We use vector autoregressions with drifting coefficients and stochastic volatility to investigate how the dynamic effects of oil supply shocks on the U.S. economy have changed over time. We find a substantial decline in the short-run price elasticity of oil demand since the mid-eighties. This...

There is no standard economic forecasting procedure that systematically outperforms the others at all horizons and with any dataset. A common way to proceed, in many contexts, is to choose the best model within a family based on a fitting criteria, and then forecast. I compare the out-of-sample...

I present evidence that a moving average (MA) trading strategy third order stochastically dominates buying and holding the underlying asset in a mean-variance-skewness sense using monthly returns of value-weighted decile portfolios sorted by market size, book-to-market cash-flow-to-price,...

I translate familiar concepts of discrete-time time-series to contnuous-time equivalent. I cover lag operators, ARMA models, the relation between levels and differences, integration and cointegration, and the Hansen-Sargent prediction formulas

There is an ongoing debate on whether disasters cause significant macroeconomic impacts and are truly a potential impediment to economic development. This paper aims to assess whether and by what mechanisms disasters have the potential to cause significant GDP impacts. The analysis first studies...

This paper considers tests of parameters instability and structural change with known, unknown or multiple breakpoints. The results apply to a wide class of parametric models that are suitable for estimation by strong rules for detecting the number of breaks in a time series. For that, we use...

This paper investigates the empirical evidence of long-run risk and its implications for the equity premium puzzle. We find that the long-run risk model is generally weakly identified and that standard inferences tend to underestimate the uncertainty of long-run risk. We extend the LM-type test...

I present evidence that a moving average (MA) trading strategy third order stochastically dominates buying and holding the underlying asset in a mean-variance-skewness sense using monthly returns of value-weighted decile portfolios sorted by market size, book-to-market cash-flow-to-price,...

In this paper we focus on analyzing the predictive accuracy of three different types of forecasting techniques, Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN), and Singular Spectral Analysis (SSA), used for predicting chaotic time series data. These techniques...