Please use this identifier to cite or link to this item:
Title: A Dynamic Nelson-Siegel Factor Model with Financial System Indicators.
Authors: Chin Han Wei Jarrett
Keywords: macro-finance, forecasting exercise, financial system indicators, dynamic Nelson-Siegel factor model, credit spread modelling, real GDP growth
Issue Date: 6-Nov-2017
Citation: Chin Han Wei Jarrett (2017-11-06). A Dynamic Nelson-Siegel Factor Model with Financial System Indicators.. ScholarBank@NUS Repository.
Abstract: After the global financial crisis and the subsequent recession, given the nascent macro-finance literature, the interactions between macroeconomics and financial markets grow more important. A related question is how interest rates affect real GDP. I explore this interaction via a forecasting exercise. First, I use a vector autoregressive model with financial system indicators within the dynamic Nelson-Siegel framework to forecast interest rates. Then, I extend the analysis to credit spread modelling, after which I investigate whether credit spreads forecasted using the dynamic Nelson-Siegel factor model, in a contemporaneous regression with real GDP growth, beat the benchmark autoregressive model in real GDP growth and autoregressive distributed lag models in forecasting real GDP growth. I found that the proposed vector autoregressive model was able to generate good yield forecasts, and also produced credit spread forecasts ranked second to the dynamic Nelson-Siegel autoregressive factor model in forecasting real GDP growth.
Appears in Collections:Bachelor's Theses

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Chin Han Wei Jarrett AY1718 Sem 1.pdf869.29 kBAdobe PDF


NoneLog In

Page view(s)

checked on Sep 18, 2020


checked on Sep 18, 2020

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.