Prediction of Long-Term Government Bond Yields Using Statistical and Artificial Intelligence Methods

2013 ◽  
pp. 341-367
Author(s):  
Marco Castellani ◽  
Emanuel A. dos Santos
Keyword(s):  
Artificial Intelligence ◽  
Government Bond ◽  
Bond Yields ◽  
Artificial Intelligence Methods

A Note Concerning the Dynamics of Government Bond Yields

2021 ◽  
pp. 056943452098827
Author(s):  
Tanweer Akram
Keyword(s):  
Interest Rate ◽  
Financial Markets ◽  
Yield Curve ◽  
Empirical Studies ◽  
State Theory ◽  
Government Bond ◽  
Bond Yields ◽  
Short Term ◽  
Government Bonds

Keynes argued that the central bank can influence the long-term interest rate on government bonds and the shape of the yield curve mainly through the short-term interest rate. Several recent empirical studies that examine the dynamics of government bond yields not only substantiate Keynes’s view that the long-term interest rate responds markedly to the short-term interest rate but also have relevance for macroeconomic theory and policy. This article relates Keynes’s discussions of money, the state theory of money, financial markets, investors’ expectations, uncertainty, and liquidity preference to the dynamics of government bond yields for countries with monetary sovereignty. Investors’ psychology, herding behavior in financial markets, and uncertainty about the future reinforce the effects of the short-term interest rate and the central bank’s monetary policy actions on the long-term interest rate. JEL classifications: E12; E40; E43; E50; E58; E60; F30; G10; G12; H62; H63

scholarly journals An Index of the Yields of Junk Bonds, 1910–1955

2017 ◽  
Vol 77 (4) ◽  
pp. 1203-1219 ◽  
Author(s):  
Peter Basile ◽  
Sung Won Kang ◽  
John Landon-Lane ◽  
Hugh Rockoff
Keyword(s):  
Twentieth Century ◽  
High Risk ◽  
Corporate Bond ◽  
High Yield ◽  
Government Bond ◽  
Bond Yields ◽  
Middle Years ◽  
Bond Index ◽  
Junk Bonds

We present a new monthly index of the yields on junk bonds (high risk, high yield bonds) for the period 1910–1955. This index supplements the indexes of government bond yields, and Aaa and Baa corporate bond yields economic historians have relied on previously to describe the long-term risk spectrum. First, we describe our sources and methods. Then we show that our junk bond index contains information that is not in the closest alternative, and suggest some ways that the junk bond index could be used to enrich our understanding of the turbulent middle years of the twentieth century.

scholarly journals The Long-Run Determinants of Indian Government Bond Yields

2019 ◽  
Vol 36 (1) ◽  
pp. 168-205 ◽  
Author(s):  
Tanweer Akram ◽  
Anupam Das
Keyword(s):  
Interest Rate ◽  
Government Bond ◽  
Bond Yields ◽  
Short Term ◽  
Indian Government ◽  
Bond Yield ◽  
Long Run ◽  
Key Driver ◽  
The Government

This paper investigates the long-term determinants of the nominal yields of Indian government bonds (IGBs). It examines whether John Maynard Keynes’ supposition that the short-term interest rate is the key driver of the long-term government bond yield holds over the long run, after controlling for key economic factors. It also appraises if the government fiscal variable has an adverse effect on government bond yields over the long run. The models estimated in this paper show that in India the short-term interest rate is the key driver of the long-term government bond yield over the long run. However, the government debt ratio does not have any discernible adverse effect on IGB yields over the long run. These findings will help policy makers to (i) use information on the current trend of the short-term interest rate and other key macro variables to form their long-term outlook about IGB yields, and (ii) understand the policy implications of the government's fiscal stance.

scholarly journals DETERMINANT OF GOVERNMENT BOND YIELDS

2020 ◽  
Vol 1 (1) ◽  
pp. 86-99
Author(s):  
Priyo Adiwibowo ◽  
Pardomuan Sihombing
Keyword(s):  
Forecast Error ◽  
Impulse Response Function ◽  
Oil Prices ◽  
Error Variance ◽  
Government Bond ◽  
Bond Yields ◽  
Determinant Factors ◽  
Bank Rate ◽  
Forecast Error Variance

