This comprehensive academic assignment focuses on the statistical examination of financial datasets employing R programming language. The objectives encompass reading and managing Excel files, executing t-tests for hypothesis evaluation, conducting ANOVA to compare multiple groups, analyzing residuals from linear regressions, and verifying assumptions like normality of errors. It delves into portfolio performance analysis through metrics such as Sharpe ratio, Jensen's alpha, Treynor index, and information ratio. The assignment further explores stock market theories including the Capital Asset Pricing Model (CAPM), Markowitz Efficient Frontier, and arbitrage pricing theory to assess stock returns and risks. Regression diagnostics are performed using residual plots and QQ-plots, while assumptions of normality for errors are tested via Shapiro-Wilk test. This analysis not only provides insights into financial metrics but also strengthens the understanding of statistical methodologies applied within finance.
![[object Object]](/_next/static/media/star-bottom.7253800d.svg)
