Exploring The Dynamics Of Inflation, Interest Rates, And Bond Yields: A Comprehensive Regression Model Comparison

This research presents a comprehensive analysis of the impact of key macroeconomic indicators, including 10- year Government Securities (10Y GSec) yields, 91-day Treasury Bill (TB) rates, interest rates, inflation, exchange rates, foreign reserves, gold prices, equity market indices (NSE Nifty), FDI, and Month-on-Month (MoM) basis returns, on interest rates, inflation, yields and vice-versa in India, using data from 2018 to 2023. The study employs multivariate correlation analysis to identify the relationships among these variables, revealing significant patterns such as the strong correlation between bond yields and interest rates, as well as the inverse relationship between equity market performance and bond yields. This research highlights the influence of monetary policy, external reserves, inflation, FDI, and equity markets in shaping bond yields and interest rates, with gold and equity markets acting as safe-haven assets during times of economic uncertainty. A key focus of this research is a detailed comparison of five regression models— Ordinary Least Squares (OLS), Heteroscedasticity-Corrected (HSC), Tobit, Logistic, and the Transformed First Difference (FD) OLS—used to analyze the relationships among these macroeconomic variables. The study demonstrates that the HSC and Logistic regressions provide the most robust and reliable insights, with the HSC model exhibiting the highest explanatory power in capturing the variance in bond yields, interest rates, and inflation. The analysis underscores the importance of selecting the right regression model to accurately capture the dynamics of financial markets, as model performance varies significantly. This comprehensive study offers a nuanced understanding of the interplay between macroeconomic indicators and financial outcomes, emphasizing the critical role of regression models in enhancing the accuracy of economic forecasting