co-kurtosis. JEL Classification: G11, G12

scholarly journals Validity of CAPM by Using Portfolios: Evidence from Indian Capital Market

2018 ◽  
Vol 2 (2) ◽  
pp. 15-25
Author(s):  
K.M. Yaseer ◽  
K.P. Shaji
Keyword(s):  
Asset Pricing ◽  
Capital Market ◽  
Conclusive Evidence ◽  
Expected Returns ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Asset Pricing Model ◽  
Daily Data ◽  
Capm Model

This article tests the validity of Capital Asset pricing Model and compares the results of 16 periods including 14 sub periods which comprises 3 years each for the prediction of the expected returns in the Indian capital Market. The tests were conducted on portfolios having different security combinations. By using Black Jenson and Scholes methodology (1972) the study tested the validity of the model for the whole and different sub periods. The study used daily data of the BSE 100 index for the period from January 2001 to December 2010. Empirical results mostly in favor of the standard CAPM model. However, the result does not find conclusive evidence in support of CAPM  

scholarly journals Time-Varying Beta And The Subprime Financial Crisis: Evidence From U.S. Industrial Sectors

2014 ◽  
Vol 30 (5) ◽  
pp. 1465
Author(s):  
Habib Hasnaoui ◽  
Ibrahim Fatnassi
Keyword(s):  
Financial Crisis ◽  
Policy Implications ◽  
Capital Asset Pricing ◽  
Subprime Crisis ◽  
Time Varying ◽  
Capital Asset ◽  
Asset Pricing Model ◽  
Industrial Sectors ◽  
Daily Data ◽  
Portfolio Managers

<p>In the current study, we investigate the effect of the subprime financial crisis on the time-varying beta of 10 U.S. industrial sectors. We use daily data, during the period 2002 through 2014, and the bivariate BEKK-GARCH model to the conditional capital asset pricing model (CAPM) to create the time-varying betas for the 10 sectors. After controlling for local and global volatilities, the data enable us to confirm the different magnitudes of influence of the subprime crisis on the 10 industrial sectors. The results are important for investors and portfolio managers, and may have policy implications.</p>

Study of REIT ETF beta

2016 ◽  
Vol 17 (3) ◽  
pp. 347-369
Author(s):  
Stoyu I. Ivanov
Keyword(s):  
Real Estate ◽  
Factor Model ◽  
Real Estate Investment Trust ◽  
Capital Asset Pricing ◽  
Exchange Traded Funds ◽  
Financial Instrument ◽  
Content Type ◽  
Asset Pricing Model ◽  
Daily Data ◽  
Retail Investors

Purpose The aim of this study is to examine real estate investment trust exchange-traded funds (REIT ETFs) and test for the existence of the “asymmetric beta puzzle” phenomenon in these financial instruments that are relatively new and are gaining popularity. The “asymmetric beta puzzle” phenomenon is used to identify the hedging and diversification benefits of a financial instrument. “Asymmetric beta puzzle” exists when betas in declining markets are higher than betas in advancing markets. Design/methodology/approach To study 14 REIT ETFs by using monthly and daily Center for Research in Security Prices (CRSP) data. Capital asset pricing model (CAPM) and Fama–French three-factor model were used to estimate betas in REIT ETFs and those in advancing and declining markets. Both the S&P 500 and the CRSP value-weighted indices were used in the beta estimation. Two hypotheses with regard to betas in both advancing and declining markets were defined and tested to test for the existence of the “asymmetric beta puzzle” phenomenon. Findings This study confirms the presence of the “asymmetric beta puzzle” in the data of monthly REIT ETFs as documented by Goldstein and Nelling (1999) and Chatrath et al. (2000) for REITs; however, this phenomenon was not found when using daily data, but quite the opposite – REIT ETF betas are higher in advancing markets than they are in declining markets – was found. Originality/value Goldstein and Nelling (1999) and Chatrath et al. (2000) identify the phenomenon of “the asymmetric REIT-beta puzzle” in monthly REIT’s returns. This study revisits the phenomenon identified in the aforementioned authors’ studies by using daily data and a relatively new real estate financial instrument – REIT ETFs. Therefore, this paper fills a void in the literature and would benefit both institutional and retail investors in their portfolio designs.

