Abstract

The financial market volatility has been a major interest to all the stakeholders of the market especially to the retail investors post 2020. In 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 capture in the construction of the Financial Market Composite Risk Index. The study intends on giving its contribution on the methodological portion of the derivation of appropriate weights to each segment of financial market. 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 nonparametric statistical tool Kruskal Wallis Test, further the pairwise comparation is also preformed to analyze the homogeneity between the types of volatility capture and method of deriving the weights. The results reveal that, GARCH based DEA Composite Risk Index is better exhibiting the volatility of the Indian Financial Markets compared to their counterpart CRI and also having a high co-movement with India VIX.

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