scholarly journals Comparison of News Impacts on Sectoral Stock Returns during the COVID-19 Pandemic in Turkey

2021 ◽  
Vol 7 (2) ◽  
pp. 35-46
Author(s):  
Metin Tetik
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Garch Models ◽  
Sample Period ◽  
Services Sector ◽  
Finance Industry ◽  
Return Data

This study examines how the volatility of the sectoral stock returns within Borsa İstanbul are affected during the COVID-19 pandemic. The analysis uses daily stock return data for four main sector indices: services, finance, industry, and technology. The sample period of the study covers 03.03.2015–11.03.2021, and 12.03.2020-03.04.2021 is separately analyzed for the COVID-19 period. When E-GARCH models and news impact curves are analyzed, it is found that the services sector stock returns volatility differs from other sectoral stock returns.

scholarly journals VOLATILITY IN STOCK RETURN SERIES OF VIETNAM STOCK MARKET

2011 ◽  
Vol 14 (3) ◽  
pp. 5-21
Author(s):  
Vinh Xuan Vo ◽  
Ngan Thi Kim Nguyen
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Structural Breaks ◽  
Garch Models ◽  
Financial Policies ◽  
Long Span ◽  
Return Variance ◽  
Daily Stock Returns ◽  
Icss Algorithm

This paper studies the features of the stock return volatility using GARCH models and the presence of structural breaks in return variance of VNIndex in the Vietnam stock market by using the iterated cumulative sums of squares (ICSS) algorithm. Using a long-span data, GARCH and GARCH in mean (GARCH-M) models seems to be effective in describing daily stock returns’ features. About structural breaks, when applying ICSS to standardized residuals filtered from GARCH (1, 1) model, the number of volatility shifts significantly decreases in comparison with the raw return series. Events corresponding to those breaks and altering the volatility pattern of stock return are found to be country-specific. Not any shifts are found during global crisis period. Further evidence also reveals that when sudden shifts are taken into account in the GARCH models, volatility persistence remarkably reduces and that the conditional variance of stock return is much affected by past trend of observed shocks and variance. Our results have important implications regarding advising investors on decisions concerning pricing equity, portfolio investment and management, hedging and forecasting. Moreover, it is also helpful for policy-makers in making and promulgating the financial policies.

scholarly journals Stock Return Volatility And Trading Volume Relationships Captured With Stable Paretian GARCH And Threshold GARCH Models

2012 ◽  
Vol 11 (1) ◽  
pp. 47 ◽  
Author(s):  
Atsuyuki Naka ◽  
Ece Oral
Keyword(s):  
Stock Returns ◽  
Trading Volume ◽  
Stock Return ◽  
Goodness Of Fit ◽  
Garch Models ◽  
Return Volatility ◽  
Font Size ◽  
Gaussian Models ◽  
Stock Return Volatility ◽  
Dow Jones Industrial Average

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify;" class="MsoNormal"><span style="font-size: 10pt; mso-fareast-language: JA;"><span style="font-family: Times New Roman;">This paper examines the volatility of Dow Jones Industrial Average stock returns and the trading volume by employing stable Paretian GARCH and Threshold GARCH (TGARCH) models. Our results indicate that the trading volume significantly contributes to the volatility of stock returns. Additionally, strong leverage effects exist with negative shocks having a larger impact on volatility than positive shocks. The likelihood ratio tests and goodness of fit support the use of stable Paretian GARCH and TGARCH models over Gaussian models.</span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

Analysis of stock returns of main European service and tourism companies

2021 ◽  
pp. 135481662199298
Author(s):  
Francisco Jareño ◽  
Ana Escribano ◽  
M Pilar Torres
Keyword(s):  
Interest Rates ◽  
Stock Returns ◽  
Factor Model ◽  
Five Factor Model ◽  
Explanatory Power ◽  
Sample Period ◽  
Services Sector ◽  
Explanatory Factors ◽  
Nominal Interest Rates ◽  
Fama And French

This research explores the sensitivity of the returns of some selected European companies to changes in the explanatory factors proposed during the sample period between January 2000 and December 2019. We focus on listed companies in the tourism and services sector and estimate an extension of the Fama and French five-factor model (2015) by applying the quantile regression approach. Specifically, this study starts from the Fama and French risk factors and adds the nominal interest rates, a momentum and momentum reversal factors and a traded liquidity factor. For robustness, this research divides the whole sample period into three sub-periods: pre-crisis, crisis and post-crisis. In line with the previous literature, the explanatory power of this factor model shows a U-shape, which is compatible with the highest R2 coefficients in the extreme quantiles, as well as in extreme stages of the economy, that is, in the bullish and bearish market states.

