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Testing the Forecasting Ability of Multi-Factor Models on Non-US Interbank Rates

Tunaru, Diana, Fabozzi, Francesco, Fabozzi, Frank J. (2021) Testing the Forecasting Ability of Multi-Factor Models on Non-US Interbank Rates. Journal of Fixed Income, 31 (2). pp. 7-33. ISSN 1059-8596. E-ISSN 2168-8648. (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:91430)

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We examine the forecasting performance of continuous time multi-factor models for the term structure of interbank rates in UK, Europe and Japan in comparison with other parsimonious models. We employ two general dynamic frameworks with different factor structures, the generalized Chan-Karolyi-Longstaff-Sanders family of models and the arbitrage-free dynamic Nelson-Siegel family of models. Applying a battery of accuracy measures and a range of formal tests of forecasting superiority, we provide evidence that extended multi-factor models have good out-of-sample forecasting performance of the short segment of the yield curve. However, for the euro and partially for the yen the random walk forecasts pass various tests consistently, indicating a higher level of market efficiency compared to the sterling pound interbank market.

Item Type: Article
Uncontrolled keywords: forecasting, interbank rates, multi-factor models, model confidence set test, superior predictive ability test
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HG Finance
Divisions: Divisions > Kent Business School - Division > Department of Accounting and Finance
Depositing User: Diana Tunaru
Date Deposited: 08 Nov 2021 21:33 UTC
Last Modified: 27 Oct 2023 13:16 UTC
Resource URI: (The current URI for this page, for reference purposes)

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