Monetary Policy Surprises and Their Effects on Financial Markets

This thesis investigates how monetary policy surprises affect the distributional dynamics of both financial markets (SP500) and financial indicators, such as the VIX, the term spread between the 10-Year and 3-Month Treasury Constant Maturity rates (T10Y3M),the excess bond premium (EBP) and the National Financial Conditions (NCFI). The analysis distinguishes between two types of monetary policy shocks: MPS shocks, which capture unexpected changes in policy rates orthogonal to information releases, and INFO shocks, which reflect adjustments driven by changes in the central bank’s information set. These are examined across multiple forecast horizons, allowing for a detailed assessment of their differential impact on financial variables. The empirical strategy is based on quantile regression (QR), which models the full conditional distribution of financial variables capturing both central tendencies and tail risks, the QR framework is augmented with latent factors extracted via a Dynamic Factor Model (DFM), which summarizes the common variation from a large panel of U.S. time series. Predictive quantiles obtained from the QR are then mapped into full predictive distributions through density matching using skewed-t distributions, enabling the analysis of skewness, entropy,expected shortfall/longrise and measures of tail risk.