Undergraduate project of the course Business Intelligence for Financial Services (BSc in Computer Science at University of Study in Milan-Bicocca).
In this project, 6 stocks in 3 sectors of different markets (2 stocks in each sector) over the past 10 years are analyzed.
Introduction:
This project focuses on applying Business Intelligence techniques in the financial services sector, with a focus on analyzing and forecasting financial data from various sources, including pandas tools for importing financial data both locally and directly from Yahoo Finance. The dataset includes financial information of companies operating in the technology, automotive, and pharmaceutical sectors. The main phases of the project include:
- Data Acquisition: The project uses pandas tools to import financial data from various sources, including Yahoo Finance, incorporating information on companies in the technology, automotive, and pharmaceutical sectors.
- Statistical Analysis and Forecasting: Once the data is acquired, the project applies a series of statistical and forecasting methods, including ARIMA, SVM, and linear regression, to analyze returns and volatility of financial data.
- Trading Strategies: The project explores various trading strategies, such as moving averages and On-Balance Volume (OBV), and subjects them to backtesting to evaluate their effectiveness over time.
- Portfolio Management: Finally, the project proposes simulation methods and analytics for building optimal portfolios, used to compare the performance of different portfolios over time.
This project provides a practical application of Business Intelligence techniques in the financial services field, offering valuable insights for portfolio management and trading strategy.
Is possible to read more details about the results obtained in the Report(IT version).
This project is licensed under the MIT License - see the LICENSE file for details.