Diffusion entropy analysis and random matrix analysis of the Indian stock market

2020 ◽  
Vol 560 ◽  
pp. 125122
Author(s):  
Sushil Kumar ◽  
Sunil Kumar ◽  
Pawan Kumar
2019 ◽  
Vol 8 (4) ◽  
pp. 9358-9362

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.


2016 ◽  
Vol 450 ◽  
pp. 462-465 ◽  
Author(s):  
Shouwei Li ◽  
Yangyang Zhuang ◽  
Jianmin He

2017 ◽  
Vol 16 (02) ◽  
pp. 1750018 ◽  
Author(s):  
Rui-Qi Han ◽  
Wen-Jie Xie ◽  
Xiong Xiong ◽  
Wei Zhang ◽  
Wei-Xing Zhou

The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 Chinese stocks. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks’ capitalizations.


Think India ◽  
2014 ◽  
Vol 17 (3) ◽  
pp. 22-24
Author(s):  
Sreekumar Ray

Since inception, the growth of the Indian stock market has been constrained through unethical, illegal and self-actualized activities of swanky persons involved in different capacities in the market. The stock market was trying to retrieve itself from the devastating effect of Harshad Mehta share market scam, when within a gap of ten years it was once again pushed into the darkness of the dungeon by another demon-child of the country- Ketan Parekh. Corporations have been looted by the insider traders, diversifying internal information to an external in lieu of cash. Investigations in the majority cases have proved the involvement of the high ranking officers of the companies in the crime, sophistically referred to as white-collar crime. It has an adverse impact on the growth and sustainability of the share market. Under the light of the above issue, this paper endeavors to study the impact of such crime on the share market. It focuses on the mechanism behind the insider-trading, its impact on the share market and the regulators supervision on the issue. Finally, suggestions have been provided which will contribute towards the dream of every Indian-a fraud-free share market focusing towards the overall development of the country.


GIS Business ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. 1-9
Author(s):  
Gunjan Sharma ◽  
Tarika Singh ◽  
Suvijna Awasthi

In the midst of increasing globalization, the past two decades have observed huge inflow of outside capital in the shape of direct and portfolio investment. The increase in capital mobility is due to contact between the different economies across the globe. The growing liberalization in the capital market leads to the growth of various financial products and services. Over the past decade, the Indian capital market has witnessed numerous changes in the direction of developing the capital markets more robust. With the growing Indian economy, the larger inflow of funds has been fetched into the capital markets. The government is continuously working on investor’s education in order to increase retail participation in the Indian stock market. The habits of the risk-averse middle class have been changing where these investors started participating in the Indian stock market. It is an explored fact that human beings are irrational and considering this fact becomes imperative to investigate factors that influence the trading decisions. In this research, ‘an attempt has been made to investigate various factors that affect the individual trading decision’. The data has been collected from various stockbroking firms and from clients of those stockbroking firms their opinions were recorded by means of a questionnaire. Data collected through the structured questionnaire, 33 questions were prepared which was given to the 330 respondents on the basis of convenience sampling out of which 220 individuals filled questionnaire, the total of 200 questionnaires was included in the study after eliminating the incomplete questionnaire. Various factors are being explored from the literature and then with the help of factor analysis some of the most influential factors have been explored. Factors like overconfidence, optimism, cognitive bias, herd behavior, advisory effect, and idealism are the factors which influenced the trading decision of the investors the most. Such kind of a study is contributing in the area of behavioral finance as a trading decision is an important aspect while investing in the stock market. And this kind of study would be helping and assisting financial advisors to strategies for their clients in making the right allocation and also the policy maker and market regulators to come up with better reforms for the Indian stock markets.


GIS Business ◽  
2017 ◽  
Vol 12 (6) ◽  
pp. 1-9
Author(s):  
Dhananjaya Kadanda ◽  
Krishna Raj

The present article attempts to understand the relationship between foreign portfolio investment (FPI), domestic institutional investors (DIIs), and stock market returns in India using high frequency data. The study analyses the trading strategies of FPIs, DIIs and its impact on the stock market return. We found that the trading strategies of FIIs and DIIs differ in Indian stock market. While FIIs follow positive feedback trading strategy, DIIs pursue the strategy of negative feedback trading which was more pronounced during the crisis. Further, there is negative relationship between FPI flows and DII flows. The results indicate the importance of developing strong domestic institutional investors to counteract the destabilising nature FIIs, particularly during turbulent times.


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