Compound volatility processes in EMS exchange rates

This paper introduces a compound GARCH/markov switching model to add flexibility to the GARCH model in order to model the volatilities of exchange rates in target zones subject to realignments. The compound volatility model endogenizes the weights given to realignments (and all other shocks) in the GARCH process. Previous GARCH applications to EMS exchange rates took polar positions by arbitrarily placing full or zero weight on realignment shocks. Markov switching in the student-t degrees-of-freedom parameter is shown to make the difference between rejection and acceptance of goodness-of-fit tests for four of the six EMS currencies studied.Foreign exchange rates

Conditional heteroskedasticity in qualitative response models of time series: a Gibbs sampling approach to the bank prime rate

Previous time series applications of qualitative response models have ignored features of the data, such as conditional heteroskedasticity, that are routinely addressed in time-series econometrics of financial data. This article addresses this issue by adding Markov-switching heteroskedasticity to a dynamic ordered probit model of discrete changes in the bank prime lending rate and estimation via the Gibbs sampler. The dynamic ordered probit model of Eichengreen, Watson and Grossman (1995) allows for serial autocorrelation in probit analysis of a time series, and the present article demonstrates the relative simplicity of estimating a dynamic ordered probit using the Gibbs sampler instead of the Eichengreen et al. maximum-likelihood procedure. In addition, the extension to regime-switching parameters and conditional heteroskedasticity is easy to implement under Gibbs sampling. The article compares tests of goodness of fit between dynamic ordered probit models of the prime rate that have constant variance and conditional heteroskedasticity.Prime rate ; Econometric models

Spring of disconnect across stock markets?

Stock market ; Rate of return

Why predict past FOMC actions?

Federal Open Market Committee

Risk premiums among corporate bonds

Corporate bonds

The preemptive Fed

Monetary policy

Kalman filtering with truncated normal state variables for Bayesian estimation of macroeconomic models

A pair of simple modifications-in the forecast error and forecast error variance-to the Kalman filter recursions makes possible the filtering of models in which one or more state variables is truncated normal and latent. Such recursions are broadly applicable to macroeconometric models, such as vector autoregressions and estimated dynamic stochastic general equilibrium models, that have one or more probit-type equation.Macroeconomics - Econometric models

Can nominal GDP targeting rules stabilize the economy?

Gross domestic product ; Money supply