scholarly journals Effects of Daylight Savings Time Changes on Stock Market Volatility

2010 ◽  
Vol 106 (2) ◽  
pp. 632-640 ◽  
Author(s):  
M. Hakan Berument ◽  
Nukhet Dogan ◽  
Bahar Onar
Keyword(s):  
United States ◽  
Stock Market ◽  
Stock Returns ◽  
Conditional Variance ◽  
Time Effect ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Stock Volatility ◽  
Time Effects ◽  
Time Changes

The presence of daylight savings time effects on stock returns and on stock volatility was investigated using an EGARCH specification to model the conditional variance. The evidence gathered from the major United States stock markets for the period between 1967 and 2007 did not support the existence of the daylight savings time effect on stock returns or on volatility. Returns on the first business day following daylight savings time changes were not lower nor was the volatility higher, as would be expected if there were an effect.

Effects of Daylight-Saving Time Changes on Stock Market Returns and Stock Market Volatility: Rebuttal

2013 ◽  
Vol 112 (1) ◽  
pp. 89-99 ◽  
Author(s):  
Mark J. Kamstra ◽  
Lisa A. Kramer ◽  
Maurice D. Levi
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Market Returns ◽  
Stock Market Returns ◽  
Daylight Saving Time ◽  
Daylight Saving ◽  
Time Changes ◽  
Saving Effect

In a 2011 reply to our 2010 comment in this journal, Berument and Dogen maintained their challenge to the existence of the negative daylight-saving effect in stock returns reported by Kamstra, Kramer, and Levi in 2000. Unfortunately, in their reply, Berument and Dogen ignored all of the points raised in the comment, failing even to cite the Kamstra, et al. comment. Berument and Dogen continued to use inappropriate estimation techniques, over-parameterized models, and low-power tests and perhaps most surprisingly even failed to replicate results they themselves reported in their previous paper, written by Berument, Dogen, and Onar in 2010. The findings reported by Berument and Dogen, as well as by Berument, Dogen, and Onar, are neither well-supported nor well-reasoned. We maintain our original objections to their analysis, highlight new serious empirical and theoretical problems, and emphasize that there remains statistically significant evidence of an economically large negative daylight-saving effect in U.S. stock returns. The issues raised in this rebuttal extend beyond the daylight-saving effect itself, touching on methodological points that arise more generally when deciding how to model financial returns data.

scholarly journals Information-Theoretic Measures and Modeling Stock Market Volatility: A Comparative Approach

Risks ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 89
Author(s):  
Muhammad Sheraz ◽  
Imran Nasir
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Approximate Entropy ◽  
Market Volatility ◽  
Comparative Approach ◽  
Stock Market Volatility ◽  
Information Theoretic ◽  
Information Theoretic Measures ◽  
Garch Modeling

The volatility analysis of stock returns data is paramount in financial studies. We investigate the dynamics of volatility and randomness of the Pakistan Stock Exchange (PSX-100) and obtain insights into the behavior of investors during and before the coronavirus disease (COVID-19 pandemic). The paper aims to present the volatility estimations and quantification of the randomness of PSX-100. The methodology includes two approaches: (i) the implementation of EGARCH, GJR-GARCH, and TGARCH models to estimate the volatilities; and (ii) analysis of randomness in volatilities series, return series, and PSX-100 closing prices for pre-pandemic and pandemic period by using Shannon’s, Tsallis, approximate and sample entropies. Volatility modeling suggests the existence of the leverage effect in both the underlying periods of study. The results obtained using GARCH modeling reveal that the stock market volatility has increased during the pandemic period. However, information-theoretic results based on Shannon and Tsallis entropies do not suggest notable variation in the estimated volatilities series and closing prices. We have examined regularity and randomness based on the approximate entropy and sample entropy. We have noticed both entropies are extremely sensitive to choices of the parameters.

scholarly journals Capital Market Response to COVID-19 Pandemic – A Systematic Review on Stock Volatility and Performance

2021 ◽  
pp. 27-49
Author(s):  
Janga Bahadur Hamal ◽  
Rishi Raj Gautam
Keyword(s):  
Stock Market ◽  
Investor Sentiment ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Stock Volatility ◽  
Government Response ◽  
Stock Market Performance ◽  
Policy Measures ◽  
And Performance ◽  
The Impact

This paper aims to identify the impact of the COVID-19 pandemic on stock market volatility and market return as well as the impact of government response to the COVID-19 pandemic on stock market performance. To analyze the same, the paper has adopted Systematic Literature Review (SLR) approach and conducted a review of 40 journal articles published between between2020 to mid-2021. The paper identified that the short-term impact of the COVID-19 outbreak and government policy measures had a significant and adverse impact on stock market volatility, return and overall performance. In the longer term, the stock markets slowly started to stabilize and revive. This effect on the stock market was also attributed to investor sentiment and thus, in the later stages, targeted government response had a positive effect on boosting investor confidence towards the market.

Day Of The Week And Its Effect On Stock Market Volatility: Evidence From An Emerging Market

2013 ◽  
Vol 29 (6) ◽  
pp. 1727 ◽  
Author(s):  
Omar Farooq ◽  
Mohammed Bouaddi ◽  
Neveen Ahmed
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Emerging Market ◽  
International Markets ◽  
Conditional Variance ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Foreign Investors ◽  
High Volatility ◽  
Day Of The Week

This paper investigates the day of the week effect in the volatility of the Saudi Stock Exchange during the period between January 7, 2007 and April 1, 2013. Using a conditional variance framework, we find that the day of the week effect is present in the volatility. Our results show that the lowest volatility occurs on Saturdays and Sundays. We argue that due to the closure of international markets on Saturdays and Sundays, there is not enough activity in the Saudi Stock Exchange. As a result, the volatility is the lowest on these days. Our results also show that the highest volatility occurs on Wednesdays. We argue Wednesday, being the last trading day of the week, corresponds with the start of four non-trading days (Thursday through Sunday) for foreign investors. Fearing that they will be stuck up with stocks in case some unfavorable information enters the market, foreign investors tend to exit the market on Wednesdays. As a result of excessive trading, there is high volatility on Wednesdays.

