A new index of financial conditions

- We construct a financial conditions index (FCI) using factor models.
- We develop methods to estimate time-varying parameters and model averaging weights.
- Modeling changing coefficients and volatilities is important for forecasting.
- Additionally, the composition of the optimal FCI has changed over time.

We use factor augmented vector autoregressive models with time-varying coefficients and stochastic volatility to construct a financial conditions index that can accurately track expectations about growth in key US macroeconomic variables. Time-variation in the models׳ parameters allows for the weights attached to each financial variable in the index to evolve over time. Furthermore, we develop methods for dynamic model averaging or selection which allow the financial variables entering into the financial conditions index to change over time. We discuss why such extensions of the existing literature are important and show them to be so in an empirical application involving a wide range of financial variables.