scholarly journals The Impact of External Factors on Stock Return Volatility in the European Banking Sector

2021 ◽  
Vol 4/2021 (94) ◽  
pp. 185-199
Author(s):  
Katarzyna Niewińska ◽  
Keyword(s):  
Capital Market ◽  
Stock Return ◽  
Banking Sector ◽  
Robust Estimator ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Valuable Addition ◽  
Body Of Knowledge ◽  
The Impact ◽  
The Capital Market

Purpose: The main aim of the paper is to examine the impact of external determinants on the banking stock return volatility to evaluate it in terms of the stock market capitalization. Design/methodology/approach: The research was conducted on 182 banks from 26 countries. The sample selected for the study includes all European banks listed on the stock exchange. Quarterly data from the period between 2004 and 2016 was used; it was collected and compiled over a period of 2 years. The research method applied was the panel data model with fixed effects (with or without a robust estimator) and random effects. Findings: Determinants that have a major and statistically significant impact on the analyzed dependent variables are: the unemployment rate, the real interest rate, the beta in Sharpe’s Single-Index Model and the implied volatility of the S&P 500 index and the EURO STOXX50 index. Research limitations/implications: Insights about the strength and direction of influence of these variables on stock return volatility are a valuable addition to the existing body of knowledge that investors resort to when making decisions relating to the capital market. Limitations: The main limitation of this study lies in the fact that the results of the analysis apply solely to the banking sector. Originality/value: Insights about the strength and direction of influence of these variables on stock return volatility are a valuable addition to the existing body of knowledge that investors resort to when making decisions relating to the capital market.

scholarly journals Does Sustainability Engagement Affect Stock Return Volatility? Evidence from the Chinese Financial Market

2018 ◽  
Vol 10 (10) ◽  
pp. 3361 ◽  
Author(s):  
Junru Zhang ◽  
Hadrian Djajadikerta ◽  
Zhaoyong Zhang
Keyword(s):  
Stock Returns ◽  
Portfolio Management ◽  
Stock Return ◽  
Return Volatility ◽  
Chinese Stock Market ◽  
Stock Return Volatility ◽  
News Release ◽  
Volatility Persistence ◽  
Google Search ◽  
The Impact

This paper examines the impact of firms’ sustainability engagement on their stock returns and volatility by employing the EGARCH and FIGARCH models using data from the major financial firms listed in the Chinese stock market. We find evidence of a positive association between sustainability engagement and stock returns, suggesting firms’ sustainability news release in favour of the market. Although volatility persistence can largely be explained by news flows, the results show that sustainability news release has the significant and largest drop in volatility persistence, followed by popularity in Google search engine and the general news. Sustainability news release is found to affect positively stock return volatility. We also find evidence that market expectation can be driven by the dominant social paradigm when sustainability is included. These findings have important implications for market efficiency and effective portfolio management decisions.

Capital Gains Taxes and Stock Return Volatility

2013 ◽  
Vol 35 (2) ◽  
pp. 1-31 ◽  
Author(s):  
Zhonglan Dai ◽  
Douglas A. Shackelford ◽  
Harold H. Zhang
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Cash Flows ◽  
Capital Gains ◽  
Return Volatility ◽  
Capital Gains Tax ◽  
Tax Rate ◽  
Stock Return Volatility ◽  
Capital Gains Taxes ◽  
The Impact

ABSTRACT This paper presents an empirical investigation of the impact of capital gains taxes on stock return volatility. We predict that the more stock returns are subject to capital gains taxation, the greater the increase in return volatility following a capital gains tax rate cut due to reduced risk-sharing in firms' cash flows between shareholders and the government. Consistent with this prediction, we find larger increases in the return volatility for more appreciated stocks than for less appreciated stocks and for non-dividend-paying stocks than for dividend-paying stocks after both 1978 and 1997 capital gains tax rate reductions. The findings imply that capital gains taxes convey a heretofore overlooked benefit of lower stock return volatility.

scholarly journals THE VOLATILITY TRANSMISSION OF MAIN GLOBAL STOCK'S RETURN TO INDONESIA

2017 ◽  
Vol 20 (2) ◽  
pp. 229-256
Author(s):  
Linda Karlina Sari ◽  
Noer Azam Achsani ◽  
Bagus Sartono
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Stock Return ◽  
Global Financial Crisis ◽  
Symmetric Model ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Volatility Transmission ◽  
The Impact

