scholarly journals Interest Rates under Falling Stars

2020 ◽  
Vol 110 (5) ◽  
pp. 1316-1354 ◽  
Author(s):  
Michael D. Bauer ◽  
Glenn D. Rudebusch
Keyword(s):  
Interest Rates ◽  
Term Structure ◽  
Yield Curve ◽  
Term Premium ◽  
Long Run ◽  
Trend Inflation ◽  
Bond Returns ◽  
Out Of Sample ◽  
Finance Theory ◽  
Macro Finance

Macro-finance theory implies that trend inflation and the equilibrium real interest rate are fundamental determinants of the yield curve. However, empirical models of the term structure of interest rates generally assume that these fundamentals are constant. We show that accounting for time variation in these underlying long-run trends is crucial for understanding the dynamics of Treasury yields and predicting excess bond returns. We introduce a new arbitrage-free model that captures the key role that long-run trends play in determining interest rates. The model also provides new, more plausible estimates of the term premium and accurate out-of-sample yield forecasts. (JEL E31, E43, E47)

scholarly journals Revisiting the Dynamic Linkages of Treasury Bond Yields for the BRICS: A Forecasting Analysis

Forecasting ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 102-129
Author(s):  
Stelios Bekiros ◽  
Christos Avdoulas
Keyword(s):  
Interest Rates ◽  
Error Correction ◽  
Term Structure ◽  
Parameter Instability ◽  
Vector Error Correction ◽  
Brics Countries ◽  
Vector Error ◽  
Long Run ◽  
Out Of Sample ◽  
Dynamic Linkages

We examined the dynamic linkages among money market interest rates in the so-called “BRICS” countries (Brazil, Russia, India, China, and South Africa) by using weekly data of the overnight, one-, three-, and six- months, as well as of one year, Treasury bills rates covering the period from January 2005 to August 2019. A long-run relationship among interest rates was established by employing the Vector Error Correction modeling (VECM), which revealed the validation of the Expectation Hypothesis Theory (EH) of the term structure of interest rates, taking into account long-run deviations from equilibrium and inherent nonlinearities. We unveiled short-run dynamic adjustments for the term structure of the BRICS, subject to regime switches. We then used Markov Switching Vector Error Correction models (MS-VECM) to forecast them dynamically during an out-of-sample period of May 2016 through August 2019. The MSIH-VECM forecasts were found to be superior to the VECM approaches. The novelty of our paper is mainly due to the exploration of the possibility of parameter instability as a crucial factor, which might explain the rejection of the restricted version of the cointegration space, and on the dynamic out-of-sample forecasts of the term structure over a more recent time span in order to assess further the usefulness of our nonlinear MS-VECM characterization of the term structure, capturing the effects of the global and domestic financial crisis.

Estimating and Forecasting the Term Structure of Korea Markets Using the Nelson-Siegel Model

2004 ◽  
Vol 12 (2) ◽  
pp. 101-126
Author(s):  
Joon Haeng Lee
Keyword(s):  
Term Structure ◽  
Yield Curve ◽  
Principal Component ◽  
Component Model ◽  
Structure Model ◽  
Sample Period ◽  
Term Structure Model ◽  
Long Run ◽  
Out Of Sample ◽  
Principal Component Model

This paper estimates and forecasts yield curve of korea bond market using a three factor term structure model based on the Nelson-Siegel model. The Nelson-Siegel model is in-terpreted as a model of level, slope and curvature and has the flexibility required to match the changing shape of the yield curve. To estimate this model, we use the two-step estima-tion procedure as in Diebold and Li. Estimation results show our model is Quite flexible and gives a very good fit to data. To see the forecasting ability of our model, we compare the RMSEs (root mean square error) of our model to random walk (RW) model and principal component model for out-of sample period as well as in-sample period. we find that our model has better forecasting performances over principal component model but shows slight edge over RW model especially for long run forecasting period. Considering that it is difficult for any model to show better forecasting ability over the RW model in out-of-sample period, results suggest that our model is useful for practitioners to forecast yields curve dynamics.

