A dynamic Nelson-Siegel model with forward-looking indicators for the yield curve in the US

Resumo

This paper proposes a Factor-Augmented Dynamic Nelson-Siegel (FADNS) model to predict the yield curve in the US that relies on a large data set of weekly financial and macroeconomic variables. The FADNS model significantly improves interest rate forecasts relative to the extant models in the literature. For longer horizons, it beats autoregressive alternatives, with a reduction in mean absolute error of up to 40%. For shorter horizons, it offers a good challenge to autoregressive forecasting models, outperforming them for the 7- and 10-year yields. The out-of-sample analysis shows that the good performance comes mostly from the forward-looking nature of the variables we employ. Including them reduces the mean absolute error in 5 basis points on average with respect to models that reflect only past macroeconomic events.

Ficha do documento

Tipo

Estudo

Ano

2017

Instituição

Escola de Economia de São Paulo

Fonte

Repositório da FGV

Idioma

Inglês

Acesso

Acesso aberto

Identificador

oai:repositorio.fgv.br:10438/18016

Temas

EconomiaDados

Palavras-chave

BondsFactor-augmented VARForecastingTerm structureYield curveEconomiaDebêntures - Estados UnidosDebêntures - Preços - Modelos econométricosInvestimentos - Estados Unidos