Stock return volatility is a very interesting phenomenon because of its impact on global financial markets. For instance, an adverse shocks in one country’s market can be transmitted to other countries’ market through a particular mechanism of transmission, causing the related markets to experience financial instability as well (Liu et al., 1998). This paper aims to determine the best model to describe the volatility of stock returns, to identify asymmetric effect of such volatility, as well as to explore the transmission of stocks return volatilities in seven countries to Indonesia’s stock market over the period 1990-2016, on a daily basis. Modeling of stock return volatility uses symmetric and asymmetric GARCH, while analysis of stock return volatility transmission utilizes Vector Autoregressive system. This study found that the asymmetric model of GARCH, resulted from fitting the right model for all seven stock markets, provides a better estimation in portraying stock return volatility than symmetric model. Moreover, the model can reveal the presence of asymmetric effects on those seven stock markets. Other finding shows that Hong Kong and Singapore markets play dominant roles in influencing volatility return of Indonesia’s stock market. In addition, the degree of interdependence between Indonesia’s and foreign stock market increased substantially after the 2007 global financial crisis, as indicated by a drastic increase of the impact of stock return volatilities in the US and UK market on the volatility of Indonesia’s stock return.

THE IMPACT OF STOCK RETURNS VOLATILITY ON CREDIT DEFAULT SWAP RATES: A COPULA STUDY

2005 ◽  
Vol 08 (08) ◽  
pp. 1135-1155 ◽  
Author(s):  
FATHI ABID ◽  
NADER NAIFAR
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Credit Default Swap ◽  
Archimedean Copula ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Credit Default ◽  
Default Swap ◽  
The Impact ◽  
Swap Rates

The aim of this paper is to study the impact of stock returns volatility of reference entities on credit default swap rates using a new dataset from the Japanese market. The majority of empirical research suggests the inadequacy of multinormal distribution and then the failure of methods based on correlation for measuring the structure of dependency. Using a copula approach, we can model the different relationships that can exist in different ranges of behavior. We study the bivariate distributions of credit default swap rates and the measure of stock return volatility estimated with GARCH (1,1) and focus on one parameter Archimedean copula. Starting from the empirical rank correlation statistics (Kendall's tau and Spearman's rho), we estimate the parameter values of each copula function presented in our study. Then, we choose the appropriate Archimedean copula that better fit to our data. We emphasize the finding that pairs with higher rating present a weaker dependence coefficient and then, the impact of stock return volatility on credit default swap rates is higher for the lowest rating class.

Impact of Weather on Return and Volatility: Evidence from Indian Stock Market

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Vijayakumar N. ◽  
Dharani M. ◽  
Muruganandan S.
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Return Volatility ◽  
Weather Factors ◽  
Stock Return Volatility ◽  
Daily Data ◽  
Indian Stock Market ◽  
The Impact

This study examines the impact of Weather factors on return and volatility of the Indian stock market. The study uses the daily data of top four metros and tests its impact on the return and volatility of S&P CNX Nifty index from January 2008 to December 2013. This study applies GARCH (1, 1) model and find that the stock returns are influenced by temperature in Chennai and the stock return volatility influenced by the temperature in Mumbai, Delhi and Kolkata.

Macroeconomic Sensitivity, Risk-Return Trade-Off and Volatility Dynamics Evidence From Developed and Developing Markets

2019 ◽  
Vol 6 (1) ◽  
pp. 1-16
Author(s):  
Faisal Khan ◽  
Hashim Khan ◽  
Saif Ur-Rehman Khan ◽  
Muhammad Jumaa ◽  
Sharif Ullah Jan
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Stock Exchange ◽  
Three Dimensions ◽  
Leverage Effect ◽  
Return Volatility ◽  
Macroeconomic Factors ◽  
Stock Return Volatility ◽  
Risk Return ◽  
The Impact

This study aims to examine the impact of macroeconomic factors on the stock return volatility along with the pricing of risk, and asymmetry and leverage effect on a comparative basis for the USA and UAE markets. Further, these three dimensions are also investigated with regard to various firm's features (such as firm's size and age). The daily data for the period 4th January 2010 to 29th December 2017 of firm stock returns from the New York Stock Exchange (NYSE), the Abu Dhabi Securities Exchange (ADSE), and the Dubai Financial Market (DFM) is considered and three time-series models were applied. The results from GARCH (1. 1) indicated that all the economic factors have significant impact on the stock return volatility in both the markets. Similarly, the study also found evidence of asymmetry & leverage effect using EGARCH in the NYSE (for all firms) and the UAE (partially). Finally, for a majority of the firms, a positive risk-return relationship is found in the UAE and a negative risk-return relationship is found in the NYSE using GARCH-in the mean. Interestingly, these results in context of both markets were different with respect to various firm features such as firm size and age. In light of these results, it is concluded that both the markets have different dynamics with regard to all three dimensions. Hence, the investors have a clear opportunity to diversify their risk and investments across developed and emerging markets.

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