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.

scholarly journals Modeling Stock Return Data using Asymmetric Volatility Models : A Performance Comparison based on the Akaike Information Criterion and Schwarz Criterion

2019 ◽  
Vol 1 (1) ◽  
pp. 40
Author(s):  
E Setiawan ◽  
N Herawati ◽  
K Nisa
Keyword(s):  
Stock Return ◽  
Information Criterion ◽  
Performance Comparison ◽  
Garch Models ◽  
Forecasting Model ◽  
Asymmetric Volatility ◽  
Volatility Models ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Schwarz Criterion ◽  
Return Data

The Generalized Autoregressive Conditional Heteroscedasticity (GARCH) modelhas been widely used in time series forecasting especially with asymmetricvolatility data. As the generalization of autoregressive conditionalheteroscedasticity model, GARCH is known to be more flexible to lag structures.Some enhancements of GARCH models were introduced in literatures, among themare Exponential GARCH (EGARCH), Threshold GARCH (TGARCH) andAsymmetric Power GARCH (APGARCH) models. This paper aims to compare theperformance of the three enhancements of the asymmetric volatility models bymeans of applying the three models to estimate real daily stock return volatilitydata. The presence of leverage effects in empirical series is investigated. Based onthe value of Akaike information and Schwarz criterions, the result showed that thebest forecasting model for daily stock return data is the APARCH model.Keywords: Volatility, GARCH, TGARCH, EGARCH, APARCH, AIC and SC.

Learning for infinitely divisible GARCH models in option pricing

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Fumin Zhu ◽  
Michele Leonardo Bianchi ◽  
Young Shin Kim ◽  
Frank J. Fabozzi ◽  
Hengyu Wu
Keyword(s):  
Option Pricing ◽  
Stock Returns ◽  
Bayesian Learning ◽  
Space Structure ◽  
Estimation Methods ◽  
Garch Models ◽  
Learning Approaches ◽  
Infinitely Divisible ◽  
Asymmetric Garch ◽  
Non Gaussian

AbstractThis paper studies the option valuation problem of non-Gaussian and asymmetric GARCH models from a state-space structure perspective. Assuming innovations following an infinitely divisible distribution, we apply different estimation methods including filtering and learning approaches. We then investigate the performance in pricing S&P 500 index short-term options after obtaining a proper change of measure. We find that the sequential Bayesian learning approach (SBLA) significantly and robustly decreases the option pricing errors. Our theoretical and empirical findings also suggest that, when stock returns are non-Gaussian distributed, their innovations under the risk-neutral measure may present more non-normality, exhibit higher volatility, and have a stronger leverage effect than under the physical measure.

scholarly journals Financial performance of shipping firms that increase LNG carriers and the support of eco-innovation

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Kian-Guan Lim ◽  
Michelle Lim
Keyword(s):  
Natural Gas ◽  
Financial Performance ◽  
Stock Returns ◽  
Stock Return ◽  
Fossil Fuel ◽  
Operational Efficiency ◽  
Liquefied Natural Gas ◽  
Marine Fuel ◽  
Financial Benefits ◽  
Firm Profitability

AbstractThe technology to liquefy natural gas for transport to countries worldwide and the increasing use of natural gas as a cleaner fossil fuel for industry and household meant that the supply of liquified natural gas (LNG) worldwide is a profitable trend. Shipping companies can strategically choose to diversify into LNG fleet to grasp this trend. By supplying more LNG shipping capacities, the greater availability of LNG worldwide, as a source of marine fuel and as a source of cleaner energy in replacing coal and oil, is supporting eco-innovation. In this paper, we investigate three economic and financial benefits to a shipping firm that diversified into liquefied natural gas (LNG) shipping, namely firm profitability performance, firm efficiency, and stock return performance. We also investigate if there is an early mover advantage in doing so. Our empirical findings indicate that fleet diversification into LNG carriers resulted in higher profitability and better operational efficiency. For the listed shipping firms, their stock returns increased with diversified exposures to the LNG business. There is some evidence of higher profitability in the early mover advantage. Firms that originated in LNG business also benefited when there was diversification into the non-LNG business.

