Asset Pricing and Volatility Modeling: The Case of Indonesia Stock Market

2014 ◽  
Author(s):  
Aldrin Herwany ◽  
Mohd Azmi Omar ◽  
Ahamed Kameel Meera ◽  
Erie Febrian
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Volatility Modeling

scholarly journals Volatility Modeling: An Overview of Equity Markets in the Euro Area during COVID-19 Pandemic

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1212
Author(s):  
Pierdomenico Duttilo ◽  
Stefano Antonio Gattone ◽  
Tonio Di Di Battista
Keyword(s):  
Stock Market ◽  
Euro Area ◽  
Risk Premium ◽  
Stock Markets ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Volatility Modeling ◽  
The Impact ◽  
Second Wave ◽  
Daily Returns

Volatility is the most widespread measure of risk. Volatility modeling allows investors to capture potential losses and investment opportunities. This work aims to examine the impact of the two waves of COVID-19 infections on the return and volatility of the stock market indices of the euro area countries. The study also focuses on other important aspects such as time-varying risk premium and leverage effect. This investigation employed the Threshold GARCH(1,1)-in-Mean model with exogenous dummy variables. Daily returns of the euro area stock markets indices from 4th January 2016 to 31st December 2020 has been used for the analysis. The results reveal that euro area stock markets respond differently to the COVID-19 pandemic. Specifically, the first wave of COVID-19 infections had a notable impact on stock market volatility of euro area countries with middle-large financial centres while the second wave had a significant impact only on stock market volatility of Belgium.

Long-term perspective on the stock market matters in asset pricing

2016 ◽  
Vol 16 ◽  
pp. 162-170
Author(s):  
Heungju Park ◽  
Bumjean Sohn
Keyword(s):  
Asset Pricing ◽  
Stock Market

The Skewness of the Stock Market over Long Horizons

2020 ◽  
Author(s):  
Anthony Neuberger ◽  
Richard Payne
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Index ◽  
Leverage Effect ◽  
Higher Moments ◽  
Data Generating Process ◽  
Short Horizon ◽  
Stock Index Returns ◽  
Standard Techniques ◽  
Daily Returns

Abstract Higher moments of long-horizon returns are important for asset pricing but are hard to measure accurately using standard techniques. We provide theory showing that short-horizon (e.g., daily) returns can be used to construct precise estimates of long-horizon (e.g., annual) moments without making strong assumptions about the data-generating process. Skewness comprises two components: skewness of short-horizon returns and a leverage effect, that is, covariance between variance and lagged returns. We provide similar results for kurtosis. An application to U.S. stock index returns shows that skew is large and negative and attenuates only slowly as one moves from monthly to multiyear horizons.

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