This study aims to analyze the influence of determinant factors: (i) exchange rates, (ii) inflation, (iii) CDS spreads, (iv) bid-ask spreads, (v) overnight rate, (vi) CB’s rate (Central Bank Rate), and (vii) oil prices on Government bond yields. The data used are monthly data in the period 2012 - 2018. The research method used is the Vector Auto Regression (VAR) approach. Our analysis indicated that the determinant factors have impact on government bond yields. Based on the analysis of the impulse response function (IRF), the yield is to respond to any shocks given by the long term. While through forecast error variance decomposition (FEVD) analysis, found that CDS spreads and oil prices contributed significantly to the movement of Government bond yields.

scholarly journals Assessing the impacts of global economic policy uncertainty and the long-term bond yields on oil prices

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oguzhan Ozcelebi
Keyword(s):  
Economic Activity ◽  
Oil Prices ◽  
Policy Uncertainty ◽  
Government Bond ◽  
Bond Yields ◽  
Content Type ◽  
Economic Policy Uncertainty ◽  
The Usa ◽  
The Impact

Purpose Might the impact of the global economic policy uncertainty (GEPU) and the long-term bond yields on oil prices be asymmetric? This paper aims to consider the effects of the GEPU and the US long-term government bond yields on oil prices using quantile-based analysis and nonlinear vector autoregression (VAR) model. The author hypothesized whether the negative and positive changes in the GEPU and the long-term bond yields of the USA have different effects on oil prices. Design/methodology/approach To address this question, the author uses quantile cointegration model and the impulse response functions (IRFs) of the censored variable approach of Kilian and Vigfusson (2011). Findings The quantile cointegration test showed the existence of non-linear cointegration relationship, whereas Granger-causality analysis revealed that positive/negative variations in GEPU will have opposite effects on oil prices. This result was supported by the quantile regression model’s coefficients and nonlinear VAR model’s IRFs; more specifically, it was stressed that increasing/decreasing GEPU will deaccelerate/accelerate global economic activity and thus lead to a fall/rise in oil prices. On the other hand, the empirical models indicated that the impact of US 10-year government bond yields on oil prices is asymmetrical, while it was found that deterioration in the borrowing conditions in the USA may have an impact on oil prices by slowing down the global economic activity. Originality/value As a robustness check of the quantile-based analysis results, the slope-based Mork test is used.

scholarly journals The Driving Factors of EMU Government Bond Yields: The Role of Debt, Liquidity and Fiscal Councils

2020 ◽  
Vol 8 (3) ◽  
pp. 53
Author(s):  
Anastasios Pappas ◽  
Ioannis Kostakis
Keyword(s):  
Risk Premium ◽  
Public Debt ◽  
Fixed Effects ◽  
Least Square ◽  
Policy Implications ◽  
Government Bond ◽  
Bond Yields ◽  
The Public ◽  
Dummy Variable

This study presents empirical evidence about the determinants of long-term government bond yields for 19 economies of the European Monetary Union (EMU) over the period 1995–2018 within a multivariate panel framework. The fixed effects estimators reveal that the relationship between public debt to the GDP ratio and yields is non-linear. We observe a threshold, which is determined to be at the area 90% of the ratio of public debt to GDP. Beyond that, area government borrowing costs increase as the public debt rises. Furthermore, we find evidence that a GDP decline and the downgrades of sovereign ratings increase the costs of government borrowing. In contrast, the operation of independent fiscal institutions helps to reduce government’s debt risk premium. Finally, liquidity in the Euro area plays a significant role on yields determination. The results remain robust when the dynamic instrumental variable fixed effect (FE-2SLS) and dynamic panel least square dummy variable corrected (LSDVC) estimators are employed. Empirical findings suggest important policy implications for the ongoing Covid-19 crisis for the EMU.

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