My economics training at MIT provided a framework for understanding how macroeconomic forces drive market movements. While stock picking often focuses on company-specific factors, the macro environment sets the tide that lifts or sinks all boats. Econometric analysis helps quantify these relationships.
Leading Indicators for Indian Markets
Through empirical analysis, we've identified several leading indicators that have predictive power for Indian equity markets:
- Credit growth (lag of 2-3 months before market moves)
- Manufacturing PMI components (new orders particularly predictive)
- Foreign portfolio flows (contemporaneous but measurable before market open)
- USD/INR volatility (inverse relationship with equity performance)
- Bond yield spread (10Y-2Y) as a cycle indicator
Vector Autoregression Models
Vector Autoregression (VAR) models are workhorses of macroeconomic forecasting. Unlike simple regression, VAR treats all variables as potentially endogenous—market returns might be predicted by GDP growth, but GDP growth might also be influenced by market performance through wealth effects.
The impulse response functions from VAR models reveal how shocks propagate through the economic system—invaluable for understanding second-order effects of policy changes.
Cointegration and Error Correction
When analyzing long-term relationships between economic variables, cointegration analysis is essential. Two non-stationary series may move together over time even if they diverge in the short run. The Error Correction Model (ECM) captures both the long-run equilibrium and short-run dynamics.
For example, we've found cointegrating relationships between corporate earnings yield and bond yields in India. When the relationship deviates significantly, it creates opportunities for tactical asset allocation.
From Academic to Applied
The challenge in applying econometric models to investment decisions is translating statistical relationships into actionable insights. We focus on:
- Model stability across different time periods
- Economic interpretability of relationships
- Transaction costs and implementation feasibility
- Confidence intervals and scenario analysis