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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Forecast evaluation methods: A Monte Carlo investigation and an application to the predictability of interest rates

Forecast evaluation methods: A Monte Carlo investigation and an application to the predictability of interest rates

Undorf, Frank

Paperback

EconomicsEnvironmental Studies

ISBN10: 3668792488
ISBN13: 9783668792487
Publisher: Grin Verlag
Published: Oct 17 2018
Pages: 68
Weight: 0.22
Height: 0.16 Width: 5.83 Depth: 8.27
Language: English
Master's Thesis from the year 2017 in the subject Economics - Statistics and Methods, grade: 1,0, University of Cologne (Institut für Ökonometrie und Statistik), language: English, abstract: This thesis overviews selected forecast evaluation tests and attempts to link the concept of testing equal mean squared error and forecast encompassing within a common simple regression framework. A Monte Carlo analysis provides size and power properties for both a model-free and model-based environment. In particular, the encompassing regression based test assessing the null hypothesis of equal mean squared error offers beneficial size and power properties compared to the Diebold-Mariano test, at least in a conditional homoskedastic small sample framework without autocorrelation. A simple application of several tests is provided by comparing different interest rate prediction models like a time series model, a linear model with macroeconomic indicators and a dynamic yield curve model. It turns out that simple time series specifications are hard to outperform for most of the comparisons. However, indicators like the German stock market index or the ifo expectation indicator provide useful information for future German government bond yields.

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