Asymmetric Linkages between BRICS Stock Returns and Country Risk Ratings: Evidence from Dynamic Panel Threshold Models

2015 ◽  
Vol 24 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Walid Mensi ◽  
Shawkat Hammoudeh ◽  
Seong-Min Yoon ◽  
Duc Khuong Nguyen
Keyword(s):  
Stock Returns ◽  
Country Risk ◽  
Threshold Models ◽  
Dynamic Panel

scholarly journals Dynamic Quantile Panel Data Analysis of Stock Returns Predictability

2016 ◽  
Vol 8 (2) ◽  
pp. 115 ◽  
Author(s):  
Bülent Guloglu ◽  
Sinem Guler Kangalli Uyar ◽  
Umut Uyar
Keyword(s):  
Panel Data ◽  
Quantile Regression ◽  
Stock Returns ◽  
Conditional Distribution ◽  
Extreme Values ◽  
Dynamic Panel Data ◽  
Regression Technique ◽  
Heterogeneous Structure ◽  
Dynamic Panel ◽  
Different Parts

<p>This paper analyses the effect of financial ratios on stock returns using quantile regression for dynamic panel data with fixed effects. Eighty three firms of manufacturing industry, which were traded on the Borsa Istanbul for 2000-2014 period, are covered in the study. The most of financial variables have heterogeneous structure so they generally include extreme values. Thus, panel quantile regression technique, suggested by Koenker (2004), is used. Since the technique yields robust estimator in the case of extreme values the Gaussian estimators will be biased and not efficient. The sensitivity of relationship, on the other hand, can be studied for different parts of the stock returns’ conditional distribution by using quantile regression technique. However, because of that the lagged of dependent variable is used as an explanatory variable in dynamic panel models, fixed effect estimators will be biased. Thereby, in this study the instrumental variable approach suggested by Chernozhukov and Hansen (2006) is used to produce unbiased and consistent estimators.</p>The results show that the stock returns respond to the changes on the financial leverage ratio, the dividend yield, the market-to-book value ratio, financial beta and the total active profitability variables differently for the different parts of the stock returns’ conditional distribution. They also indicate that, at high quantiles, return fluctuations in the current period will be more effective for investors’ transaction attitudes on stocks for the next period.

COVID-19-induced Returns, Attention, Sentiments and Social Isolation: Evidence from Dynamic Panel Model

2021 ◽  
pp. 097215092199617
Author(s):  
Farzan Yahya ◽  
Zhang Shaohua ◽  
Ulfat Abbas ◽  
Muhammad Waqas
Keyword(s):  
Stock Returns ◽  
Social Isolation ◽  
Stock Exchange ◽  
Investor Sentiment ◽  
Good News ◽  
Dynamic Panel ◽  
Investor Attention ◽  
Dynamic Panel Model ◽  
Panel Model ◽  
Investor Sentiments

This article develops a dynamic panel model to examine the association among coronavirus outbreak, investor attention, social isolation, investor sentiments and stock returns in the German Stock exchange. The results of the two-step GMM estimator show a significant effect of coronavirus disease 2019 (COVID-19) cases on the Frankfurt Stock Exchange after controlling for calendar anomalies, meteorological conditions, country-specific factors and oil returns. Results also show that a higher level of stock returns during social isolation (lockdown period) is explained by investor attention to buy underpriced stocks. Thus, temporary social isolation enhances an investor’s ability to make better investment decisions. Investor sentiment indicators (momentum and liquidity) are also positively associated with the stock return and partially mediate the COVID-returns link, but they have no direct effect on investor attention. The stock market attracts investor attention under good news shocks (recovered cases) when investor sentiments are optimistic. Our results are robust across the transparency level of firms and their size.

scholarly journals Forecasted E/P Ratio and ROE: Shanghai Stock Exchange (SSE), China

SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110231
Author(s):  
Muhammad Usman Arshad
Keyword(s):  
Stock Returns ◽  
Dynamic Models ◽  
Stock Exchange ◽  
Price Ratio ◽  
Chinese Market ◽  
Dynamic Panel ◽  
Panel Data Estimation ◽  
Research Findings ◽  
Log Linear ◽  
Data Estimation

This study explores the influence of forecasted earnings to price ratio (E/P) and ROE to explain the part of the variation in the Shanghai Stock Exchange (SSE) returns. The study analyzed the explanatory capacity of fundamental, risk, and combined valuation approaches variables on comparative mode between static and dynamic models with the induction of un-balanced panel data estimation. A linear dynamic panel technique is being undertaken to forecast the variables. The research findings indicate that the forecasted E/P ratio and ROE significantly explain the variation in SSE stock return and remain highly statistically significant after incorporating risk proxy variables. Moreover, the author also confirms the existence of size, momentum, liquidity, and dividend yield in the Shanghai Stock Exchange. The study introduces the fundamental valuation approach to the Chinese market based on its unique features and designs a log-linear model, which comprises forecasted E/P and ROE in addition to current E/P as an estimator for future stock returns. The incorporation of Driscoll and Kraay standard errors (DKSE) and Panel Corrected standard error (PCSE) under static while difference and system GMM under the scope of dynamic panel estimation is considered to be another contribution of the study.

scholarly journals Country Risk Ratings and Stock Market Returns in Brazil, Russia, India, and China (BRICS) Countries: A Nonlinear Dynamic Approach

Risks ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 94 ◽  
Author(s):  
Adnen Ben Nasr ◽  
Juncal Cunado ◽  
Rıza Demirer ◽  
Rangan Gupta
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Commodity Price ◽  
Global Market ◽  
Country Risk ◽  
Market Returns ◽  
Stock Market Returns ◽  
Brics Countries ◽  
Long Run ◽  
India And China

This study examines the linkages between Brazil, Russia, India, and China (BRICS) stock market returns, country risk ratings, and international factors via Non-linear Auto Regressive Distributed Lags models (NARDL) that allow for testing the asymmetric effects of changes in country risk ratings on stock market returns. We show that BRICS countries exhibit quite a degree of heterogeneity in the interaction of their stock market returns with country-specific political, financial, and economic risk ratings. Positive and negative rating changes in some BRICS countries are found to have significant implications for both local stock market returns, as well as commodity price dynamics. While the commodity market acts as a catalyst for these emerging stock markets in the long-run, we also observe that negative changes in the country risk ratings generally command a higher impact on stock returns, implying the greater impact of bad news on market dynamics. Our findings suggest that not all BRICS nations are the same in terms of how they react to ratings changes and how they interact with global market variables.

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