Real options with priced regime-switching risk

We develop a model of regime-switching risk premia as well as regimedependent factor risk premia to price real options. The model incorporates the observation that the underlying risky income streams of real options are subject to discrete shifts over time as well as random changes. The presence of discrete shifts is due to systematic and unsystematic risk associated with changes in business cycles or in economic policy regimes or events such as takeovers, major changes in business plans. We analyze the impact of regime switching behavior on the valuation of projects and investment opportunities. We find that accounting for Markov switching risk results in a delay in the expected timing of the investment while the regime-specific factor risk premia make the possibility of a regime shift more pronounced

Asymmetric effects of monetary policy in the United States

This paper tests for the presence of asymmetric effects of monetary policy on output. The asymmetries that the authors examine are related to the size and sign of monetary policy shocks and are based on economic theory. Using M1 as the basis for measuring monetary policy shocks, they find evidence in line with previous evidence of larger real effects resulting from positive shocks than from negative shocks—although the authors cannot reject symmetry either. However, using the federal funds rate instead, a measure that is more closely related to the actual conduct of monetary policy, they find that only small negative shocks affect real aggregate activity. The results are interpreted in terms of menu-cost models.Monetary policy ; Macroeconomics

Multivariate Markov switching with weighted regime determination: giving France more weight than Finland

This article deals with using panel data to infer regime changes that are common to all of the cross section. The methods presented here apply to Markov switching vector autoregressions, dynamic factor models with Markov switching and other multivariate Markov switching models. The key feature we seek to add to these models is to permit cross-sectional units to have different weights in the calculation of regime probabilities. We apply our approach to estimating a business cycle chronology for the 50 U.S. States and the Euro area, and we compare results between country-specific weights and the usual case of equal weights. The model with weighted regime determination suggests that Europe experienced a recession in 2002-03, whereas the usual model with equal weights does not.Business cycles ; France ; Finland

Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting

This paper proposes a contemporaneous smooth transition threshold autoregressive model (C-STAR) as a modification of the smooth transition threshold autoregressive model surveyed in Teräsvirta (1998), in which the regime weights depend on the ex ante probability that a latent regime-specific variable will exceed a threshold value. We argue that the contemporaneous model is well-suited to rational expectations applications (and pricing exercises), in that it does not require the initial regimes to be predetermined. We investigate the properties of the model and evaluate its finitesample maximum likelihood performance. We also propose a method to determine the number of regimes based on a modified Hansen (1992) procedure. Furthermore, we construct multiple-step ahead forecasts and evaluate the forecasting performance of the model. Finally, an empirical application of the short term interest rate yield is presented and discussed.Smooth Transition Threshold Autoregressive, Forecasting, Nonlinear Models

Contemporaneous-threshold smooth transition GARCH models

This paper proposes a contemporaneous-threshold smooth transition GARCH (or C-STGARCH)model for dynamic conditional heteroskedasticity. The C-STGARCH model is a generalization tosecond conditional moments of the contemporaneous smooth transition threshold autoregressive model of Dueker et al. (2007) in which the regime weights depend on the ex ante probability that a contemporaneous latent regime-specific variable exceeds a threshold value. A key feature of the C-STGARCH model is that its transition function depends on all the parameters of the model as well as on the data. The structural properties of the model are investigated, in addition to the finite-sample properties of the maximum likelihood estimator of its parameters. An application to U.S. stock returns illustrates the practical usefulness of the C-STGARCH model

Cross-Sectional Aggregation and Persistence in Conditional Variance

This paper explores the interactions between cross-sectional aggregation and persistence of volatility shocks. We derive the ARMA-GARCH representation that linear aggregates of ARMA processes with GARCH errors admit, and establish conditions under which persistence in volatility of the aggregate series is higher than persistence in the volatility of the individual series. The practical implications of the results are illustrated empirically in the context of an option pricing exercise.ARMA process; Cross-sectional aggregation; GARCH process; Volatility persistence.

The effects of different parameterizations of Markov-switching in a CIR model of bond pricing

We examine several discrete-time versions of the Cox, Ingersoll and Ross (CIR) model for the term structure, in which the short rate is subject to discrete shifts. Our empirical analysis suggests that careful consideration of which parameters of the short-term interest rate equation that are allowed to be switched is crucial. Ignoring this issue may result in a parameterization that produces no improvement (in terms of bond pricing) relative to the standard CIR model, even when there are clear breaks in the data

An Empirical Examination of Term Structure Models with Regime Shifts

We examine several continuous-time term structure models in which the short rate is subject both to continuous changes and to discrete shifts. Several regime-switching term structure models are developed, with regime-dependence in various combinations of their drift and diffusion parameters. We examine their predictive power. Our empirical analysis suggests that it is important to attempt to specify the switching model correctly: badly parameterized switching models may not be an improvement (in terms of pricing) over models which do not allow for regime switching, even when there are clear breaks in the data.term structure of interest rates, bond yields, stochastic discount factor/pricing kernel, regime switching

Contemporaneous threshold autoregressive models: estimation, testing and forecasting

This paper proposes a contemporaneous smooth transition threshold autoregressive model (C-STAR) as a modification of the smooth transition threshold autoregressive model surveyed in Teräsvirta (1998), in which the regime weights depend on the ex ante probability that a latent regime-specific variable will exceed a threshold value. We argue that the contemporaneous model is well-suited to rational expectations applications (and pricing exercises), in that it does not require the initial regimes to be predetermined. We investigate the properties of the model and evaluate its finite-sample maximum likelihood performance. We also propose a method to determine the number of regimes based on a modified Hansen (1992) procedure. Furthermore, we construct multiple-step ahead forecasts and evaluate the forecasting performance of the model. Finally, an empirical application of the short term interest rate yield is presented and discussed. ; Earlier title: Contemporaneous threshold autoregressive models: estimation, forecasting and rational expectations applicationsRational expectations (Economic theory) ; Forecasting

A simple method for testing cointegration subject to regime changes

In this paper, we propose a simple method for testing cointegration in models that allow for multiple shifts in the long run relationship. The procedure consists of computing conventional residual-based tests with standardized residuals from Markov switching estimation. No new critical values are needed. An empirical application to the present value model of stock prices is presented, complemented by a small Monte Carlo experiment.Cointegration; Markov Switching; Standardized residuals.