Price Limit and Volatility in Taiwan Stock Exchange: Some Additional Evidence from the Extreme Value Approach

2007 ◽  
Vol 10 (01) ◽  
pp. 51-61 ◽  
Author(s):  
Aktham I. Maghyereh ◽  
Haitham A. Al Zoubi ◽  
Haitham Nobanee
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Extreme Value ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Price Limits ◽  
Stock Volatility ◽  
Price Limit ◽  
Taiwan Stock Exchange

We reexamine the effects of price limits on stock volatility of Taiwan Stock Exchange using a new methodology based on the Extreme-Value technique. Consistent with the advocates of price limits, we find that stock market volatility is sharply moderated under more restrictive price limits.

scholarly journals The Effect of Political Elections on Stock Market Volatility in Malaysia

2018 ◽  
Vol 7 (3.21) ◽  
pp. 114
Author(s):  
Ricky Chia Chee Jiun
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
General Election ◽  
Stock Index ◽  
Stock Market Volatility ◽  
Political Uncertainty ◽  
Stock Volatility ◽  
Volatility Risk ◽  
Company Stock ◽  
General Elections

During the past general elections held in Malaysia, empirical evidence showed a significant election effect in stock volatility. In this study, we investigate the influence of election on Malaysian stock market during the 12th and 13th general election where political tensions persisted due to the close fight between the two major parties. The findings indicate that the political uncertainty surrounding elections significantly affected investors respond. Results from statistical analysis uncover significant higher stock volatility in the pre-general election periods. Nevertheless, lower stock volatility is only found in two stock indices in the post-general election periods. By using the EGARCH model, a significant election effect is found in stock volatility but not in stock returns. Notably, political uncertainty showed up its significant role in influencing the stock volatility prior to the general elections in the year 2008 and 2013. Furthermore, lower stock volatility is found in the Shariah-compliant indices and stock index with greater market capitalization. Our findings have important implications for investors who are exposed to volatility risk. Investors may shift to large company stock and Shariah-compliant stock during the general election period. Investors should also be cautious because the high volatility is not compensated with a significant abnormal return. 

Forecasting Stock Market Volatility: Evidence from Six Emerging Markets

2013 ◽  
Vol 14 (2) ◽  
pp. 68-93
Author(s):  
Naliniprava Tripathy ◽  
Ashish Garg
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Stock Price ◽  
Market Volatility ◽  
Future Market ◽  
Investment Strategies ◽  
Stock Market Volatility ◽  
Efficient Management ◽  
Asymmetric Garch

This paper forecasts the stock market volatility of six emerging countries by using daily observations of indices over the period of January 1999 to May 2010 by using ARCH, GARCH, GARCH-M, EGARCH and TGARCH models. The study reveals the positive relationship between stock return and risk only in Brazilian stock market. The analysis exhibits that the volatility shocks are quite persistent in all country’s stock market. Further the asymmetric GARCH models find a significant evidence of asymmetry in stock returns in all six country’s stock markets. This study confirms the presence of leverage effect in the returns series and indicates that bad news generate more impact on the volatility of the stock price in the market. The study concludes that volatility increases disproportionately with negative shocks in stock returns. Hence investors are advised to use investment strategies by analyzing recent and historical news and forecast the future market movement while selecting portfolio for efficient management of financial risks to reap benefits in the stock markets.

scholarly journals Influence of non-monetary information signals of the USA on the Ukrainian stock market volatility

2019 ◽  
Vol 16 (1) ◽  
pp. 319-333 ◽  
Author(s):  
Roman Pavlov ◽  
Tetiana Pavlova ◽  
Anna Lemberg ◽  
Oksana Levkovich ◽  
Iryna Kurinna
Keyword(s):  
United States ◽  
Stock Market ◽  
Price Index ◽  
Consumer Price Index ◽  
The United States ◽  
Market Volatility ◽  
Stock Index ◽  
Stock Market Volatility ◽  
Economic Sectors ◽  
The Usa

The Ukrainian PFTS stock index volatility reaction as a whole and its constituent economic sectors (“Basic Materials”, “Financials”, “Industrials”, “Oil & Gas”, “Telecommunications”, “Utilities”) to seven non-monetary US information signals (“Consumer price index”, “Personal spending”, “Unemployment rate”, “Gross domestic product”, “Industrial production”, “Consumer confidence”, “Housing starts”) was carried out for the period 2000–2017 on the basis of closing stock quotations in the trading day format. To assess the “surprise” component direct influence nature of the USA selected non-monetary information signals on the PFTS stock index, an AR-GARCH econometric modelling device was used. The results achieved clearly indicate the presence of some PFTS stock index economic sectors heterogeneous reaction to the United States individual non-monetary information signals announcement. For example, such economic sectors as “Basic Materials”, “Financials”, and “Oil & Gas” volatility response to the US non-monetary information signal “Consumer price index” “surprise” components the opposite of the overall PFTS stock index reaction. It can also be concluded that the United States non-monetary information signals influence on the Ukrainian stock market volatility depends not only on the financial cycle phase and data frequency, but also on the PFTS stock index economic sector.

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