We examine whether latent economic regimes can be identified before they become obvious in asset prices. The framework combines state-space estimation, transition probabilities, volatility structure and macroeconomic variables to distinguish expansion, deterioration and stress regimes.
Commodity shocks rarely transmit uniformly across equity markets. Using local projections and conditional response functions, we study how oil, energy and industrial input shocks propagate through margins, inflation expectations and sector-level equity performance.
Nominal equity prices cannot be interpreted independently of the monetary environment. We test long-run relationships between money supply, financial liquidity, valuation multiples and equity indices using cointegration, error-correction dynamics and rolling parameter estimates.
Hundreds of variables appear predictive in historical samples, but only a fraction remain stable out of sample. We compare regularized cross-sectional models, shrinkage estimators and rolling validation procedures to identify signals that survive changing market environments.
Correlations estimated during normal periods can severely understate relationships during market stress. We investigate conditional volatility, asymmetric dependence and joint tail behavior using GARCH-type processes and copula-based dependence structures.
No single macroeconomic indicator reliably identifies turning points. We combine yield-curve information, credit spreads, labor-market dynamics and financial conditions within a probabilistic framework designed to estimate changes in recession and recovery risk over time.