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 Unsupervised Learning Based Stock Price Recommendation using Collaborative Filtering

2019 ◽  
Vol 8 (11) ◽  
pp. 2051-2055
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Collaborative Filtering ◽  
Portfolio Management ◽  
Recommender System ◽  
Stock Price ◽  
Stock Exchange ◽  
Performance Measure ◽  
Machine Learning Algorithms ◽  
Market Data

In this study, 17 stock market data were adopted for long term Prediction of stock price. Now days, Stock market data have got a significant role for invest finance in portfolio management. The various non-linear algorithms and statistical models are used for forecasting of financial data. In this article, we have used application of recommender system for this purpose. We primarily focused on use of machine learning algorithms for developing a stock market data recommender system. Machine learning has become a widely operational tool in financial recommendation systems. Here we considered the daily wise equity trading of Nifty 50 from National Stock Exchange (NSE) of 50 companies in 10 different sectors around 5986 days’ transactions as data. We adopted k-Nearest Neighbors classification algorithm to classify users based recommender system. Collaborative filtering method uses for recommend the stock, the performance measure through RMSE, and R2. The result also reveals that k-NN algorithm shown more accuracy as compare to other existing methods

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>

scholarly journals Securities Analysis and Portfolio Management of Selected NSE Securities

2021 ◽  
pp. 540-543
Author(s):  
Prof. (Dr) Pramod Sharma
Keyword(s):  
Stock Market ◽  
Portfolio Management ◽  
Intrinsic Value ◽  
Technical Analysis ◽  
Future Price ◽  
Market Participants ◽  
Major Market ◽  
Price Trends ◽  
Indian Stock Market ◽  
A Company

“Technical Analysis is the study of data generated by the action of markets and by the behaviour and psychology of market participants and observers”: -Constitution of the market technicians Association Technical analysis is a completely different approach to stock market investing- it doesn’t try to find the intrinsic value of a company or try to find whether a share is mispriced or undervalued. "Technical analysis is the study of market action, primarily through the use of charts, for the purpose of forecasting future price trends. “A technical analyst is interested only in the price movements in the market. So, it is all about analysing the demand and supply or a price volume analysis. Technical analysis considers only the actual price behaviour of the market or instrument, based on the premise that price reflects all relevant factors before an investor becomes aware of them through other channels. These stock market indicators would help the investor to identify major market turning points. This paper examines the technical analysis of selected companies which helps to understand the price behaviour of the shares, the signals given by them and to assist investment decisions in the Indian stock Market.

scholarly journals Optimizing Stock Market Returns during Global Pandemic Using Regression in the Context of Indian Stock Market

2021 ◽  
Vol 14 (8) ◽  
pp. 386
Author(s):  
Pradip Debnath ◽  
Hari Mohan Srivastava
Keyword(s):  
Stock Market ◽  
Portfolio Management ◽  
Stock Exchange ◽  
Real Life ◽  
Third Wave ◽  
Stock Market Returns ◽  
Global Pandemic ◽  
Proposed Model ◽  
Real Life Situation ◽  
Indian Stock Market

Stock markets around the world experienced a massive collapse during the first wave of COVID-19. Roughly in the month of January 2021, the second wave of COVID-19 struck in India, reaching its peak in May, and by the end of May, the active cases started to decline. A third wave is again predicted by the end of 2021, and as such, the COVID-19 pandemic seems to have become a periodic phenomenon over the last couple of years. Therefore, the study of the behavior of the stock market as well as that of the investors becomes very interesting and crucial in this highly volatile and vulnerable market trend. Motivated by these facts, in the present paper, the researcher develops a model for portfolio management, using curve-fitting techniques and shows that this model can encounter the market volatility efficiently in the context of the Indian stock market. The portfolio is designed based on data taken from the National Stock Exchange (NSE), India, during 1 January 2020 to 31 December 2020. The performance of the portfolio in real-life situation during 1 January 2021 to 21 May 2021 is examined, assuming investments are made according to the proposed model.

Insider Trading: A White-Collar Crime and its Impact on Share Market

Think India ◽  
2014 ◽  
Vol 17 (3) ◽  
pp. 22-24
Author(s):  
Sreekumar Ray
Keyword(s):  
Stock Market ◽  
Insider Trading ◽  
White Collar Crime ◽  
White Collar ◽  
Adverse Impact ◽  
High Ranking ◽  
Internal Information ◽  
Indian Stock Market ◽  
The Impact

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.

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