Analyzing sector performance and investment strategies: A decade of FTSE data

Ritvik Gupta (), Tharunya Katikireddy () and Eugene Pinsky ()

International Journal of Economics and Financial Modelling, 2025, vol. 10, issue 1, 75-85

Abstract: Data analysis techniques play a pivotal role in extracting meaningful insights from complex datasets, enabling informed decision-making across industries. In this project, we applied these techniques to analyze a decade of historical data from the FTSE (Financial Times Stock Exchange), a prominent index that tracks the performance of major UK-based companies across key sectors. Focusing on five critical sectors—Finance, Technology, Retail, Healthcare, and Basic Resources—we aimed to identify the most stable and least volatile investment opportunities for investors. By categorizing the sectors into Top 3, Middle 3, and Bottom 3 based on performance, time series analysis was utilized to uncover trends and patterns, testing various investment strategies such as buy-and-hold, Top 4, and equal-weight allocation across multiple frequencies, including yearly, bi-yearly, quarterly, and monthly. Through comprehensive visualizations and statistical analysis, we derived actionable insights to help investors optimize their strategies, minimize risk, and maximize returns in a dynamic market environment.

Keywords: FTSE analysis; Investment strategies; Sector performance; Time series analysis; Portfolio optimization; Rebalancing frequency; Risk-adjusted returns; Statistical performance metrics. (search for similar items in EconPapers)
Date: 2025
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