4_Data Mining Predictive Analysis of Stocks_6MinuteDream

Project Name: Predictive Modelling of Stock Markets

Team Number: 4 (G Raviteja, Manmohan Agarwal, Ankit Gupta, D Sushanth Reddy)

Team Name: El Matador

Problem Statement: What is the effect of the change in the price of a particular stock over other stocks present in a particular Index or over various indexes or for that matter over different markets, over different time periods?

Data Source: BSE SENSEX and NIFTY websites provide an ample resource of daily stock related data for any individual stock. Also the data could be obtained from the financial portals like moneycontrol.com

The Benefit / Utility: The data analysis would reveal patterns of correlation between individual stocks. The correlation could be positive or negative or even neutral. The correlation patterns obtained could be a base for different types of investors in making their financial investments. The target set of investors could be an individual investor, an institutional investor, an investment bank, a hedge fund firm, a PE player, and market regulators like SEBI etc.

Individual Investor – Individual investors, by nature of being risk averse, would like to invest or park his money in safer stocks. If he/she is confident that a particular stock is safe to invest in, the analysis would provide him with a option of a diversified portfolio wherein he can hedge his risk.

Institutional Investor – Institutional investors create a portfolio of different set of stocks i.e they try to invest their money into stocks from different sectors, stocks of companies of different sizes etc. Our analysis could provide a stronger foundation to the investment decisions of the institutional investors and also allow them to plan their investments in a way that they could minimise their risk.

Hedge Funds – Hedge funds usually offset their potential losses by hedging their investments, notably by short selling. Since we are analysing stock correlations across different time periods, we feel that the short term data analysis would be helpful for such companies.

Market Regulators – The market regulators could keep a track on the movement of shares and an uneven spike or a correlation that is not normal could be investigated.

Expected Outcomes: The relationships between stocks are either positively, negatively or neutrally correlated to each other as an exhaustive set. The outcome gives as an overview of how different stocks change in their relation to other stocks in different length of time, across different parameters, different markets. It provides you with an overall bird’s eye view as well as a very specific view as what happens to the change in a particular day for a particular stock. The outcome would be an exhaustive set which caters to any kind of requirements for any kind of users who play in the equity markets. This model may be further extended to even derivative markets which are now a days termed as the ‘Weapons of Mass Destructions’ and can be used as a effective defensive tool against them.