FINAL MAJOR PROJECT  

Stock Market Analysis 

Mentor: Ms. Sakshi Aggarwal

 Submitted By:

Gauri Bansal (Batch B8) 10104685

ABSTRACT My aim is to develop a website on stock market analysis which will

deal with the role of markets in our daily life and will help the users

to have the opportunity of knowing what is presently happening in

the markets both in India and globally.

The website would display the current news of stock market, latest

trends of various commodities, show the present value of various

indices and calculate the change values.

The website basically aims to advice people about trading through

BSE and NSE. The user can have a complete view of the current

news and markets.

There will be a live sensex index to show the sensex values for

various top companies.

PURPOSE• To help the users in recommending the stocks that would help to to

invest in the market wisely. The users can buy the stocks of any particular company by viewing their historical data and comparing the stock market prices with another company.

• The main purpose of this project is to build a website where user can have a complete view of the current news and markets trends and be recommended what and where to invest based on various Data mining algorithms.

 

SCOPE

Currently there are very less websites, especially in India, that provide complete information on stocks as well as commodities fluctuation information in an integrated form. They provide basic information on stock market.

These websites display lot of updates which leads to the same amount of confusion, above all, the most important updates are submerged beneath all other ordinary updates.

So, I am trying to provide a more user friendly portal with recommendation on investments. These recommendations are based on top grossing, top trending, top gainers, Expert advice , online and offline experts and what are their friend’s up to etc.

Solution Approach In Terms Of Technology Used The comprehensive study of the following areas is consists of my content requirement:Understanding basics of stock marketLive data of stock marketThe concept of recommendationExpert’s opinion (online and offline experts)Facilities provided to the userCharts and graphs generated for the historical data of the companies.Top gainers and losers using Hybrid algorithmPrediction of the pricesCalculation of the EMI ,better investment avenue , savings, monthly reducing rate.Feedback option by the experts.

Implementation details• Collection of data: The .csv files are downloaded from Yahoo

Finance which provides financial news and information and also offers news and information about stock quotes, stock exchange rates, corporate press releases and financial reports, and popular message boards for discussing a company's prospects and stock valuation.

  Data Importing: The .csv files are then imported to the MySQL server so that the database is compatible with PHP and further computations be done.

Recommendation system• Top Grossing: Highest volume of the stock of the companies would be

recommended on the basis of current data. The mean average volume of the companies is calculated.

 • What are your friends Upto: Application of nearest neighbor’s algorithm on

the user's friend's stock buying pattern.  • Top trending: Association rules are applied and corresponding results are

recommended to the user.  • Based on expert advice: Application of nearest neighbor based on CRSP

values where CRSP=number of shares * closing price.  • Stock’s prices: the recommendations would be "Buy " and "Accumulate".

Application of neural network to predict future prices based on historical data.

• Top gainers/ losers : Application of hybrid algorithm.

Calculators

This website has a login option where new registers can register themselves and the existing users can log on using their credentials and can view the historical data of any company and can invest in the stocks recommended to them on the latest stocks purchased by their friends, or by online and offline expert advice . Users could also be recommended on the basis of the various other factors.

NOVELTYThe novelty of this project is that different algorithms have been implemented. K- nearest neighbor algorithm is used where the difference in the CRSP=number of shares * closing price of the current users and different users in noted down. Then Euclidean distance formula is applied on the values so that the neighbor which is nearest to the user recommends him to invest in that stock.Neural network concept is used which gives different weights to stock purchased by user 1 and user 2. This way the algorithm helps in predicting the prices of the stocks and recommending it to the user. This website has an exciting feature of Crawler where Mercator crawler has been used which crawls the yahoo finance news and displays it on the main page. Use of hybrid algorithm for finding out the change in the current prices of the companies.This type of website has never created where the blend of all the algorithms is used.

LIVE MARKET

Design Scenario

1

• Database Upadation• Csv files downloaded from yahoo finance• Stock tables updated to the latest values

2

• User Login• Each user has a login id using which he can access his previous

transactions• Each user has a friend list as well

3

• User can view stock charts, compare with other companies and also view historical data

• Recommender where he can be recommended based on various criteria

4

• Neural Network: feed the network with past values as well as result of test data set

• A generalized result is obtained by giving weightage to different parameters

Existing Approach 

The approach adopted in this paper firstly creates user profile

based on the documents viewed by the user. It is discussed in

detail in literature. Each user profile is represented as a

concept tree. Traditional methods represent user profile as

keyword word vector. However, the keyword vectors can be

extremely sparse and it also suffers from the problem of

semantic ambiguity. Then, the correlation strength between

users is computed using tree-edit distance. Finally, the

spreading activation model is employed to search for users

those have similar interests with target user. The strength of

spreading activation model lies in its ability to analyze the

relationship among users based on correlation strength. 

User Profile-Based PersonalizedResearch Paper Recommendation System

Predicting the future price and recommending the user where he should accumulate his previous stocks or purchase the new ones . This relies on the concept of neural networks which help in predicting forecast based on the historical data.

Apart from the recommender system, the user can also use other features of the website such as comparison of stocks, viewing the past data or even analyzing data using graphs and charts. Charts are formalized into trading rules or are used in neural networks to predict the future stock prices.

Comparison of Vodafone with TTM from year 2013 to 2014

Comparison of Vodafone from year 2013 to 2014

Future Recommendation System

I believe that apart from the indicators used here, various other factors can also be considered for the recommendations. The short term and long term investment patterns and user will can be further looked upon. A wide range of companies can be included so that users from different domains are also benefitted from my website. The project can further be extended for countries other than India. There can be a live Sensex index to show the Sensex values for various top countries. A large dataset of the users could be added which could help the user to choose the stocks of the company by the historical data of the other users and their preference.

CONCLUSIONI have developed a website on Investment Portal which deals with the role of markets in our daily life. The website would help the people or users to have the opportunity of knowing what is presently happening in the markets both in India and globally.

The user would be recommended based on the type of investment of the user- short term or long term. The user would be recommended on the option he chooses. Suppose if he chooses top grossing then he would be recommended on the highest volume of the company . Users can also see their friends activity and can see how many shares they are have purchased and could be recommended on the basis of k nearest algorithm.

The website displays the current news of stock market, latest trends of various commodities, like converting from one currency to another and also shows the present value of various indices . It also crawls the news from yahoo finance through Mercator crawler

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2004

THANK YOU!