Understanding the Impact of Monetary Policy in Korea using a Macro-Finance Term Structure Model with

2014 ◽  
Vol 22 (2) ◽  
pp. 161-192
Author(s):  
Woon Wook Jang ◽  
Jaehoon Hahn
Keyword(s):  
Monetary Policy ◽  
Term Structure ◽  
Yield Curve ◽  
Call Rate ◽  
Monetary Policy Shocks ◽  
Macroeconomic Factors ◽  
Term Structure Model ◽  
Term Premium ◽  
Policy Shocks ◽  
Macro Finance

This paper examines the interaction between monetary policy and the macroeconomy using a macro-finance term structure model of Joslin, Priebsch, and Singleton (2012), in which macroeconomic risks are not assumed to be spanned by information about the shape of the yield curve. For model estimation, we apply the Kalman filter to a large number of macroeconomic time series data grouped into output, inflation, and market stress categories and extract three common factors. For the factors determining the shape of the yield curve, we use the call rate, the spread between 10-year government bond yield and the call rate, and a combination of the call rate, 2- and 10-year government bond yields as proxies for the level, slope, and curvature factors. We interpret the call rate as a proxy for both the short rate and the instrument of monetary policy. Empirical results show that the macroeconomic factors have a significant impact on the risk premium associated with monetary policy shocks. Furthermore, we find that monetary policy shocks increase the term premium, which in turn affects the factors determining the yield curve, and such effects on the shape of the yield curve feeds back into the macroeconomic factors. Taken together, empirical findings in this paper can be interpreted as evidence supporting the term premium channel (Ferman, 2011) of monetary policy transmission mechanism.

The Yield Spread and Bond Return Predictability in Expansions and Recessions

2020 ◽  
Author(s):  
Martin M Andreasen ◽  
Tom Engsted ◽  
Stig V Møller ◽  
Magnus Sander
Keyword(s):  
Term Structure ◽  
Yield Curve ◽  
Return Predictability ◽  
Yield Spread ◽  
Market Prices ◽  
Term Structure Model ◽  
Bond Returns ◽  
Bond Return ◽  
Key Driver ◽  
Macro Finance

Abstract This paper uncovers that expected excess bond returns display a positive correlation with the slope of the yield curve (i.e., yield spread) in expansions but a negative correlation in recessions. We use a macro-finance term structure model with different market prices of risk in expansions and recessions to show that a very accommodating monetary policy in recessions is a key driver of this switch in return predictability.

Analyzing and forecasting the Chinese term structure of interest rates using functional principal component analysis

2018 ◽  
Vol 8 (3) ◽  
pp. 275-296 ◽  
Author(s):  
Pan Feng ◽  
Junhui Qian
Keyword(s):  
Principal Component Analysis ◽  
Interest Rates ◽  
Term Structure ◽  
Yield Curve ◽  
Principal Component ◽  
Functional Principal Component Analysis ◽  
Content Type ◽  
Functional Principal Component ◽  
Out Of Sample ◽  
Chinese Term

Purpose The purpose of this paper is to analyze and forecast the Chinese term structure of interest rates using functional principal component analysis (FPCA). Design/methodology/approach The authors propose an FPCA-K model using FPCA. The forecasting of the yield curve is based on modeling functional principal component (FPC) scores as standard scalar time series models. The authors evaluate the out-of-sample forecast performance using the root mean square and mean absolute errors. Findings Monthly yield data from January 2002 to December 2016 are used in this paper. The authors find that in the full sample, the first two FPCs account for 98.68 percent of the total variation in the yield curve. The authors then construct an FPCA-K model using the leading principal components. The authors find that the FPCA-K model compares favorably with the functional signal plus noise model, the dynamic Nelson-Siegel models and the random walk model in the out-of-sample forecasting. Practical implications The authors propose a functional approach to analyzing and forecasting the yield curve, which effectively utilizes the smoothness assumption and conveniently addresses the missing-data issue. Originality/value To the best knowledge, the authors are the first to use FPCA in the modeling and forecasting of yield curves.

