Does Geopolitical Risk Drive Equity Price Returns of BRIC Economies? Evidence from Quantile on Quantile Estimations

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.

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Shareholder activism and equity price reactions

Economics Letters ◽

10.1016/j.econlet.2017.09.012 ◽

2017 ◽

Vol 160 ◽

pp. 100-104

Author(s):

Timothy King ◽

Konstantinos Bozos ◽

Dimitrios Koutmos

Keyword(s):

Shareholder Activism ◽

Price Reactions ◽

Equity Price

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Modelling uncertainty of flood quantile estimations at ungauged sites by Bayesian networks

Journal of Hydroinformatics ◽

10.2166/hydro.2013.065 ◽

2013 ◽

Vol 16 (4) ◽

pp. 822-838 ◽

Cited By ~ 2

Author(s):

D. Santillán ◽

L. Mediero ◽

L. Garrote

Keyword(s):

Bayesian Networks ◽

Explanatory Variables ◽

Modelling Uncertainty ◽

Ungauged Sites ◽

Estimation Uncertainty ◽

Linear Relationships ◽

Flood Quantiles ◽

Quantile Estimations ◽

Probabilistic Nature

Prediction at ungauged sites is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. Regression models relate physiographic and climatic basin characteristics to flood quantiles, which can be estimated from observed data at gauged sites. However, some of these models assume linear relationships between variables and prediction intervals are estimated by the variance of the residuals in the estimated model. Furthermore, the effect of the uncertainties in the explanatory variables on the dependent variable cannot be assessed. This paper presents a methodology to propagate the uncertainties that arise in the process of predicting flood quantiles at ungauged basins by a regression model. In addition, Bayesian networks (BNs) were explored as a feasible tool for predicting flood quantiles at ungauged sites. Bayesian networks benefit from taking into account uncertainties thanks to their probabilistic nature. They are able to capture non-linear relationships between variables and they give a probability distribution of discharge as a result. The proposed BN model can be applied to supply the estimation uncertainty in national flood discharge mappings. The methodology was applied to a case study in the Tagus basin in Spain.

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Equity Price Discovery with Informed Private Debt

Review of Financial Studies ◽

10.1093/rfs/hhz128 ◽

2019 ◽

Vol 33 (8) ◽

pp. 3766-3803 ◽

Cited By ~ 5

Author(s):

Jawad M Addoum ◽

Justin R Murfin

Keyword(s):

Capital Structure ◽

Mutual Funds ◽

Wall Street Journal ◽

Equity Markets ◽

Wall Street ◽

Private Debt ◽

Oxford University ◽

The Wall Street Journal ◽

Equity Price ◽

Published Paper

Abstract Equity markets fail to account for the value-relevant nonpublic information enjoyed by syndicated loan participants and reflected in publicly posted loan prices. A long-short strategy that buys (sells) the equities of firms with recently appreciated (depreciated) loans earns large risk-adjusted returns, suggesting a surprising and economically important level of segmentation across the same firm’s capital structure. The information lag captured by trading strategy returns is not affected by drivers of firm-specific attention, including the publication of loan returns in the Wall Street Journal. Instead, returns to the strategy are eliminated among equities held by mutual funds also trading in syndicated loans. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

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The relevance of valuation models: insights from Palestine exchange

International Journal of Islamic and Middle Eastern Finance and Management ◽

10.1108/imefm-08-2019-0367 ◽

2020 ◽

Vol 13 (5) ◽

pp. 827-845

Author(s):

Murad Harasheh ◽

Andrea Amaduzzi ◽

Fairouz Darwish

Keyword(s):

Financial Statements ◽

Relevant Information ◽

Market Model ◽

Content Type ◽

Flow Models ◽

Volatility Models ◽

Market Beta ◽

Equity Price ◽

Relevant Factors ◽

Better Than

Purpose This paper aims to investigate the relevance of two groups of valuations models as follows: the accounting models based on the residual income (RIM) and the standard market model, on equity price, return and volatility relevance. Design/methodology/approach The models are tested on companies traded on Palestine exchange from 2009 to 2018, using panel regression analysis. Two-price and two-return models derived from RIM to compare with the market model and four volatility models. Findings The standard RIM outperformed other models in equity price modeling. The dividend discount model (DDM) outperformed the rest of the models in terms of return estimation. However, the authors find that the market model can explain equity variance better than RIM and DDM models. Practical implications For investors, market beta does not necessarily capture all relevant factors of value and traditional financial statements are still important in providing relevant information and different models are used for different values perspectives (price, return and volatility). Originality/value Previous studies focus on comparing the price and return relevance of accounting-based models (RIM and cash flow models). Three aspects differentiate this paper and contribute to its originality, namely, the uniqueness of the context, incorporating the market model into the picture along with the accounting-based models and adding Volatility dimensions of relevance.

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