𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Forecasting recessions using the yield curve

✍ Scribed by Marcelle Chauvet; Simon Potter

Publisher
John Wiley and Sons
Year
2005
Tongue
English
Weight
452 KB
Volume
24
Category
Article
ISSN
0277-6693

No coin nor oath required. For personal study only.

✦ Synopsis

We compare forecasts of recessions using four different specifications of the probit model: a time invariant conditionally independent version; a business cycle specific conditionally independent model; a time invariant probit with autocorrelated errors; and a business cycle specific probit with autocorrelated errors. The more sophisticated versions of the model take into account some of the potential underlying causes of the documented predictive instability of the yield curve. We find strong evidence in favour of the more sophisticated specification, which allows for multiple breakpoints across business cycles and autocorrelation. We also develop a new approach to the construction of real time forecasting of recession probabilities.

📜 SIMILAR VOLUMES

Parsimonious modeling and forecasting of
Parsimonious modeling and forecasting of corporate yield curve
✍ Wei-Choun Yu; Donald M. Salyards 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 504 KB

## Abstract This paper investigates the sensitivity of out‐of‐sample forecasting performance over a span of different parameters of l in the dynamic Nelson–Siegel three‐factor AR(1) model. First, we find that the ad hoc selection of l is not optimal. Second, we find a substantial difference in fact

Forecasting the Yield Curve in a Data-Ri
Forecasting the Yield Curve in a Data-Rich Environment Using the Factor-Augmented Nelson–Siegel Model
✍ Peter Exterkate; Dick Van Dijk; Christiaan Heij; Patrick J. F. Groenen 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 328 KB 👁 1 views

## ABSTRACT This paper compares various ways of extracting macroeconomic information from a data‐rich environment for forecasting the yield curve using the Nelson–Siegel model. Five issues in extracting factors from a large panel of macro variables are addressed; namely, selection of a subset of th

Use of Growth Indices in Yield Forecast
Use of Growth Indices in Yield Forecast
✍ Dr. R. C. Jain; R. Agrawal; M. P. Jha 📂 Article 📅 1985 🏛 John Wiley and Sons 🌐 English ⚖ 249 KB 👁 1 views

A iiiodel has been developed for forecasting of crop yields in which growth indicctj of biometrical characters based on two or more periods simultaneously have been utilised. The growth indices are obtained as weighted accumulations of observations on biometrical characters in different periods, wei

Forecasting of curves using a Kohonen cl
Forecasting of curves using a Kohonen classification
✍ Marie Cottrell; Bernard Girard; Patrick Rousset 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 193 KB

This paper addresses an extensively studied problem, which is a particular case of long-term forecasting. In many practical situations, one has to predict a complete curve, i.e. the set of the 24 hourly values for the next day, of all the daily values for the next month or for the next year. For exa

Nelson–Siegel, Affine and Quadratic Yiel
Nelson–Siegel, Affine and Quadratic Yield Curve Specifications: Which One is Better at Forecasting?
✍ Ken Nyholm; Rositsa Vidova-Koleva 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 176 KB

## ABSTRACT In this paper we compare the in‐sample fit and out‐of‐sample forecasting performance of no‐arbitrage quadratic, essentially affine and dynamic Nelson–Siegel term structure models. In total, 11 model variants are evaluated, comprising five quadratic, four affine and two Nelson–Siegel mod