We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for the observations. We observe significant changes in the forecasts when long-range dependence is taken into account. Using Monte Carlo...

This paper proposes a measure of real-time inflation expectations based on metadata, i.e., data about data, constructed from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation Search Index (GISI) is assessed relative to 37 other...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

I present evidence that higher frequency measures of inflation expectations outperform lower frequency measures of inflation expectations in tests of accuracy, predictive power, and rationality. For decades, the academic literature has focused on three survey measures of expected inflation: the...

We present a hybrid model for diagnosis and critical time forecasting of real estate bubbles. The model combines two elements: 1) the Log Periodic Power Law (LPPL) model to describe endogenous price dynamics originated from positive feedback loops between economic agents; and 2) a diffusion...

We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for the observations. We observe significant changes in the forecasts when long-range dependence is taken into account. Using Monte Carlo...

This paper studies the forecasting properties of linear GARCH models for closing-day futures prices on crude oil, first position, traded in the New York Mercantile Exchange from January 1995 to November 2005. In order to account for fat tails in the empirical distribution of the series, we...

In this paper bilateral models formalizing monthly growth of US imports and exports are employed to investigate the potential of nonlinear relationships linking exchange rate uncertainty and trade growth. Parametric linear and nonlinear as well as semiparametric time series models are evaluated...

Stock market return is one of financial variables that contain information to forecast real activity such as industrial production and real GDP growth. However, it is still controversial that stock market return can have a predictive content on real activity. This paper attempts to investigate...