Term Structure Forecasting: No-Arbitrage Restrictions vs Large Information Set

Carlo Favero (), Luca Sala () and Linlin Niu

No 6206, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: This paper addresses the issue of forecasting the term structure. We provide a unified state-space modelling framework that encompasses different existing discrete-time yield curve models. Within such framework we analyze the impact on forecasting performance of two crucial modelling choices, i.e. the imposition of no-arbitrage restrictions and the size of the information set used to extract factors. Using US yield curve data, we find that: a. macro factors are very useful in forecasting at medium/long forecasting horizon; b. financial factors are useful in short run forecasting; c. no-arbitrage models are effective in shrinking the dimensionality of the parameter space and, when supplemented with additional macro information, are very effective in forecasting; d. within no-arbitrage models, assuming time-varying risk price is more favourable than assuming constant risk price for medium horizon-maturity forecast when yield factors dominate the information set, and for short horizon and long maturity forecast when macro factors dominate the information set; e. however, given the complexity and the highly non-linear parameterization of no-arbitrage models, it is very difficult to exploit within this type of models the additional information offered by large macroeconomic datasets.

Keywords: Factor models; Forecasting; Large data set; Term structure of interest rates; Yield curve (search for similar items in EconPapers)
JEL-codes: C33 C53 E43 E44 (search for similar items in EconPapers)
Date: 2007-03
New Economics Papers: this item is included in nep-ecm, nep-fmk, nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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Working Paper: Term Structure Forecasting: No-arbitrage Restrictions vs. Large Information Set (2007)
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