scholarly journals Chinese and Indian Stock Market Linkages with Developed Stock Markets

2011 ◽  
Vol 2 (2) ◽  
Author(s):  
Gurcharan Singh Pritam Singh
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Market Linkages ◽  
Developed Stock Markets ◽  
Indian Stock Market

Do Lower Foreign Flows and Higher Domestic Flows Reduce Indian Equity Market Volatility?

2021 ◽  
pp. 097226292199098
Author(s):  
Vaibhav Aggarwal ◽  
Adesh Doifode ◽  
Mrityunjay Kumar Tiwary
Keyword(s):  
Stock Market ◽  
Mutual Fund ◽  
Stock Markets ◽  
Large Scale ◽  
Structural Changes ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Equity Investments ◽  
Net Equity ◽  
Indian Stock Market

This study examines the relationship that both domestic and foreign institutional net equity flows have with the India stock markets. The motivation behind is the study to examine whether increased net equity investments from domestic institutional investors has reduced the influence of foreign equity flows on the Indian stock market volatility. Our results indicate that only during periods in which domestic equity inflows surpass foreign flows by a significant margin, as seen during 2015–2018, is the Indian stock market volatility not significantly influenced by foreign equity investments. However, during periods of re-emergence of strong foreign net inflows, the Indian market volatility is still being impacted significantly, as has been observed since 2019. Furthermore, we find that both large-scale net buying and net selling by domestic funds increased the stock market volatility as observed during 2015–2018 and COVID-impacted year 2020 respectively. The implications of this study are multi-fold. First, the regulators should discuss with industry bodies before enforcing major structural changes like reconstituting of mutual fund investment mandate in 2017 which forced domestic funds to quickly change portfolio allocation amongst large-cap, mid-cap and small-cap stocks resulting in higher stock market volatility. Second, adequate investor educational and awareness programmes need to be conducted regularly for retail investors to minimize herd behaviour of investing during market rise and heavy redemptions at times of fall. Third, the economic policies should be stable and forward-looking to ensure foreign investors remain attracted to the Indian stock markets at all times.

Comovement Dynamics between Central and Eastern European and Developed European Stock Markets during European Integration and Amid Financial Crises – A Wavelet Analysis

2012 ◽  
Vol 23 (1) ◽  
pp. 22-32 ◽  
Author(s):  
Silvo Dajcman ◽  
Mejra Festic ◽  
Alenka Kavkler
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Financial Crises ◽  
Eastern European ◽  
Short Term ◽  
Market Return ◽  
Stock Market Return ◽  
Time Period ◽  
Developed Stock Markets ◽  
European Stock Markets

Stock market comovements between developed (represented in the article by markets of Austria, France, Germany, and the UK) and developing stock markets (represented here by three Central and Eastern European (CEE) markets of Slovenia, the Czech Republic, and Hungary) are of great importance for the financial decisions of international investors. From the point of view of portfolio diversification, short-term investors are more interested in the comovements of stock returns at higher frequencies (short-term movements), while long-term investors focus on lower frequencies comovements. As such, one has to resort to a time-frequency domain analysis to obtain insight about comovements at the particular time-frequency (scale) level. The empirical literature on the CEE and developed stock markets interdependence predominantly apply simple (Pearsons) correlation analysis, Granger causality tests, cointegration analysis, and GARCH modeling. None of the existent empirical studies examine time-scale comovements between CEE and developed stock market returns. By applying a maximal overlap discrete wavelet transform correlation estimator and a running correlation technique, we investigated the dynamics of stock market return comovements between individual Central and Eastern European countries and developed European stock markets in the period from 1997-2010. By analyzing the time-varying dynamics of stock market comovements on a scale-by-scale basis, we also examined how major events (financial crises in the investigated time period and entrance to the European Union) affected the comovement of CEE stock markets with developed European stock markets. The results of the unconditional correlation analysis show that the developed European stock markets of France, the UK, Germany and Austria were more interdependent in the observed period than the CEEs stock markets. The later group of countries exhibited a lower degree of comovement between themselves as well as with the developed European stock markets during all the observed time period. The Slovenian stock market was the least correlated with other stock markets. By using the rolling wavelet correlation technique, we wanted to answer the question as to how the correlation between CEE and developed stock markets changed over the observed period. In particular, we wanted to examine whether major economic (financial) and political events in the world and European economies (the Russian financial crisis, the dot-com financial crisis, the attack on the WTC, the CEE countries joining the European union, and the recent global financial crisis) have influenced the dynamics of CEE stock market comovements with developed European stock markets. The results show that stock market return comovements between CEE and developed European stock markets varied over time scales and time. At all scales and during the entire observed time period the Hungarian and Czech stock markets were more interconnected to developed European stock markets than the Slovenian stock market was. The highest comovement between the investigated CEE and developed European stock market returns was normally observed at the highest scales (scale 5, corresponding to stock market return dynamics over 32-64 days, and scale 6, corresponding to stock market return dynamics over 32-64 and 64-128 days). At all scales the Hungarian and Czech stock markets were more connected to developed European stock markets than the Slovenian stock market. We found that European integration lead to increased comovement between CEE and developed stock markets, while the financial crises in the observed period led only to short-term increases in stock market return comovements.DOI: http://dx.doi.org/10.5755/j01.ee.23.1.1221

