This chapter explores econometric modeling techniques for assessing market risk in equity-based investments, which are inherently subject to price fluctuations. Investors and researchers alike seek to evaluate and compare market risk while computing risk-adjusted returns for index funds. The chapter introduces key risk measures, including Value at Risk (VaR), Expected Shortfall, Median Shortfall, Sharpe ratio, and Treynor ratio. It further discusses estimation approaches for these measures using historical asset price data, covering both parametric and nonparametric techniques, with a particular focus on Extreme Value Theory (EVT). Additionally, the chapter examines time series modeling methods, specifically the GARCH and MSGARCH models. Finally, it presents back-testing procedures to evaluate the performance of these models in an out-of-sample context. The methodologies are applied to real data from the Indian equity market, with all empirical analyses conducted using the R programming language.