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.

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.

Impact of board structure, board activities and institutional investors on the firm risk: evidence from India

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pankaj Chaudhary
Keyword(s):  
Institutional Investors ◽  
Stock Return ◽  
Stock Exchange ◽  
Independent Directors ◽  
Board Structure ◽  
Return Volatility ◽  
Method Of Moment ◽  
Content Type ◽  
Stock Return Volatility ◽  
The Impact

PurposeStock return volatility is an important aspect of financial markets which requires specific attention of researchers. This study examines the impact of board structure, board activities and institutional investors on the stock return volatility of the Indian firms.Design/methodology/approachThe author had selected the non-financial companies of the National Stock Exchange (NSE), which form the part of the NSE 500 index. Regression models had been estimated using the system generalised method of moment (GMM) framework designed by Arellano and Bover (1995) and Blundell and Bond (1998) to deal with endogeneity concerns.FindingsThe author found that the stock return volatility was affected by the institutional investors, particularly pressure-insensitive (PI) investors. Moreover, this study supported the non-linear relationship between stock return volatility and institutional investors. Unlike developed world, the author found that the independent directors were positively associated with the stock return volatility.Research limitations/implicationsIt is important for the investors and regulators to understand that the behaviour of the institutional investors depends on its class and having more independent directors will not ensure containment of the stock return volatility as suggested in previous literature reviews.Originality/valueMost of the prior studies have used simple standard deviation (SD) to compute stock return volatility. In this study, besides SD, the author used the generalised autoregressive conditional heteroskedasticity (GARCH) model to compute the stock return volatility of the firms.

Proposed Framework for Predicting Stock Return Volatility Using Neural Network: An Applied Study on the Egyptian Stock Exchange

2018 ◽  
Vol 8 (4) ◽  
pp. 424
Author(s):  
Osama EL-Ansary ◽  
Nazeer Elshahat ◽  
Maha Saad Metawea
Keyword(s):  
Neural Network ◽  
Stock Returns ◽  
Stock Return ◽  
Stock Exchange ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
The Neural Network ◽  
High Volatility ◽  
Internal And External Factors ◽  
Egyptian Stock Exchange

Purpose: the primary purpose of the study is to determine the effect of both internal and external factors on stock returns volatility using different statistical methods, applied on Egyptian stock exchange.Methodology: the researchers have compared the accuracy of (GLS Model, GARCH Model, and Neural Network) in predicting the stock return volatility to choose the most accurate one. Data was collected from the Egyptian Stock Exchange (EGYX 30) for the period (2014 to 2017) on a monthly basis.Findings: The results of the study revealed that the Neural Network Model has proven to outperform the traditional models in the prediction of stock return volatility.Originality: the study contributes to literature as it used Artificial Neural Network in two functions (Prediction of stock return volatility) and (Classification of the volatility to –high volatility and Low volatility). Also few studies concerned with stock return volatility in developing countries, especially Egypt.

Stock Returns and Volatility: Evidence from Select Emerging Markets

2009 ◽  
Vol 12 (04) ◽  
pp. 567-592 ◽  
Author(s):  
Ravinder Kumar Arora ◽  
Himadri Das ◽  
Pramod Kumar Jain
Keyword(s):  
Emerging Markets ◽  
Stock Returns ◽  
Stock Return ◽  
Leverage Effect ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Developed Markets ◽  
Return Distributions ◽  
The Mean ◽  
Return Data

This paper investigates the behavior of stock returns and volatility in 10 emerging markets and compares them with those of developed markets under different measures of frequency (daily, weekly, monthly and annual) over the period January 1, 2002 to December 31, 2006. The ratios of mean return to volatility for emerging markets are found to be higher than those of developed markets. Sample statistics for stock returns of all emerging and developed markets indicate that return distributions are not normal and return volatility shows clustering. In most cases, GARCH (1, 1) specification is adequate to describe the stock return volatility. The significant lag terms in the mean equation of GARCH specification depend on the frequency of the return data. The presence of leverage effect in volatility behavior is examined using the TAR-GARCH model and the evidence indicates that is not present across all markets under all measures of frequency. Its presence in different markets depends on the measure of frequency of stock return data.

Investor sentiment and stock return volatility: evidence from the Indian Stock Exchange

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sreenu N ◽  
Suresh Naik
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Stock Exchange ◽  
Investor Sentiment ◽  
Return Volatility ◽  
Stock Market Volatility ◽  
Content Type ◽  
Stock Return Volatility

PurposeIn any stock market, volatility is a significant factor in strengthening their asset pricing. The upsurge in volatility in the stock market can activate and bring changes in the financial risk. According to financial conventional theory, the stakeholders (investors) are selected to be balanced and variations in pertinent risk are also to be anticipated due to the outcome of the drive-in basic factors in Indian stock markets. The hypothesis shows that there are actions in systematic and unsystematic risks that are determined by volatility. It is allied to sentiment-driven in the trader movement.Design/methodology/approachThe paper used the methodology of generalized autoregressive conditional heteroskedasticity-in mean GARCH-M and exponential GARCH-M (E-GARCH-M) methods on the Indian stock market. The data have been covered from 2000 to 2019.FindingsFinally, the study suggests that due to the unfitness of the capital asset pricing model (CAPM), the selection has enhanced with sentiment is an important risk factor.Practical implicationsThe investor sentiment and stock return volatility statement are established by using the investor sentiment amalgamated stock market index built.Originality/valueThe outcome of the study shows that there is an important association between stakeholder (investor) sentiment and stock return, in case of volatility behavioural finance can significantly explain the behaviour of stock returns on the Indian Stock Exchange.

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