Financial Analysis Software for Trading

Stock traders usually left unaware of the rapid stock market?s changing trends and figures. They face the problem of efficient stock trade in order to gain more profit. Financial analysts do know that the stock market trends highly depend upon relevant vast amount of global news and information.

Project Title

Financial Analysis Software for Trading

Project Area of Specialization

Software Engineering

Project Summary

Stock traders usually left unaware of the rapid stock market’s changing trends and figures. They face the problem of efficient stock trade in order to gain more profit.
Financial analysts do know that the stock market trends highly depend upon relevant vast amount of global news and information. Considering the assumptions that updated news articles might give much better predictions of the stock market. We would develop a system which would be able to model the reaction of stock market to news articles and predict their reactions. By doing so, the investors would be
able to foresee the future behavior of the stock market when relevant news are released and act immediately upon it.
It’s a web based application. The application utilizes the concepts of Machine Learning, Natural language processing, Sentimental analysis and Data mining.
 

Project Objectives

The project aim is to create web application that analyses
previous stock data of companies and implement these values in data mining algorithm to determine the value that particular stock will have in near future with suitable accuracy. The project will be useful for investors to invest in stock market based on the various factors i.e.
? To generate the pattern from large set of data of stock market for prediction
? To predict an approximate value of share price
? To provide analysis for users through web application
? To Provide Sentimental analysis of Data
These predicted and analyzed data can be used to know the
financial status of companies and their comparisons. Company and industry can use it to breakdown their limitation and enhance their stock value for their company. It can be very useful to even researchers, stock brokers, industrials market makers, government and general people. We will determine the patterns in data with help of data mining algorithms.
 

Project Implementation Method

Proposed Solution

It’s a web-based application. The application utilizes the
concepts of Machine Learning, Natural language processing, Sentimental analysis and Data mining. Through this web application they would see the future behavior of the stock market when relevant news is released and act immediately upon it. The investors would be able to foresee the future behavior of the stock market when relevant news is released and act immediately upon it which we provide to data analysis, sentimental and prediction.

Methodology
The purposed method for developing the system consists of
main three steps. Firstly, data is collected and sorted for relevancy from various sources. Secondly, analysis is carried out on the collected data by examining the current market direction, tracking the industry group and specific companies after which the data is represented and scored accordingly. At last, a suitable algorithm yielding best accuracy is chosen to predict the stock value.
This project attempts to predict the stock value with respect to the stock market previous value and trends. It requires historic data of stock market previous value and trends as the project also emphasizes on data mining techniques. The stock market is a very fluctuating(market ups and down). There are many companies of different sectors and the values as well as parameters can vary differently in time. In our purposed system, there is a training phase where some parameters named weights are found from this section and Backpropagation Algorithm is used for this training phase. These weights are used in prediction. The collected data are arranged according to the format for the library we use for trainings
 

Benefits of the Project

Stock Market Analysis of stocks using data mining and machine learning will be useful for new investors to invest in stock market based on the various factors like forecasting and prediction. Stock market includes daily activities like calculations, exchange of shares. The exchange provides an efficient and transparent market for trading in equity its relative derivatives. Our software will be analyzing company’s stock value. The stock values of company depend on some of the following these factors:
• Dollar value: The fluctuations in the dollar value day by day will be playing crucial part in the stock values of companies basically for I.T based companies and the impact of dollar values will be different for different companies.
• Corporate results: This will be regarding to the profits or loss of the company over a span of time.
• Inflation: This is the overall rise in price of all the products which affects purchasing power. The stock value depends on other factors as well, but we focused only these particular factors which are discussed above.
 

Technical Details of Final Deliverable

Analysis:
By using real time news data from different online sources. We will analyze sentiments of different news to decide the outcome as positive, negative or neutral. We will also analyze the potential impact of news on the stock trends. Our algorithm will predicts based on this analysis. For this purpose, we will use the concepts of Natural language processing and sentiment analysis. We will also take in consideration the experience of stockbrokers and agents.
Forecast:
The system would be able to forecast market trends using historical data and trends. The system would
be trained to forecast possible stock market trends for future. We will fetch data from different online platforms and will be classified based on the previous data classes in the system. This market forecast has potential significant benefits of gaining more profit for stock traders.
Advice:
Based on analysis and forecast, our system will give an advice to potential investors. What possible trends
markets will follow based on our analysis and predictions. The stock trader would be able to decide whether he should invest or not based on advice given by our system. Also, it will include the warnings and possibilities of stock market trends.
Research Paper:
We will write a research paper as an outcome of this research oriented FYP. We will use standard news dataset to train different conventional and deep learning classifiers for prediction. We will thoroughly investigate the performance of each classifier for predicting the behavior of PSX. We aim to publish our research work in a quality conference or journal.
 

Final Deliverable of the Project

Hardware System

Core Industry

Finance

Other Industries

IT

Core Technology

Big Data

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Decent Work and Economic Growth

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com