Research Dataset and Analytical Framework for Developing the Dynamic Risk Resilience Index (DRRI): Indian Hybrid Mutual Funds (2007–2026)

This dataset provides the complete research materials supporting the development of the Dynamic Risk Resilience Index (DRRI) for evaluating mutual fund resilience under market stress conditions. The dataset contains historical market data, processed analytical files, computational codes, statistical outputs, and publication-ready results used in the study titled “Beyond Risk-Adjusted Returns: Developing a Dynamic Risk Resilience Index for Mutual Fund Evaluation Under Market Stress — Evidence from Indian Hybrid Funds (2007–2026)”. The dataset is based on historical Net Asset Value (NAV) data of Indian hybrid mutual funds covering the period 2007–2026. The data captures multiple market stress phases, including major market downturns and recovery periods, enabling analysis of fund behaviour across different volatility regimes. The dataset includes the original collected NAV records, cleaned and transformed datasets, drawdown event identification outputs, recovery analysis results, DRRI component calculations, fund-level resilience scores, rankings, classifications, and investor-oriented resilience profiles. The DRRI framework evaluates mutual fund resilience through three complementary dimensions: risk resistance, recovery capability, and stability. The dataset includes the intermediate calculations used to derive these dimensions through drawdown-based risk assessment, recovery efficiency measurement, and consistency evaluation. The final composite DRRI score enables comparative assessment of mutual funds based on their ability to withstand market shocks, recover losses, and maintain stable performance behaviour. The repository also contains the complete analytical workflow, including Python scripts/notebooks used for data preprocessing, event identification, metric calculation, index construction, statistical analysis, and generation of tables and figures presented in the research article. The inclusion of raw data, processed datasets, codes, and analytical outputs supports transparency, reproducibility, and further application of resilience-based approaches in mutual fund evaluation. This dataset can be used by researchers, academicians, investment analysts, asset management professionals, and policymakers interested in financial resilience measurement, mutual fund evaluation, downside risk analysis, and composite index development. Keywords: Dynamic Risk Resilience Index; Mutual Funds; Financial Resilience; Market Stress; Drawdown Analysis; Recovery Capability; Composite Index; Hybrid Funds; Investment Risk Assessment.