Determinants of Treasury-LIBOR Swap Spreads

2005 ◽  
Vol 08 (04) ◽  
pp. 687-705 ◽  
Author(s):  
D. K. Malhotra ◽  
Vivek Bhargava ◽  
Mukesh Chaudhry
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Default Risk ◽  
Yield Curve ◽  
Short Term ◽  
Long Run ◽  
Interest Rate Volatility ◽  
Short Run ◽  
Using Data ◽  
Swap Spreads

Using data from the Treasury versus London Interbank Offer Swap Rates (LIBOR) for October 1987 to June 1998, this paper examines the determinants of swap spreads in the Treasury-LIBOR interest rate swap market. This study hypothesizes Treasury-LIBOR swap spreads as a function of the Treasury rate of comparable maturity, the slope of the yield curve, the volatility of short-term interest rates, a proxy for default risk, and liquidity in the swap market. The study finds that, in the long-run, swap spreads are negatively related to the yield curve slope and liquidity in the swap market. We also find that swap spreads are positively related to the short-term interest rate volatility. In the short-run, swap market's response to higher default risk seems to be higher spread between the bid and offer rates.

scholarly journals Liquidity-Adjusted Benchmark Yield Curves: A Look at Trading Concentration and Information

2007 ◽  
Vol 10 (04) ◽  
pp. 491-518 ◽  
Author(s):  
William T. Lin ◽  
David S. Sun
Keyword(s):  
Term Structure ◽  
Yield Curve ◽  
Information Discovery ◽  
Affine Term Structure ◽  
Term Structure Model ◽  
Long Run ◽  
Fitting Method ◽  
Bond Issues ◽  
Short Run

Estimation of benchmark yield curve in developing markets is often influenced by liquidity concentration. Based on an affine term structure model, we develop a long run liquidity weighted fitting method to address the trading concentration phenomenon arising from horizon-induced clientele equilibrium as well as information discovery. Specifically, we employ arguments from models of liquidity concentration and benchmark security information. After examining time series behavior of price errors against our fitted model, we find results consistent with both the horizon and information hypotheses. Our evidence indicates that trading liquidity carries information effect in the long run, which cannot be fully captured in the short run. Trading liquidity plays a key role in long run term structure fitting. Markets for liquid benchmark government bond issues collectively form a long term equilibrium. Compared with previous studies, our results provide a robust and realistic characterization of the spot rate term structure and related price forecasting over time, which in turn help portfolio investment of fixed income and long run pricing of financial instruments.

scholarly journals Yield curve dynamics with macroeconomic factors in Iberian economies

2020 ◽  
Vol 10 (3) ◽  
pp. 193-203
Author(s):  
Isabel Maldonado ◽  
Carlos Pinho
Keyword(s):  
Interest Rates ◽  
Term Structure ◽  
Yield Curve ◽  
Error Variance ◽  
Impact Factors ◽  
Strong Impact ◽  
Impulse Response Functions ◽  
Macroeconomic Factors ◽  
Vector Autoregressive ◽  
Future Evolution

Abstract The aim of this paper is to analyse the bidirectional relation between the term structure of interest rates components and macroeconomic factors. Using a factor augmented vector autoregressive model, impulse response functions and forecasting error variance decompositions we find evidence of a bidirectional relation between yield curve factors and the macroeconomic factors, with increased relevance of yield factors over it with increased forecasting horizons. The study was conduct for the two Iberian countries using information of public debt interest rates of Spain and Portugal and macroeconomic factors extracted from a set of macroeconomic variables, including indicators of activity, prices and confidence. Results show that the inclusion of confidence and macroeconomic factors in the analysis of the relationship between macroeconomics and interest rate structure is extremely relevant. The results obtained allow us to conclude that there is a strong impact of changes in macroeconomic factors on the term structure of interest rates, as well as a significant impact factors of the term structure in the future evolution of macroeconomic factors.

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