SomweJoel/Predictive-Time-Series-Model-Case-Study-NSE-Kenya-20-Share-Index

# Predictive Time Series Model Case Study NSE Kenya 20 Share Index ### Team Members: 1. Whitney Ngili 2. Catherine Chelagat 3. Gibson Wanjau 4. Bella Somwe 5. George Mungai ## Introduction The Nairobi Securities Exchange (NSE) is the principal securities exchange of Kenya, providing a platform for the buying and selling of various financial instruments, including stocks, bonds, and derivatives. The NSE is a key player in the East African capital markets, attracting local and international investors who seek to capitalize on the investment opportunities presented by the growing Kenyan economy. The NSE 20 Share Index, launched in 1953, is one of the most widely followed stock market indices in East Africa, comprising the top 20 blue-chip companies listed on the NSE. The index serves as a benchmark for the overall performance of the Kenyan stock market and provides investors with an indication of the market sentiment and direction. With the advent of technology and the availability of vast amounts of financial data, investors are increasingly turning to quantitative analysis and machine learning techniques to predict stock prices and generate alpha. In this project, we aim to develop a predictive time series model to forecast the stock prices of companies listed in the NSE, using a range of market-specific factors as inputs. Our target partners for this project include SACCOs, insurance companies, and pension funds, who are important players in the Kenyan financial market. By developing a reliable time series model to forecast stock prices, we hope to provide our partners with valuable insights that can inform their investment decisions and enable them to optimize their portfolio returns. The project will involve collecting and analyzing historical stock prices and market-specific factors, exploring the various time series models available, and developing and evaluating the performance of the selected model. The results of the project could provide valuable in …