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.

scholarly journals Dynamic Cross-Correlations between Participants’ Attentions to P2P Lending and Offline Loan in the Private Lending Market

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Yingxiu Zhao ◽  
Wei Zhang ◽  
Xiangyu Kong
Keyword(s):  
Correlation Analysis ◽  
Power Law ◽  
Cross Correlation ◽  
Granger Causality Test ◽  
Short Term ◽  
Causality Test ◽  
Cross Correlation Analysis ◽  
Private Lending ◽  
P2p Lending ◽  
Cross Correlations

In this paper, we examine the dynamic cross-correlations between participants’ attentions to the P2P lending and offline loan (lending) with the method of multifractal detrended cross-correlation analysis (MF-DCCA). The empirical result mainly shows that (1) the power-law cross-correlation exists between participants’ attentions to the P2P lending and offline loan and is persistent, (2) the cross-correlation is more stable in the short term, and (3) the relation subjected to a small fluctuation is more cross-correlated than that under larger ones. Furthermore, we carry out the robustness test to verify the result. The Granger causality test indicates that participants’ attentions to P2P lending and offline loan Granger cause each other in the short term.

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.

scholarly journals Leveraged Bootstrap Test of Volatility: A Novel Approach to the Energy Consumption and Economic Growth Puzzle

2017 ◽  
Vol 9 (9) ◽  
pp. 117 ◽  
Author(s):  
Kuo-Hao Lee ◽  
Jonathan Ohn ◽  
Evren Eryilmaz
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Stock Returns ◽  
Causal Relationship ◽  
Stock Prices ◽  
Granger Causality Test ◽  
Energy Industry ◽  
Causality Test ◽  
Bootstrap Test ◽  
Novel Approach

The main purpose of this research is to examine the causal relationship between the Energy industry and nine other industries by use of volatility instead of returns. Existing literatures find a causal relationship by use of stock returns, however, we find that using volatility reveals a causal relationship that might not otherwise be revealed through returns alone. Since the existing literature shows that volatility of stock prices is informative, we apply a Granger causality test by use of a leveraged bootstrap test developed by Hacker and Hatemi (2006) to investigate the causal behavior of the volatility. Our results show that volatility of the Energy industry causes volatility in two other industries- Industrials and Health Care. Also, the Energy industry market is affected by the Materials, Consumer Staples and Utilities industries. This finding is substantially different from the findings of previous research, and provides a novel approach to analyzing and solving the energy consumption and economic growth puzzle.

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.

scholarly journals The Earnings Expectations Game and the Dispersion Anomaly

2021 ◽  
Author(s):  
David Veenman ◽  
Patrick Verwijmeren
Keyword(s):  
Stock Returns ◽  
Return Predictability ◽  
Analyst Forecast ◽  
Forecast Dispersion ◽  
Earnings Expectations ◽  
Negative Relation ◽  
Earnings Surprises ◽  
Ex Ante ◽  
New Evidence

This study examines the role of differences in firms’ propensity to meet earnings expectations in explaining why firms with high analyst forecast dispersion experience relatively low future stock returns. We first demonstrate that the negative relation between dispersion and returns is concentrated around earnings announcements. Next, we show that this relation disappears when we control for ex ante measures of firms’ propensity to meet earnings expectations and that the component of dispersion explained by these measures drives the return predictability of dispersion. We further demonstrate that firms with low analyst dispersion are substantially more likely to achieve positive earnings surprises and provide new evidence consistent with both expectations management and strategic forecast pessimism explaining this result. Overall, we conclude that investor mispricing of firms’ participation in the earnings-expectations game provides a viable explanation for the dispersion anomaly. Accepted by Brian Bushee, accounting.

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.

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