Commodity prices are of interest to investors, central banks and policymakers since they are believed to influence general price levels. Therefore, in this thesis I study whether it is possible to forecast commodities returns using economic indicators over different horizons and economic cycles. I establish an out-of-sample (OOS) predictability using different economic variables such as: inflation, unemployment rate, dividend price ratio, industrial production, among others. The time span of the analysis is from 1951 to 2014, over a monthly, quarterly an annual horizon. I observe that inflation is consistently a good predictor for in-sample (IS) and OOS univariate models. Multivariate OOS estimations tend to be more accurate when ...
Na trajetória da economia mundial, destaca-se a importância do agronegócio, que exerce um papel esse...
This paper examines the hypothesis that commodity price trends are useful indicators of OECD price d...
Using more than 140 years of data, we comprehensively analyze the predictive power of a broad set of...
We develop an econometric modelling framework to forecast commodity prices taking into account poten...
We investigate the power of commodity prices to improve inflation forecast performance in 21 OECD co...
This paper aims to create an econometric model capable of anticipating recessions in the United Stat...
Economists agree on the relevant role of monetary policy in the process of maintaining sustained eco...
This paper demonstrates that "commodity currency" exchange rates have remarkably robust power in pre...
AbstractThis work applies time series methods, such as VAR, ARMA-GARCH and Cointegration/VEC, in ord...
This thesis will try to answer the question if it is possible to use commodities to predict the Swed...
This paper examines whether the inclusion of several commodity indexes in multivariate mod- els coul...
Recent evidence highlights that commodity price changes exhibit a short-lived, yet robust contempora...
© 2020 Elsevier Inc. This paper investigates whether economic policy uncertainty is predictable usin...
This thesis consists of three chapters on forecasting techniques in economics. In chapter 1, I use c...
A threefold analysis of commodity prices is carried out to observe their long-run behaviour, their s...
Na trajetória da economia mundial, destaca-se a importância do agronegócio, que exerce um papel esse...
This paper examines the hypothesis that commodity price trends are useful indicators of OECD price d...
Using more than 140 years of data, we comprehensively analyze the predictive power of a broad set of...
We develop an econometric modelling framework to forecast commodity prices taking into account poten...
We investigate the power of commodity prices to improve inflation forecast performance in 21 OECD co...
This paper aims to create an econometric model capable of anticipating recessions in the United Stat...
Economists agree on the relevant role of monetary policy in the process of maintaining sustained eco...
This paper demonstrates that "commodity currency" exchange rates have remarkably robust power in pre...
AbstractThis work applies time series methods, such as VAR, ARMA-GARCH and Cointegration/VEC, in ord...
This thesis will try to answer the question if it is possible to use commodities to predict the Swed...
This paper examines whether the inclusion of several commodity indexes in multivariate mod- els coul...
Recent evidence highlights that commodity price changes exhibit a short-lived, yet robust contempora...
© 2020 Elsevier Inc. This paper investigates whether economic policy uncertainty is predictable usin...
This thesis consists of three chapters on forecasting techniques in economics. In chapter 1, I use c...
A threefold analysis of commodity prices is carried out to observe their long-run behaviour, their s...
Na trajetória da economia mundial, destaca-se a importância do agronegócio, que exerce um papel esse...
This paper examines the hypothesis that commodity price trends are useful indicators of OECD price d...
Using more than 140 years of data, we comprehensively analyze the predictive power of a broad set of...