Financial Stress Index for India (India–FSI)

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We are pleased to host the new Financial Stress Index for India (India-FSI) developed by Aswini Kumar Mishra, Nishad Kotkar, and Atharva Singh Rathore in Macro-financial shocks and search sentiment: A new Financial Stress Index for India. Their index reflects internet search sentiment extracted from Google Trends for core financial distress terms in India, covering the period from July 2006 to March 2026.

Construction

The India–FSI captures financial distress across four dimensions: (i) banking and liquidity distress, (ii) market panic and volatility, (iii) corporate and sovereign distress, and (iv) external-sector stress.

An initial pool of 52 financial-distress search terms was identified across these dimensions. Principal Component Analysis (PCA) was used to reduce redundancy, resulting in 20 core keywords: 11 related to banking and liquidity, 4 to market panic and volatility, 4 to corporate and sovereign distress, and 1 to external-sector stress. The complete classification is provided in Online Appendix, Table A1.

Weekly Google Trends data for India are collected for each keyword and normalized against the benchmark search term “economy” to account for changes in overall search intensity. Each query is repeated three times, with the median retained to reduce sampling variation. The resulting series are winsorized at the 99th percentile and aggregated to monthly frequency.

The 20 keywords are combined using a TF–IDF-style anchor-term weighting scheme, which assigns relatively greater weight to less frequent terms that become strongly activated during distress episodes. The weighted series are aggregated to form the raw India–FSI. The index is then seasonally adjusted using X-13 ARIMA-SEATS where available, or robust STL decomposition otherwise. Finally, the one-sided Hamilton (2018) regression filter is applied to extract the cyclical component while avoiding reliance on future observations.

Interpretation

The India–FSI is a relative measure of financial stress. Higher values indicate unusually elevated search interest in financial distress relative to the estimated trend, while lower values indicate comparatively subdued financial stress. The index is updated regularly at a monthly frequency, allowing it to provide a timely measure of changing financial-stress conditions.

Source: Mishra, A. K., Kotkar, N., & Rathore, A. S. (2026). Macro–financial shocks and search sentiment: A new financial stress index for India. Finance Research Letters, Vol. 112, 110748. https://doi.org/10.1016/j.frl.2026.110748. The keyword classification and PCA reduction are documented in the Online Appendix, Table A1.