Is Foreign Capital Smarter? Multifractal Evidence from the Shanghai–Hong Kong Stock Connect Program

2020 ◽  
Vol 19 (04) ◽  
pp. 2050047
Author(s):  
Qingsong Ruan ◽  
Zilin Wang ◽  
Jing Liu ◽  
Dayong Lv
Keyword(s):  
Hong Kong ◽  
Stock Returns ◽  
Granger Causality ◽  
Cross Correlation ◽  
Foreign Capital ◽  
Granger Causality Test ◽  
Capital Inflow ◽  
Capital Flow ◽  
Causality Test ◽  
Domestic Capital

This paper investigates whether foreign capital is smarter money using multifractal cross-correlation analysis (MFCCA) and nonlinear Granger Causality test. Using multifractal detrended fluctuation analysis (MF-DFA) method, we find that time series of stock returns, foreign-capital inflow from Shanghai–Hong Kong Stock Connect (SHKSC), and domestic-capital flow (proxied by margin-trading activities capital) exhibit strong multifractality. In addition, MFCCA results show that there exists a strong persistent cross-correlation between stock returns and foreign-capital inflow, but anti-persistent cross-correlation between stock returns and domestic-capital flow. Moreover, using nonlinear Granger Causality test, we find that foreign-capital inflow is the granger cause of stock returns. Our findings provide empirical evidence that foreign-capital inflow is positively associated with future stock returns, i.e., foreign capital is smarter money.

MARGIN-TRADING ACTIVITIES AND FUTURE STOCK RETURNS: NEW EVIDENCE FROM NONLINEAR ANALYSIS

Fractals ◽  
2020 ◽  
Vol 28 (06) ◽  
pp. 2050126
Author(s):  
QINGSONG RUAN ◽  
JIARUI ZHANG ◽  
YAPING ZHOU ◽  
DAYONG LV
Keyword(s):  
Stock Returns ◽  
Cross Correlation ◽  
Predictive Power ◽  
Granger Causality Test ◽  
Return Predictability ◽  
Positive Information ◽  
Causality Test ◽  
Cross Correlation Analysis ◽  
Trading Activities ◽  
New Evidence

Using multifractal detrended cross-correlation analysis (MF-DCCA) and nonlinear Granger causality test, this paper examines the return predictability of margin-trading activities. Results show that the predictive power of margin-trading activities on subsequent stock returns varies with respect to the different aspects of margin trading. In line with previous studies, we find no significant correlation between margin-buying amount and subsequent stock returns. However, the margin-covering amount is negatively associated with subsequent stock returns; and margin debt is positively associated with the future stock returns. In general, our findings suggest that margin traders may have no positive information when they conduct a margin-buying position, but may possess negative information when covering their positions.

An Econometric Analysis of Linkages between Macroeconomic Variables and Stock Markets: Evidence from Asian Emerging Markets

GIS Business ◽  
2018 ◽  
Vol 13 (5) ◽  
pp. 21-30
Author(s):  
Risha Khandelwal
Keyword(s):  
Emerging Markets ◽  
Interest Rates ◽  
Stock Returns ◽  
Granger Causality ◽  
Stock Markets ◽  
Unit Root Test ◽  
Granger Causality Test ◽  
Causality Test ◽  
Macroeconomic Variables ◽  
Study Results

The purpose of this paper is to investigate impact of macroeconomic variables on stock markets of India and Indonesia. This paper also attempts to identify linkages between markets and macroeconomic variables. The rationale behind selecting these countries for the present study is MSCI emerging markets index of Asia, which comprises emerging economies with huge return potential for prospective investors. This study will help investors and researchers to understand dynamics of linkages between markets and macroeconomic variables. Augmented Dickey-Fuller (ADF) unit root test is used to assess the stationary of time series, Johansen test co-integration is applied to examine long-term integration among variables, Granger causality test is used to examine the causality relationship between macroeconomic variables and stock returns. The monthly data are taken for the study which ranges from July 1997 to July 2017. Currency exchange rates, interest rates, money supply, and inflation are the macroeconomic variables for the current study. Results revealed that there is one co-integrating equation of long-run equilibrium between the variables for both countries. Granger causality test reveals that there exists unidirectional and bidirectional relationship between the variables.

scholarly journals Evidence for Nonlinear Asymmetric Causality in US Inflation, Metal, and Stock Returns

2008 ◽  
Vol 2008 ◽  
pp. 1-7 ◽  
Author(s):  
D. Hristu-Varsakelis ◽  
C. Kyrtsou
Keyword(s):  
Stock Returns ◽  
Granger Causality ◽  
Discrete Time ◽  
Granger Causality Test ◽  
Causality Test ◽  
Glass Model ◽  
Causality Testing ◽  
Asymmetric Causality

The purpose of this paper is to propose a version of causality testing that focuses on how the sign of the returns affects the causality results. We replace the traditional VAR specification used in the Granger causality test by a discrete-time bivariate noisy Mackey glass model. Our test reveals interesting and previously unexplored relationships in US economic series, including inflation, metal, and stock returns.

