Time-varying cross-correlation between trading volume and returns in US stock markets

2021 ◽  
pp. 126211
Author(s):  
E. Rodriguez ◽  
J. Alvarez-Ramirez
Keyword(s):  
Stock Markets ◽  
Trading Volume ◽  
Cross Correlation ◽  
Time Varying

POWER LAW AND STRETCHED EXPONENTIAL EFFECTS OF EXTREME EVENTS IN CHINESE STOCK MARKETS

2010 ◽  
Vol 09 (02) ◽  
pp. 203-217 ◽  
Author(s):  
XIAOJUN ZHAO ◽  
PENGJIAN SHANG ◽  
YULEI PANG
Keyword(s):  
Correlation Analysis ◽  
Power Law ◽  
Extreme Events ◽  
Stock Markets ◽  
Cross Correlation ◽  
Extreme Values ◽  
Cumulative Distribution ◽  
Stretched Exponential ◽  
Cross Correlation Analysis ◽  
Chinese Stock Markets

This paper reports the statistics of extreme values and positions of extreme events in Chinese stock markets. An extreme event is defined as the event exceeding a certain threshold of normalized logarithmic return. Extreme values follow a piecewise function or a power law distribution determined by the threshold due to a crossover. Extreme positions are studied by return intervals of extreme events, and it is found that return intervals yield a stretched exponential function. According to correlation analysis, extreme values and return intervals are weakly correlated and the correlation decreases with increasing threshold. No long-term cross-correlation exists by using the detrended cross-correlation analysis (DCCA) method. We successfully introduce a modification specific to the correlation and derive the joint cumulative distribution of extreme values and return intervals at 95% confidence level.

Time-varying inter-market linkage of international stock markets

2008 ◽  
Vol 40 (19) ◽  
pp. 2501-2507 ◽  
Author(s):  
Y.-P. Hu ◽  
L. Lin ◽  
J.-W. Kao
Keyword(s):  
Stock Markets ◽  
Time Varying ◽  
International Stock Markets ◽  
Market Linkage

scholarly journals The Symmetric and Asymmetric Time-Varying Causality Relationships Between the COVID-19 Outbreak and the Stock Exchange: The Case of Selected Countries

Ekonomika ◽  
2021 ◽  
Vol 100 (2) ◽  
pp. 144-170
Author(s):  
Cuma Demirtaş ◽  
Munise Ilıkkan Özgür ◽  
Esra Soyu
Keyword(s):  
Mortality Rate ◽  
Stock Market ◽  
Stock Markets ◽  
Time Varying ◽  
Causality Test ◽  
Causality Tests ◽  
Bed Capacity ◽  
Case Rate ◽  
Asymmetric Causality ◽  
Second Wave

In this study, the effects of COVID-19 (mortality rate, case rate, and bed capacity) on the stock market was examined within the framework of the efficient market hypothesis. Unlike other studies in the literature, we used the variable of bed capacity besides the mortality rate and case rate variables. The relationship between the mentioned variables, using daily data between December 31 of 2019 and November 10 of 2020, has been analyzed with time-varying symmetric and asymmetric causality tests for China, Germany, the USA, and India. Considering that the responses to positive and negative shocks during the pandemic process may be different and that the results may change depending on time, time-varying symmetric and asymmetric causality tests were used. According to the time-varying symmetric causality test, stock markets in all countries were affected in the period when the cases first appeared. A causal relationship between COVID-19 and country stock markets was found. The results showed that the effects of the case rate and bed capacity on the stock market occurred around the same time in Germany and the United States; however, these dates differed in China and India. According to time-varying asymmetric causality test findings, the asymmetric effect of the pandemic on the stock market in countries emerged during the second wave. The findings showed that the period during which positive and negative information about the pandemic intensified coincided with the period during which the second wave occurred; besides, the results show the effect of this information on the stock market differed as positive and negative shocks.

scholarly journals Time-Varying Linkages of Economic Activities in China and the Stock Markets in ASEAN-5

