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Financial market volatility has been a major interest to all the market stakeholders, especially retail investors, since 2020. Against this backdrop, the study is focused on constructing a Composite Risk Index (CRI) for the Indian Financial Market and examining the various methods of weighting as well as types of volatility captured in the construction of the Financial Market Composite Risk Index. The study intends to contribute to the methodological portion of the derivation of appropriate weights for each financial market segment. The study is based on the daily price series from 1st January 2020 to 31st March 2023. The research develops nine (09) different Composite Risk Index based on the types of volatility capture [Standard Deviation (SD), Autoregressive Conditional Heteroskedastic (ARCH), Generalised Autoregressive Conditional Heteroskedastic (GARCH)] and method of deriving the weights [Principal Component Analysis (PCA), Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA)] of various sub-markets [ Equity, Commodity and Forex] and its segments [Spot and Derivatives]. The inter and intra-evaluation of nine CRI are carried out with the help of the nonparametric statistical tool Kruskal Wallis Test; further, the pair-wise comparation is also performed to analyse the homogeneity between the types of volatility capture and method of deriving the weights. The results reveal that the GARCH-based DEA Composite Risk Index better exhibits the volatility of the Indian financial markets compared to their counterpart CRI and also has a high co-movement with India VIX.