Do Macroeconomic Variables Impact the Indian Stock Market?

2016 ◽  
Vol 5 (3) ◽  
Author(s):  
Khalid Ul Islam ◽  
Mohsina Habib
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Returns ◽  
Causal Relationship ◽  
Granger Causality ◽  
Oil Prices ◽  
Granger Causality Test ◽  
Causality Test ◽  
Macroeconomic Variables ◽  
Indian Stock Market

This paper is intended to study the impact of various macroeconomic variables on Indian stock market. Based on the Arbitrage Pricing Theory (APT) propounded by Ross in 1976 and various other studies, a number of macroeconomic variables including, inflation, industrial production, exchange rate, money supply, interest rate, and oil price have been identified to have a significant impact on the stock market. We have applied the multivariate extension of the classical linear regression model computed on Ordinary Least Squares method and Granger Causality test to re-establish the relationship between macroeconomic variables and stock returns over a period of 10 years from 2005 to 2015 using monthly observations. The results of this study show that only exchange rate has a significant negative impact on stock returns. The other macroeconomic variables are not significantly affecting stock returns, however, their impact is in accordance with the economic theory. The Granger Causality test reveals absence of any causal relationship between stock returns and macroeconomic variables, except in case of oil prices, where we find a unidirectional causal relationship running from stock returns to oil prices. However, the Granger Causality results should not be taken in the conventional meaning of causality, but results merely identifying precedence.

Money supply in Russia for the period from 2015 to 2019: The exogenous and endogenous approaches

2020 ◽  
Vol 26 (6) ◽  
pp. 1338-1351
Author(s):  
O.V. Lunyakov
Keyword(s):  
Granger Causality ◽  
Money Supply ◽  
Cross Correlation ◽  
Granger Causality Test ◽  
Causal Relationships ◽  
Test Results ◽  
Var Models ◽  
Causality Test ◽  
Russian Economy ◽  
The Future

Subject. This article explores the process of money supply generation in the Russian economy. Objectives. The article aims to define the direction of causal relationships between monetary indicators and credit in Russia from the perspective of exogenous and endogenous approaches. Methods. For the study, I used VAR models, group cross-correlation, and the Granger causality test. Results. Based on the analysis of the formation of money supply in Russia for the period from 2015 to 2019, the article presents certain formalization of causal relationships between monetary indicators and credit. The results of the study show that the formation of money supply in Russia was rather exogenous. Conclusions and Relevance. The results of the study are aimed at the development of the science of money and formalization of cause-and-effect relationships in the change of money supply based on real statistics. They can be used in the future in terms of clarifying the size of money supply changing.

scholarly journals Uncertainty Due to Infectious Diseases and Stock–Bond Correlation

Econometrics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 17
Author(s):  
Konstantinos Gkillas ◽  
Christoforos Konstantatos ◽  
Costas Siriopoulos
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Infectious Diseases ◽  
Granger Causality ◽  
Predictive Value ◽  
High Frequency ◽  
Causal Relation ◽  
Granger Causality Test ◽  
Causality Test ◽  
Non Linear

We study the non-linear causal relation between uncertainty-due-to-infectious-diseases and stock–bond correlation. To this end, we use high-frequency 1-min data to compute daily realized measures of correlation and jumps, and then, we employ a nonlinear Granger causality test with the use of artificial neural networks so as to investigate the predictability of this type of uncertainty on realized stock–bond correlation and jumps. Our findings reveal that uncertainty-due-to-infectious-diseases has significant predictive value on the changes of the stock–bond relation.

scholarly journals R&D Investment, Financial and Environmental Performance Nexuses via Bootstrap Fourier Quantiles Granger Causality Test

Economies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 85
Author(s):  
Feng-Li Lin
Keyword(s):  
Financial Performance ◽  
Granger Causality ◽  
Environmental Performance ◽  
Co2 Emission ◽  
Positive Relationship ◽  
Granger Causality Test ◽  
Causality Test ◽  
Emission Reductions ◽  
Policy Makers ◽  
D Investment

This study investigated the relationship between R&D investments and financial and environmental performance. The direction, size, and significance of various phases of these variables were generated using the bootstrap Fourier quantiles Granger causality test. In our results, a positive relationship between R&D investment and CO2 emission reductions was found at two tails of quantiles. Additionally, we observed a significantly positive relationship between financial performance and CO2 emission reductions at the 0.5 quantile and above. The correlation between R&D investment and financial performance was identified to be positive under the 0.3, 0.4, 0.5 and 0.9 quantiles and negative under the 0.5 and 0.6 quantiles. The changing linkages among R&D investment, environmental performance and financial performance found in this study provide important information for policy makers, aiding in the development of R&D strategies to upgrade financial and environmental performance simultaneously.

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