This paper analyzes the ability of both economic variables and moving-average rules to forecast the monthly U.S. equity premium using out-of-sample tests for 1960–2008. Both approaches provide statistically and economically significant out-of-sample forecasting gains, which are concentrated in U.S. business-cycle recessions. Nevertheless, economic variables and moving-average rules capture diff...

This paper reviews and documents methodology for fitting hidden Markov switching models to New Zealand GDP data. A primary objective is to better understand the utility of these methods for modelling growth and volatility regimes present in the New Zealand data and their interaction. Properties of the models are developed together with a description of the estimation methods, including use of t...

This paper introduces a Markov-Switching model where transition probabilities depend on higher frequency indicators and their lags, through polynomial weighting schemes. The MSV-MIDAS model is estimated via maximum likelihood methods. The estimation relies on a slightly modified version of Hamilton’s recursive filter. We use Monte Carlo simulations to assess the robustness of the estimation pro...

Using 15 years worth of additional data, a study is carried out to explore the extent to which the results in Rothman (1991) still hold. Using raw unfiltered data, the aggregate unemployment rate appears to be a Neftci-type symmetric process. But use of two detrending procedures produces strong evidence in favor of asymmetry for this series. The most robust result is that the manufacturing sect...

Article history: Received 7 October 2014 Received in revised form 28 January 2015 Accepted 28 January 2015 Available online 7 February 2015 The objectives of this study are two-fold: i) to derive time-varying exchange rate pass-through (ERPT) degree and ii) investigate the macroeconomic determinants of the degree of ERPT. For this purpose, the study adopts a distinct methodology combining Dynam...

We study situations in which autoregressive models are estimated on time series that contain switches in the data generating parameters and these switches are not accounted for. The geometry of this estimation problem causes estimated vector autoregressive models to display a unit eigenvalue, and the sum of the estimated autoregressive parameters of ARMA and GARCH models to be close to one. Thi...

Accurate volatility predictions are crucial for the successful implementation of risk management. The use of high frequency data approximately renders volatility from a latent to an observable quantity, and opens new directions to forecast future volatilities. Our goals in this paper are: (i) to select an accurate forecasting procedure for predicting volatilities based on high frequency data fr...

This paper examines the hypothesis that both stock returns and volatility are asymmetric functions of past information derived from domestic and US stock-market news. The evidence finds the presence of negative autocorrelation, which is consistent with the dominance of positive-feedback trading behavior. By employing a double-threshold autoregressive GARCH model to investigate four major index-...

We study forward-looking economic models assuming that agents take one step ahead expectations looking back k time periods. We show that the dynamics of the economy with such an expectation function are characterized by the coexistence of perfect foresight and nonperfect foresight cycles. The stability of all these periodic solutions under bounded rationality is related to the stability of the ...