The Effect of Profitability, Asset Structure, Company Size on Stock Returns with Corporate Governance as Moderating Variables in Manufacturing Companies on the IDX in 2009-2018

2021 ◽  
Vol 8 (8) ◽  
pp. 55-63
Author(s):  
Deby Yurika Lasmarito Siahaan ◽  
Rina Br Bukit ◽  
Tarmizi .
Keyword(s):  
Corporate Governance ◽  
Stock Returns ◽  
Firm Size ◽  
Significant Influence ◽  
Stock Return ◽  
Company Size ◽  
Research Model ◽  
Manufacturing Companies ◽  
Research Results ◽  
Moderating Variables

The research objective was to examine and analyze whether Profitability, Asset Structure, Firm Size simultaneously and partially influenced Stock Returns in Manufacturing Companies. In addition, this study also tries to prove whether Corporate Governance can be used as a moderator in the research model. The research results showed that simultaneously Profitability, Asset Structure, Firm Size significantly influenced Stock Returns. Partially, profitability has a positive and significant influence on Stock Returns. Asset Structure has a positive and significant influence on Stock Returns, and Company size has a positive and insignificant influence on Stock Returns. The variable of Corporate Governance can moderate the influence of Asset Structure on Stock Returns. However, Corporate Governance will not be able to moderate the influence of Profitability on Stock Returns. Keywords: Profitability, Asset Structure, Firm Size, Stock Return, and Corporate Governance.

PENGARUH CURRENT RATIO, RETURN ON EQUITY DAN EARNING PER SHARE TERHADAP RETURN SAHAM PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2010 – 2019

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Susi Lusiana
Keyword(s):  
Data Collection ◽  
Stock Returns ◽  
Stock Return ◽  
Stock Exchange ◽  
Financial Statements ◽  
Financial Ratios ◽  
Manufacturing Companies ◽  
Current Ratio ◽  
Return On Equity ◽  
Earnings Per Share

The study of this research is to determine the effect of returning shares in manufacturing companies. This study uses the financial ratios contained in the company's financial statements. The financial ratios used in this study are the current ratio, return on equity, and earnings per share to stock returns in manufacturing companies listed on the Indonesian stock exchange in 2010-2019. This type of research used in this research is quantitative and the analytical method used is purposive sampling using SPSS 21 as many 10 manufacturing companies in the food, beverage, textile, rubber goods (tires), fisheries, and agriculture sectors. Data collection techniques are used by retrieving data through the website www.idx.co.id. The results showed that Current Ratio (CR) has a positive and significant effect on Stock Returns, Return On Equity (ROE) has a positive and significant effect on Stock Returns, and Earning Per Share (EPS) has a negative and significant effect on Stock Return.

scholarly journals Clarifying the Response of Gold Return to Financial Indicators: An Empirical Comparative Analysis Using Ordinary Least Squares, Robust and Quantile Regressions

2019 ◽  
Vol 12 (1) ◽  
pp. 33 ◽  
Author(s):  
Takashi Miyazaki
Keyword(s):  
Stock Returns ◽  
Structural Changes ◽  
Global Financial Crisis ◽  
Ordinary Least Squares ◽  
Stock Market Volatility ◽  
Financial Indicators ◽  
Sample Period ◽  
Flight To Quality ◽  
Crude Oil Prices ◽  
The Global Financial Crisis

In this study, I apply a quantile regression model to investigate how gold returns respond to changes in various financial indicators. The model quantifies the asymmetric response of gold return in the tails of the distribution based on weekly data over the past 30 years. I conducted a statistical test that allows for multiple structural changes and find that the relationship between gold return and some key financial indicators changed three times throughout the sample period. According to my empirical analysis of the whole sample period, I find that: (1) the gold return rises significantly if stock returns fall sharply; (2) it rises as the stock market volatility increases; (3) it also rises when general financial market conditions tighten; (4) gold and crude oil prices generally move toward the same direction; and (5) gold and the US dollar have an almost constant negative correlation. Looking at each sample period, (1) and (2) are remarkable in the period covering the global financial crisis (GFC), suggesting that investors divested from stocks as a risky asset. On the other hand, (3) is a phenomenon observed during the sample period after the GFC, suggesting that it reflects investors’ behavior of flight to quality.

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