scholarly journals Granger causality stock market networks: Temporal proximity and preferential attachment

2015 ◽  
Vol 427 ◽  
pp. 262-276 ◽  
Author(s):  
Tomáš Výrost ◽  
Štefan Lyócsa ◽  
Eduard Baumöhl
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Preferential Attachment ◽  
Temporal Proximity ◽  
Market Networks

scholarly journals Understanding the Interdependency between the Nifty 50 Future Index and the Advanced Future Stock Market through Econometrics

2019 ◽  
Vol 8 (4) ◽  
pp. 3660-3664
Keyword(s):  
Hong Kong ◽  
Stock Market ◽  
Granger Causality ◽  
Foreign Exchange ◽  
Financial Market ◽  
Stock Prices ◽  
Economic Condition ◽  
The Future ◽  
Bidirectional Movement ◽  
High Degree

In recent times the stock market is accepted as a tool to measure the economic condition of a nation. It is found that the Indian financial market as highly volatile due to the lower value of rupees in foreign exchange with the dollar. This motivated the researchers to measure the interdependencies of [Nifty 50 future (India), Nikkei 225(Japan), NASDAQ 100 Futures (USA), Dow Jones 30 (USA), SSEC (China), Hang Seng Future (Hong Kong), and FTSE 100 (London)]. The analysis covers monthly stock prices for a period of 10years from April 2008 to March 2018. The measurement of interdependencies is studied through granger causality and correlation after the confirmation of the non-normality of data and stationary of data. The result shows a high degree of correlation between NASDAQ and Dow Jones shows 98.76% followed by 96.89% between Nifty 50 future and NASDAQ. The co-movement result of Nifty 50 future through granger causality states Nifty 50 future can explain the future stock market of Nikkei (Japan) and SSEC (China) and the Hang Seng future (Hong Kong) has a bidirectional movement with Nifty 50 futures. The study is useful for the investors to identify the interdependencies of the indices and understand the movement in a significant manner.

Housing market networks in China's major cities: a conditional causality approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lu Yang ◽  
Nannan Yuan ◽  
Shichao Hu
Keyword(s):  
Housing Market ◽  
Granger Causality ◽  
House Price ◽  
Housing Markets ◽  
Content Type ◽  
Scale Free ◽  
Second Tier ◽  
The Difference ◽  
Secondary Housing Market ◽  
Market Networks

PurposeTo explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a combination of conditional Granger causality and network analysis.Design/methodology/approachAlthough housing market networks have been well discussed for different countries, the question of housing market networks in China's major cities based on the conditional causality perspective has yet to be answered.FindingsWe discover that second-tier cities are more influential than first-tier cities. Although the connectivity of the primary housing market is more complex than the diversified connectivity observed in the secondary housing market, both markets are scale-free networks that exhibit high stability. Moreover, we reveal that geographic conditions and economic development jointly determine the housing market's modular hierarchical structure. Our results provide meaningful information for both Chinese policymakers and investors.Originality/valueBy excluding the influence of other cities, our conditional Granger causality identifies the true casual relation between cities' housing markets. Moreover, it is the first paper to consider the primary housing market and secondary housing market separately. Specifically, Chinese prefer new house rather than second-hand house from both speculative and self-housing. Generally speaking, the new house price is lower than the second-hand house price since the new house is off-plan property. Therefore, understanding the difference between primary and secondary housing markets will provide useful information for both policymakers and speculators.

The Relationship Between Stock Market Indices of the Biggest Six Economies of the European Union and BIST 100

2020 ◽  
pp. 257-275
Author(s):  
Serdar Ögel ◽  
Fatih Temizel
Keyword(s):  
European Union ◽  
Stock Market ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Var Model ◽  
The European Union ◽  
Causality Test ◽  
Integration Test ◽  
Causality Relationship ◽  
The Relationship

This chapter examines the relationship between stock market indices of the biggest six economies of the European Union and BIST 100. In this context, this study used the daily time series regarding indices of DAX for Germany, CAC 40 for France, FTSE MIB for Italy, IBEX 35 for Spain, AEX for Holland, FTSE 100 for United Kingdom, and BIST 100 for Turkey from 2014 to 2018. To test whether there is a co-integration relationship among indices, Johansen co-integration test was used. Since a co-integration relationship was not found between series, causality relationship between the European stock market indices and Turkey was tested with Granger causality test by establishing standard VAR model. As a result, a unidirectional Granger causality relationship was found from DAX, FTSE 100, CAC 40, IBEX 35, and AEX to BIST 100 according to lag length 1 and 2. However, a unidirectional Granger causality relationship was only found from FTSE MIB to BIST 100 for lag length 1. For lag length 1 and 2, no causality relationship was found from BIST 100 to the selected European stock market indices.