2016 ◽  
Vol 10 (2) ◽  
pp. 137-152 ◽  
Author(s):  
Kee Tuan Teng ◽  
Siew Hwa Yen ◽  
Soo Y. Chua ◽  
Hooi Hooi Lean
Keyword(s):  
Stock Markets ◽  
Time Varying ◽  
Economic Activities

scholarly journals Linkages and performance comparison among Eastern Europe stock markets

2014 ◽  
Author(s):  
José Soares Da Fonseca
Keyword(s):  
Stock Markets ◽  
Performance Comparison ◽  
Market Model ◽  
Var Model ◽  
Time Varying ◽  
Comparative Performance ◽  
Regional Market ◽  
Auto Regressive ◽  
And Performance ◽  
The Empirical Analysis

This article studies the linkages among the stock markets of Bulgaria, Czech Republic, Estonia, Hungary, Poland, Romania, Russia, Serbia, Slovenia and Ukraine. The empirical analysis begins with the estimation of a regional market model, whose beta parameters depend on predetermined information variables. Those parameters support the calculation of time‑varying Treynor ratios used on a comparative performance analysis. A Vector Auto Regressive Model (VAR) is used to estimate the performance causality within this group of markets. The VAR model results provide evidence that there is reciprocal performance across the majority of the selected stock markets.

Time-varying synchronization of European stock markets

2010 ◽  
Vol 40 (2) ◽  
pp. 393-407 ◽  
Author(s):  
Balázs Égert ◽  
Evžen Kočenda
Keyword(s):  
Stock Markets ◽  
Time Varying ◽  
European Stock Markets

Does the weather affect the Chinese stock markets? Evidence from the analysis of DCCA cross-correlation coefficient

2014 ◽  
Vol 29 (01) ◽  
pp. 1450236 ◽  
Author(s):  
Guangxi Cao ◽  
Yan Han
Keyword(s):  
Correlation Coefficient ◽  
Stock Markets ◽  
Cross Correlation ◽  
Sunshine Duration ◽  
Statistical Test ◽  
Nonlinear Method ◽  
Weather Variables ◽  
Chinese Stock Markets ◽  
The Cross ◽  
The Relationship

Recent studies confirm that weather affects the Chinese stock markets, based on a linear model. This paper revisits this topic using DCCA cross-correlation coefficient (ρ DCCA (n)), which is a nonlinear method, to determine if weather variables (i.e., temperature, humidity, wind and sunshine duration) affect the returns/volatilities of the Shanghai and Shenzhen stock markets. We propose an asymmetric ρ DCCA (n) by improving the traditional ρ DCCA (n) to determine if different cross-correlated properties exist when one time series trending is either positive or negative. Further, we improve a statistical test for the asymmetric ρ DCCA (n). We find that cross-correlation exists between weather variables and the stock markets on certain time scales and that the cross-correlation is asymmetric. We also analyze the cross-correlation at different intervals; that is, the relationship between weather variables and the stock markets at different intervals is not always the same as the relationship on the whole.

The Impact of Regulatory Standards, Interest Rates and Trading Volume on Volatility Transmission between Cross-Listed European Equities

2009 ◽  
Vol 10 (1) ◽  
pp. 89-105
Author(s):  
Koulakiotis Dasilas ◽  
Tolikas Molyneux
Keyword(s):  
Interest Rates ◽  
Stock Markets ◽  
Trading Volume ◽  
Positive Impact ◽  
Stock Exchanges ◽  
Volatility Transmission ◽  
Volatility Spillovers ◽  
Regulatory Standards ◽  
European Stock Markets ◽  
The Impact

This paper investigates the relationship between volatility transmission and stock market regulatory structures, interest rates and trading volume for European securities which are cross-listed on stock exchanges of higher, lower or similar regulatory standards compared to their home stock markets. The empirical results suggested that the regulatory environment has a significant impact on volatility spillovers and the level of interest rates and trading volume have a positive impact on the magnitude and persistence of these volatility spillovers. These findings have potentially important implications for both regulators and investors who are concerned with the effectiveness of legislation aiming to harmonise the European stock markets and the effects of volatility transmission on investment positions across European stock markets.

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