Perspective of the Behaviour of Retail Investors: An Analysis with Indian Stock Market Data

2019 ◽  
pp. 605-616
Author(s):  
Abhijit Dutta ◽  
Madhabendra Sinha ◽  
Padmabati Gahan
Keyword(s):  
Stock Market ◽  
Market Data ◽  
Retail Investors ◽  
Indian Stock Market

A Study of Union Budget Impact on Indian Stock Market

2016 ◽  
Vol 11 (01) ◽  
Author(s):  
Ashish Kr. Jha
Keyword(s):  
Stock Market ◽  
Institutional Investors ◽  
Budget Impact ◽  
Fiscal Deficit ◽  
Weight Estimation ◽  
Economic Event ◽  
Volatility Index ◽  
Retail Investors ◽  
Foreign Institutional Investors ◽  
Indian Stock Market

This study focused on the event of Union budget on Indian stock market, the analysis has been made between a periods of 2012- 13 to 2015-16. Union Budget is considered to one of the major economic event which takes place every year. The direction of Indian economy is drafted by government of India through Union Budget. Volatility index (Vix) of the index was observed high throughout the month of February every year. Sharp differential Measures indicate that the performance of market goes to one direction after budget announcement and its analysis by the investors. Regression weight estimation initiated that Indian growth is influenced by the fiscal deficit. This analysis is useful for the equity investors namely Retail investors, Domestic Institutional investors (DII), Foreign Institutional Investors (FII) etc.

Clustering Indian stock market data for portfolio management

2010 ◽  
Vol 37 (12) ◽  
pp. 8793-8798 ◽  
Author(s):  
S.R. Nanda ◽  
B. Mahanty ◽  
M.K. Tiwari
Keyword(s):  
Stock Market ◽  
Portfolio Management ◽  
Market Data ◽  
Indian Stock Market

scholarly journals An intelligent indian stock market forecasting system using LSTM deep learning

2021 ◽  
Vol 21 (2) ◽  
pp. 1082
Author(s):  
K Kumar ◽  
Dattatray P. Gandhmal
Keyword(s):  
Deep Learning ◽  
Stock Market ◽  
Optimization Algorithm ◽  
Learning Algorithm ◽  
Stock Exchange ◽  
Market Data ◽  
Deep Learning Algorithm ◽  
Area Of Interest ◽  
Accuracy Of Prediction ◽  
Indian Stock Market

<p><span>Stock market data is considered to be one of the chaotic data in nature. Analyzing the stock market and predicting the stock market has been the area of interest among the researchers for a long time. In this paper, we have stepped forward and used a deep learning algorithm with classification to predict the behavior of the stock market. LSTM deep learning algorithm is used with an optimization algorithm to formulate the hyperparameters. To further improve the accuracy of prediction the stock data is first given to a classification algorithm to reduce the number of input parameters. In this research Technical indicators are subjected to classification and deep LSTM algorithm which are both integrated to improve the accuracy of prediction. Deep LSTM hyperparameters are trained using the optimization algorithm. In this paper infosys and zensar stocks data is collected from the Indian stock market data i.e. both national stock exchange (NSE) and bombay stock exchange (BSE). The proposed approach is applied on infosys and zensar share values, the prediction accuracy obtained by employing this integrated approach of classification and LSTM has given a prominent value of MSE and RMSE as 1.034 and 1.002 respectively. </span></p>

Investors' preferences and the factors affecting investment in the Indian stock market: an industry view

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bhaskar Chhimwal ◽  
Varadraj Bapat ◽  
Sarthak Gaurav
Keyword(s):  
Stock Market ◽  
Random Effect ◽  
Investment Decisions ◽  
Macroeconomic Factors ◽  
Content Type ◽  
Factors Affecting ◽  
Large Numbers ◽  
Retail Investors ◽  
Service Oriented ◽  
Indian Stock Market

PurposeThe authors examine the industrywise investment preferences of foreign portfolio investors (FPIs), domestic institutional investors (DIIs) and retail investors in the Indian context. They also investigate the factors influencing their preferences.Design/methodology/approachUsing the quarterly shareholdings and returns data of the Indian market from March 31, 2009 to March 31, 2018, the authors employ analysis of variance to study investors' preferences and a random effect panel data model to examine the factors that influence these preferences.FindingsFPIs hold proportionally more stocks in service-oriented industries and large-cap firms, DIIs hold proportionally large numbers of shares in paper industries and retail investors hold proportionally more shares in chemicals and textiles. FPIs prefer stocks with a high export-to-sales ratio and firms registered on a foreign stock market. Domestic investors, especially retail investors, prefer small-cap stocks and firms whose operations require local knowledge. In addition, industry heterogeneity determines investment decisions. Firm-specific and macroeconomic factors that influence investment decisions differ across industries. Finally, government policies and reforms also play a key role in attracting investors.Practical implicationsPolicymakers can identify the key variables that influence investment, which can help direct and regulate investment in India and similar emerging markets.Originality/valueThis study fills a research gap by addressing how industry-level heterogeneity affects investors' preferences in terms of the industrywise preferences of different types of investors and the factors that influence their preferences.

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