scholarly journals BEYOND CAPM: AN INNOVATIVE FACTOR MODEL TO OPTIMIZE THE RISK AND RETURN TRADE-OFF

2013 ◽  
Vol 15 (4) ◽  
pp. 615-630 ◽  
Author(s):  
Shima Lashgari ◽  
Jurgita Antuchevičienė ◽  
Alireza Delavari ◽  
Omid Kheirkhah
Keyword(s):  
Factor Model ◽  
Asset Returns ◽  
Capital Asset Pricing ◽  
Traditional Theory ◽  
Capital Asset ◽  
Asset Return ◽  
Asset Pricing Model ◽  
Financial Factors ◽  
Multiple Factors ◽  
Explanatory Factors

Different models have tried to improve the Capital Asset Pricing Model findings, on the basis that different factors can affect asset return. This paper examines a series of explanatory factors, broader than those explained by traditional theory, to see whether they are able to more accurately explain the returns. Should the previous point be confirmed, we must consider that the risk of an asset depends on multiple factors, rather than the few that are usually identified in the literature. Even though more than 300,000 factors are examined in this paper, the results show that in recent years just 87 factors are able to fully explain the returns of 4,500 companies in the 15 European countries examined. Our analysis also shows that business and macroeconomic, rather than financial factors, are those that heavily bear on asset returns; and that factors that affect asset return, either only positively or only negatively, do not exist. However, the same factor can affect some companies positively and others negatively. Thus, since not all firms are always sensitive to the same factors, there is the possibility to further decrease risk in proportion to return, through a factor-based risk optimisation process.

scholarly journals The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas

2020 ◽  
Vol 66 (6) ◽  
pp. 2474-2494 ◽  
Author(s):  
Fabian Hollstein ◽  
Marcel Prokopczuk ◽  
Chardin Wese Simen
Keyword(s):  
Asset Pricing ◽  
High Frequency ◽  
Capital Asset Pricing Model ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Cross Sectional ◽  
Conditional Capm ◽  
Asset Pricing Model ◽  
Daily Data

When using high-frequency data, the conditional capital asset pricing model (CAPM) can explain asset-pricing anomalies. Using conditional betas based on daily data, the model works reasonably well for a recent sample period. However, it fails to explain the size anomaly as well as three out of six of the anomaly component excess returns. Using high-frequency betas, the conditional CAPM is able to explain the size, value, and momentum anomalies. We further show that high-frequency betas provide more accurate predictions of future betas than those based on daily data. This result holds for both the time-series and the cross-sectional dimensions. This paper was accepted by Karl Diether, finance.

scholarly journals Maximum Entropy Analysis of Consumption-based Capital Asset Pricing Model and Volatility

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Tae-Hwy Lee ◽  
Millie Yi Mao ◽  
Aman Ullah
Keyword(s):  
Asset Pricing ◽  
Regression Function ◽  
Asset Returns ◽  
Capital Asset Pricing ◽  
Return Volatility ◽  
Pricing Model ◽  
Capital Asset ◽  
Consumption Growth ◽  
Asset Return ◽  
Asset Pricing Model

AbstractBased on the maximum entropy (ME) method, we introduce an information theoretic approach to estimating conditional moment functions with incorporating a theoretical constraint implied from the consumption-based capital asset pricing model (CCAPM). Using the ME conditional mean/variance functions obtained from the ME density, we analyze the relationship between asset returns and consumption growth under the theoretical constraint of the CCAPM. We evaluate the predictability of asset return using consumption growth through in-sample estimation and out-of-sample prediction in the ME mean regression function. We also examine the ME variance regression function for the asset return volatility as a function of the consumption growth. Our findings suggest that incorporating the CCAPM constraint can capture the nonlinear predictability of asset returns in mean especially in tails, and that the consumption growth has an effect on reducing stock return volatility, indicating the counter-cyclical variation of stock market volatility.

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