Stock Market Linkages Before and After the Asian Financial Crisis: Evidence from Three Greater China Economic Area Stock Markets and the US

2006 ◽  
Vol 09 (02) ◽  
pp. 297-315 ◽  
Author(s):  
Hwahsin Cheng ◽  
John L. Glascock
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
The United States ◽  
Asian Financial Crisis ◽  
Greater China ◽  
Market Linkages ◽  
Economic Area ◽  
Before And After

We investigate the stock market linkages between the United States and three Greater China Economic Area stock markets — China, Hong Kong, and Taiwan, before and after the 1997 Asian financial crisis. Daily stock market indices from January 1995 to December 2000 are used for the analysis. Results from Granger causality test indicate increased feedback relationships between the markets in the post-crisis period. We also find, from the principal component analysis, fewer common factors affecting stock returns after the crisis, suggesting more harmonious market co-movements after the financial crisis. Additionally, results from a variance decomposition analysis suggest that stock markets are more responsive to foreign shocks after the crisis. This further strengthens the evidence that stock markets become more interrelated after the 1997 Asian financial crisis.

scholarly journals Diffusion Entropy Analysis: Stability of Indian Stock Market

2019 ◽  
Vol 8 (4) ◽  
pp. 9358-9362
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Stock Exchange ◽  
Significant Drop ◽  
Bear Market ◽  
Diffusion Entropy ◽  
The Usa ◽  
The Stability ◽  
Indian Stock Market

The large amount of available data of stock markets becomes very beneficial when it is transformed to valuable information. The analysis of this huge data is essential to extract out the useful information. In the present work, we employ the method of diffusion entropy to study time series of different indexes of Indian stock market. We analyze the stability of Nifty50 index of National Stock Exchange (NSE) India and SENSEX index of Bombay Stock Exchange (BSE), India in the vicinity of global financial crisis of 2008. We also apply the technique of diffusion entropy to analyze the stability of Dow Jones Industrial Average (DJIA) index of USA. We compare the results of Indian Stock market with the USA stock market (DJIA index). We conduct an empirical analysis of the stability of Nifty50, Sensex and DJIA indexes. We find significant drop in the value of diffusion entropy of Nifty50, Sensex and DJIA during the period of crisis. Both Indian and USA stock markets show bull market effects in the pre-crisis and post-crisis periods and bear market effect during the period of crisis. Our findings reveal that diffusion entropy technique can replicate the price fluctuations as well as critical events of the stock market.

scholarly journals The Impact of Covid-19 Spread on Stock Markets: The Case of the GCC Countries

2020 ◽  
Vol 13 (11) ◽  
pp. 16
Author(s):  
Nader Alber ◽  
Amr Saleh
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Market Index ◽  
Stock Market Return ◽  
Gcc Countries ◽  
Developed Stock Markets ◽  
The Impact

This paper attempts to investigate the effects of 2020 Covid-19 world-wide spread on stock markets of GCC countries. Coronavirus spread has been measured by cumulative cases, new cases, cumulative deaths and new deaths. Coronavirus spread has been measured by numbers per million of population, while stock market return is measured by Δ in stock market index. Papers conducted in this topic tend to analyze Coronavirus spread in the highly infected countries and focus on the developed stock markets. Countries with low level of infection that have emerging financial markets seem to be less attractive to scholars concerning with Coronavirus spread on stock markets. This is why we try to investigate the GCC stock markets reaction to Covid-19 spread.   Findings show that there are significant differences among stock market indices during the research period. Besides, stock market returns seem to be sensitive to Coronavirus new deaths. Moreover, this has been confirmed for March without any evidence about these effects during April and May 2020.