Are stock market networks non-fractal? Evidence from New York Stock Exchange

2016 ◽  
Vol 17 ◽  
pp. 97-102 ◽  
Author(s):  
Zhi-Jian Zeng ◽  
Chi Xie ◽  
Xin-Guo Yan ◽  
Jue Hu ◽  
Zhou Mao
Keyword(s):  
New York ◽  
Stock Market ◽  
Stock Exchange ◽  
New York Stock Exchange ◽  
York Stock Exchange ◽  
Market Networks

Intensity of shock transmission amid US-BRICS markets

2015 ◽  
Vol 10 (3) ◽  
pp. 311-328 ◽  
Author(s):  
P. Lakshmi ◽  
S. Visalakshmi ◽  
Kavitha Shanmugam
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Stock Markets ◽  
Subprime Mortgage ◽  
Content Type ◽  
Brics Countries ◽  
Long Run ◽  
The Us ◽  
The Usa ◽  
Short Run

Purpose – The purpose of this paper is to analyze the intensity of transmission of shocks from USA to BRICS countries in the long-run and short-run deviations and swiftness of recovery during US subprime mortgage crisis. This analysis enables the authors to explore the evolving patterns of relationships between these markets and examine whether their co-movements altered either in response to international shocks that originated in advanced markets like USA or due to their domestic fluctuations. Design/methodology/approach – Employing data of daily stock market indices (open and close) of BRICS countries for the period January 2, 2001 to May 31, 2012, this paper examines the interactions and characteristics of price movements of BRICS with US market by applying co-integration tests, vector error correction model and Granger causality relationship. The daily stock market indices data are derived from respective stock exchange web sites. Findings – The results exhibit that both long-run co-integration relationships and short-run Granger causality relationships exist between the stock markets of US-BRICS. Furthermore, this nexus is amplified in the short-run during 2007-2009, when the subprime mortgage financial crisis in the USA cropped up. This finding lends support to the prominence of developed (US) market links in the proliferation of persistent co-movements of BRICS stock markets. Research limitations/implications – The findings imply an increasing degree of global market integration due to quick dissemination of global shocks originating from developed market like USA, and swift recovery which can be attributed to the increased resilience, consistent with the moderated level of domestically driven risk in the BRICS markets. In spite of their similarities, long-run and short-run interdependences with the US stock market exhibit differences among the BRICS. This can be attributed to the regional heterogeneity in long-run risk and return co-movements with the USA. Practical implications – Changes from the US index easily affect these stock markets in the short-run, which implies that the US index may act as a leading indicator for investing funds in BRICS markets. Originality/value – This study would enable the authors to understand whether BRICS economies actually remain resilient to adverse developments in USA and could serve as alternative investment destinations for global portfolio diversification.

scholarly journals Effects of Interest Rate on Stock Market Returns in Kenya

2017 ◽  
Vol 9 (8) ◽  
pp. 40
Author(s):  
Donald A. Otieno ◽  
Rose W. Ngugi ◽  
Nelson H. W. Wawire
Keyword(s):  
Interest Rate ◽  
Stock Market ◽  
Granger Causality ◽  
Moving Average ◽  
Market Returns ◽  
Treasury Bills ◽  
Stock Market Returns ◽  
Long Run ◽  
Lending Rate ◽  
Short Run

Debate on the stochastic behaviour of stock market returns, 3-month Treasury Bills rate, lending rate and their cointegrating residuals remains unsettled. This study examines the stochastic properties of the macroeconomic variables, stock market returns and their cointegrating residuals using an Autoregressive Fractionally Integrated Moving Average (ARFIMA) model. It also investigates Granger causality between the two measures of interest rate and stock market returns. The study uses monthly data from 1st January 1993 to 31st December 2015. The results indicate that the 3-month Treasury Bills rate, lending rate and stock market returns are fractionally integrated which implies that shocks to the variables persist but eventually disappear. The results also reveal that the cointegrating residuals are fractionally integrated which suggests that a new and harmful long-run equilibrium might be established when each of the measures of interest rate is driven away from stock market returns. Additionally, the results indicate that the 3-month Treasury Bills rate and lending rate negatively Granger cause stock market returns in the long run. This suggests that stocks and Treasury Bills are competing investment assets. On the other hand, ARFIMA-based Granger causality reveals that stock market returns lead the 3-month Treasury Bills rate and lending rate with a negative sign in the short run. This implies that a prosperous stock market results into a favorable macroeconomic environment. A key contribution of this study is that it is the first to empirically examine fractional cointegration and ARFIMA-based Granger Causality between interest rate and stock market returns in Kenya.

REAL EXCHANGE RATE RETURNS AND REAL STOCK PRICE RETURNS IN THE STOCK MARKET OF MALAYSIA

2016 ◽  
Vol 64 (05) ◽  
pp. 1319-1349
Author(s):  
HOCK TSEN WONG
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Real Exchange Rate ◽  
Granger Causality ◽  
Unit Root ◽  
Stock Price ◽  
Unit Root Test ◽  
The United States ◽  
Test Statistics ◽  
Time Invariant

This study examines the relationships between real exchange rate returns and real stock price returns in the stock market of Malaysia. The Kwiatkowski, Phillips, Schmidt and Shin (KPSS) and Dickey and Fuller (DF) unit root test statistics show that all the variables examined are found to be stationary in the first differences. The constant conditional correlation (CCC)-multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) model shows that real exchange rate return of Malaysian ringgit against the United States dollar (RM/USD) and real stock price return of Kuala Lumpur Composite Index (KLCI) are found to be negative and significantly correlated. However, there is insignificant correlation between real exchange rate return of Malaysian ringgit against Japanese Yen (RM/¥) and real stock price return of KLCI. Moreover, the CCC-MGARCH models show that real exchange rate returns and real stock price returns of some stocks are found to be significantly correlated. The KPSS unit root test statistics show that the time invariant conditional variances of real exchange rate returns and real stock price returns are mostly found to be stationary in the levels. There is no evidence of Granger causality between the time invariant conditional variances of real exchange rate returns and real stock price return of KLCI but some evidence of Granger causality between the time invariant conditional variances of real exchange rate returns and real stock price returns. There is a link between the exchange rate market and the stock market in Malaysia but not every real stock price return is significantly linked with real exchange rate return.

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