This paper aims to develop a financial cycle for India by aggregating key financial indicators from different sectors of the financial system and then comparing it with the business cycle to understand the macroeconomic implications.
The research uses various econometric tests to analyze the relationship among the financial indicators before applying the principal component analysis and filtering technique to extract the aggregate financial cycle. After this, the dynamic conditional correlation – generalized autoregressive conditional heteroscedasticity model is applied to understand how it interacts with the economy.
The result of this study creates an aggregate financial cycle that effectively reflects the most influential components of the financial system, empowering policymakers to measure and safeguard the stability of the financial system and economy.
The authors’ contribution lies in the systematic integration of key indicators into a comprehensive aggregate financial cycle for India, which has not been thoroughly explored in existing research. This study also emphasizes the significance of banking sectors and other financial intermediaries that were undermined in the existing financial cycle studies.