Stock Market Seasonality in an Emerging Market

2004 ◽  
Vol 29 (3) ◽  
pp. 35-42 ◽  
Author(s):  
S N Sarma
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Abnormal Returns ◽  
Market Returns ◽  
Reform Era ◽  
Stock Market Returns ◽  
Active Strategy ◽  
Calendar Anomalies ◽  
Indian Stock Market ◽  
Daily Returns

The objective of this paper is to explore the day-of-the-week effect on the Indian stock market returns in the post-reform era. Till the late seventies, empirical studies provided ample evidence as to the informational efficiency of the capital markets advocating futility of information in consistently generating abnormal returns. However, later studies identified certain anomalies in the efficient market postulate. One major anomaly brought forth was the calendar-related abnormal rates of return. Various studies in this domain empirically demonstrated, through parametric and non-parametric tests on the stock returns data, that turn of the year, month, week, and holidays have consistently generated abnormal equity returns in both the developed and emerging markets unrelated to the attendant risks. Studies on the Indian stock markets' calendar anomalies, especially in the post-reform era, are very few. In an attempt to fill this gap, this study explores the Indian stock market's efficiency in the 'weak form' in the context of calendar anomalies, especially in respect of the weekend effect. Daily returns generated by the SENSEX, NATEX, and BSE200 during January 1st 1996 to August 10th 2002 comprising a total of 1,667 observations for each of the indices are considered for testing the seasonality. While most of the studies have considered the returns of one of the major indices based on the closing values, this study examines the multiple indices for possible seasonality. An analysis of returns' pattern of multiple indices is helpful in identifying the presence or otherwise of the stock market seasonality associated with various portfolios and for testing the efficacy of investment game based on the observed patterns of the returns. This study employed the daily mean index value for generating the daily returns to relax the implied assumption of the earlier studies — by considering the closing values of the indices — that trading is done at the closing values. A non-parametric test — Kruskall-Wallis test using 'H' statistic — is employed for testing the seasonality in the Indian stock market returns. The null hypothesis tested is that there are no differences in the mean daily returns across the weekdays. The major findings of the study are as follows: The Indian stock markets do manifest seasonality in their returns' pattern. The Monday-Tuesday, Monday-Friday, and Wednesday-Friday sets have positive deviations for all the indices. The Monday-Friday set for all the indices has the highest positive deviation thereby indicating the presence of opportunity to make consistent abnormal returns through a trading strategy of buying on Mondays and selling on Fridays. The above-mentioned active strategy is found to be beneficial in case of SENSEX The above-mentioned active strategy is found to be beneficial in case of SENSEX alone during the study period while for the others — NATEX and BSE200 — a passive ‘buy and hold’ strategy is more effective. The study concludes that the observed patterns are useful in timing the deals thereby exploring the opportunity of exploiting the observed regularities in the Indian stock market returns.

Cointegration of Asian Stock Markets: Empirical Evidence from India

2016 ◽  
Vol 6 (2) ◽  
Author(s):  
Beeralaguddada Srinivasa Veerappa
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Causality Test ◽  
Long Run ◽  
Equilibrium Relationship ◽  
Short Run ◽  
Auto Regressive ◽  
Global Stock Markets ◽  
Indian Stock Market

At present stock return is significantly related to other global stock markets. The present paper empirically investigates the short run and long run equilibrium relationship between the stock market of India, Japan Hong Kong, Singapore, Malaysia, China, and Australia monthly data during January 1995 to December 2013. Researcher employs correlation test, multivariate co-integration framework, Vector Auto Regressive error-correction model and Granger causality test with reference to financial up evils in Asia and world viz., Asian crisis (1997/98), financial crisis (2008) Inflation conditions, Natural disasters, financial up evils etc. of long run relationship. Results find that the Indian stock market return is significantly co-integrated with long run and short run situations/causalities in Asian Stock returns.

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