scholarly journals Election Cycles and Stock Market Reaction: International Evidence

2015 ◽  
Vol 30 (3) ◽  
pp. 23-40
Author(s):  
Park Cheol Beom ◽  
An Ji Youn
Keyword(s):  
Stock Market ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Dynamic Pattern ◽  
International Evidence ◽  
Stock Market Reaction ◽  
Before And After ◽  
Using Data ◽  
Over Time ◽  
Made In

This study investigates movements of stock market volatility during election periods (the six months before and after an election) using data from 16 countries. The main findings of this study are (1) volatility declines over time as elections approach, (2) the level of volatility during election periods is lower than that during nonelection periods, and (3) volatility rises quickly during election months and immediately after the elections. The first and second findings confirm assertions made in previous studies, such as Pantzalis, Stangeland, and Turtle (2000) and Wisniewski (2009), regarding the dynamic pattern of stock market volatility during election years.

Forecasting stock market volatility: Further international evidence

2006 ◽  
Vol 12 (2) ◽  
pp. 171-188 ◽  
Author(s):  
Ercan Balaban ◽  
Asli Bayar ◽  
Robert W. Faff
Keyword(s):  
Stock Market ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
International Evidence

scholarly journals Stock market volatility during dividend announcement a case of selected scripts

2012 ◽  
Vol 1 (3) ◽  
pp. 184-190
Author(s):  
POORNIMA S ◽  
CHITRA V
Keyword(s):  
Information Technology ◽  
Stock Market ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Daily Data ◽  
Time Period ◽  
The Individual ◽  
Autoregressive Conditional Heteroscedasticity ◽  
The Empirical Analysis ◽  
Made In

An attempt has been made in this paper to explain the stock market volatility at the individual script level and at the aggregate indices level. The empirical analysis has been done by using Generalised Autoregressive Conditional Heteroscedasticity (GARCH) model. It is based on daily data for the time period from January 2007 to December 2009. The analysis reveals the same trend of volatility in the case of aggregate indices and three different sectors such as Banking,Information Technology and Cement. The GARCH (1,1) model is persistent for all the five aggregate indices and individual company.

scholarly journals Stock Market Volatility and Recent Crises

2021 ◽  
Vol 11 (3) ◽  
pp. 87
Author(s):  
Xin Tan ◽  
Sorin A. Tuluca
Keyword(s):  
Economic Policy ◽  
Stock Market ◽  
Great Recession ◽  
Economic Effect ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Policy Makers ◽  
The Great Recession ◽  
The Us ◽  
Before And After

We study the volatility of the US stock market and its sectors as defined by S&P before and after four recent crises: the Mexican crises, the Asian crises, the Dotcom crises and the Great Recession. We compare the increase in daily volatility with the increase in the implied daily volatility (derived from the monthly volatility) to determine if there was a lasting economic effect of each crisis or the increase in volatility was due to financial transitory components. We find that for each crisis the effect was different even though the increase in volatility was present for most of the crises in the post crises period. The paper helps investors and economic policy makers understand what the response to each crisis should be to stabilize the economy.

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