That financial markets can influence real economic activity has been accepted by economists long ago and became dramatically apparent again in the last financial crisis, when the sharp decline in housing prices in the US was followed by a severe recession. In general, asset prices are determined in a forward-looking manner, stock prices for example reflect the expected profitability of firms in the future and thus are linked to expected future economic conditions. Furthermore, many macroeconomic models suggested by economic theory in-corporate interest rates, interest spreads or exchange rates, which can be seen as some sort of financial assets, and believing in these models means believing that asset prices influence developments of macroeconomic v ariables in the future. These considerations and observations gave rise to examine the pre-dictive power of asset prices to forecast output and inflation and a survey of this literature as well as empirical tests for a variety of predictors in different countries can be found e.g. in Stock and Watson (2003).
Inhaltsverzeichnis (Table of Contents)
- Introduction
- Methods
- Pseudo Out-of-Sample forecasts
- Benchmark forecasts
- Forecast evaluation
- Diebold Mariano test.
- Forecasting with individual predictors
- Forecast combination.
- The Data
- Results
- Individual predictor forecasts
- Combination forecasts
- A (short) closer look at the last financial crisis
- Conclusion
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This research investigates the predictive power of asset prices for output and inflation forecasting. The study analyzes whether including asset prices in forecasting models improves prediction accuracy compared to traditional autoregressive models. It examines a variety of predictors across different countries and time periods, focusing on the stability and consistency of predictive power across different contexts.
- Predictive power of asset prices
- Forecasting output and inflation
- Comparison of forecast accuracy
- Stability of predictive power across time and countries
- Model combination forecasts
Zusammenfassung der Kapitel (Chapter Summaries)
The first chapter, "Introduction," lays out the background and motivation for the study, highlighting the potential influence of financial markets on real economic activity, particularly exemplified by the recent financial crisis. It discusses the forward-looking nature of asset prices and their relationship to future economic conditions. The chapter then introduces the research question and outlines the approach taken to examine the predictive power of asset prices.
The second chapter, "Methods," delves into the specific methodologies employed in the study. This includes explanations of the "Pseudo Out-of-Sample" forecasting technique, benchmark forecasts, and forecast evaluation methods. The chapter further details the Diebold Mariano test, which is used to assess the statistical significance of any differences in forecast accuracy. It then discusses the forecasting process with individual predictors and model combination techniques.
Schlüsselwörter (Keywords)
This paper focuses on the informational content of asset prices for forecasting output and inflation. Key concepts include asset prices, predictive power, forecasting models, autoregressive processes, root mean squared forecast error (RMSFE), model combination, pseudo out-of-sample forecasting, Diebold Mariano test, and stability of predictive power. The research aims to determine whether including asset prices in forecasting models improves prediction accuracy and investigates the consistency of this predictive power across different countries and time periods.
- Quote paper
- Gerret Halberstadt (Author), 2014, On the informational content of asset prices for output (and inflation) forecasting, Munich, GRIN Verlag, https://www.grin.com/document/276378
