GARCH Model, Heavy Tails and the Chinese Stock Market Returns

2017 ◽  
Author(s):  
Michael Day ◽  
Mark Diamond
Keyword(s):  
Stock Market ◽  
Heavy Tails ◽  
Garch Model ◽  
Chinese Stock Market ◽  
Market Returns ◽  
Stock Market Returns

scholarly journals A New Class of Heavy-Tailed Distribution and the Stock Market Returns in Germany

2017 ◽  
Vol 4 (2) ◽  
pp. 13 ◽  
Author(s):  
John Oden ◽  
Kevin Hurt ◽  
Susan Gentry
Keyword(s):  
Stock Market ◽  
Global Economy ◽  
Heavy Tails ◽  
Financial Sector ◽  
Superior Performance ◽  
Market Returns ◽  
Stock Market Returns ◽  
Volatility Clustering ◽  
Empirical Performance ◽  
Heavy Tailed

As the fourth largest economy over the world, Germany’s financial sector plays a key role in the global economy. As one of the most important components of the financial sector, the equity market played a more and more important role. Thus, risk management of its stock market is crucial for welfare of its market participants. To account for the two stylized facts, volatility clustering and conditional heavy tails, we take advantage of the framework in Guo (2016) and consider empirical performance of the GARCH model with normal reciprocal inverse Gaussian distribution in fitting the German stock return series. Our results indicate the NRIG distribution has superior performance in fitting the stock market returns.

LONG-TERM MEMORY IN EMERGING MARKETS: EVIDENCE FROM THE CHINESE STOCK MARKET

2006 ◽  
Vol 05 (03) ◽  
pp. 495-501 ◽  
Author(s):  
CHAOQUN MA ◽  
HONGQUAN LI ◽  
LIN ZOU ◽  
ZHIJIAN WU
Keyword(s):  
Stock Market ◽  
Emerging Markets ◽  
Emerging Market ◽  
Long Term Memory ◽  
Chinese Stock Market ◽  
Market Returns ◽  
Stock Market Returns ◽  
Term Memory ◽  
Rescaled Range Analysis

The notion of long-term memory has received considerable attention in empirical finance. This paper makes two main contributions. First one is, the paper provides evidence of long-term memory dynamics in the equity market of China. An analysis of market patterns in the Chinese market (a typical emerging market) instead of US market (a developed market) will be meaningful because little research on the behaviors of emerging markets has been carried out previously. Second one is, we present a comprehensive research on the long-term memory characteristics in the Chinese stock market returns as well as volatilities. While many empirical results have been obtained on the detection of long-term memory in returns series, very few investigations are focused on the market volatility, though the long-term dependence in volatility may lead to some types of volatility persistence as observed in financial markets and affect volatility forecasts and derivative pricing formulas. By means of using modified rescaled range analysis and Autoregressive Fractally Integrated Moving Average model testing, this study examines the long-term dependence in Chinese stock market returns and volatility. The results show that although the returns themselves contain little serial correlation, the variability of returns has significant long-term dependence. It would be beneficial to encompass long-term memory structure to assess the behavior of stock prices and to research on financial market theory.

scholarly journals DETERMINANTS OF G7 AND CHINESE STOCK MARKET RETURNS DURING COVID-19 OUTBREAK

2020 ◽  
Vol S.I. (1) ◽  
pp. 256-266
Author(s):  
Ahmed JERIBI ◽  
◽  
Mohamed FAKHFEKH ◽  
Keyword(s):  
Growth Rate ◽  
Stock Market ◽  
Financial Markets ◽  
Portfolio Diversification ◽  
Chinese Stock Market ◽  
Market Returns ◽  
Stock Market Returns ◽  
Hedging Strategies ◽  
The Us

The purpose of this paper is to discuss the determinants of G7, and Chinese stock market returns during the COVID-19 outbreak. We find that Bitcoin and Ethereum can generate benefits from portfolio diversification and hedging strategies for G7 financial investors in early 2020. Our result reveals that Gold is neither hedge nor haven during the COVID-19 pandemic. In addition, the results indicated that the expected volatility of the US stock market has no effect on the Japanese and Chinese financial markets. Finally, our results suggest that the growth rate of confirmed COVID-19 cases and deaths has an impact only on the US stock market.

scholarly journals The Relevance of Cboe Volatility Index to Stock Markets in Emerging Economies

2015 ◽  
Vol 6 (1) ◽  
pp. 93-106
Author(s):  
Tamara Mariničevaitė ◽  
Jovita Ražauskaitė
Keyword(s):  
Stock Market ◽  
Emerging Economies ◽  
Stock Markets ◽  
Chinese Stock Market ◽  
Stock Market Volatility ◽  
Global Risk ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Volatility Index

We examine the capability of CBOE S&P500 Volatility index (VIX) to determine returns of emerging stock market indices as compared to local stock markets volatility indicators. Our study considers CBOE S&P500 VIX, local BRIC stock market volatility indices and BRIC stock market MSCI indices daily returns in the period from January 1, 2009 to September 30, 2014. Research is conducted in two steps. First, we perform Spearman correlation analysis between daily changes in CBOE S&P500 VIX, local BRIC stock market VIX and MSCI BRIC stock market indices returns. Second, we perform multiple regression analysis with ARCH effects to estimate the relevance of CBOE S&P500 VIX and local VIX in determining BRIC stock market returns. Research reports weak correlation between CBOE S&P500 VIX and local VIX (except for Brazil). Furthermore, results challenge the assumption of CBOE S&P500 VIX being an indicator of global risk aversion. We conclude that commonly documented trends of rising globalization and stock markets co-integration are not yet present in emerging economies, therefore the usage of CBOE S&P500 VIX alone in determining BRIC stock market returns should be considered cautiously, and local volatility indices should be accounted for in analysis. Furthermore, the data confirms the presence of safe haven properties in Chinese stock market index.

Sign in / Sign up

Export Citation Format

Share Document