scholarly journals Long Forward Probabilities, Recovery, and the Term Structure of Bond Risk Premiums

2018 ◽  
Vol 31 (12) ◽  
pp. 4863-4883 ◽  
Author(s):  
Likuan Qin ◽  
Vadim Linetsky ◽  
Yutian Nie
Author(s):  
Roberto Gomez-Cram ◽  
Amir Yaron

Abstract Macrofinance term structure models rely too heavily on the volatility of expected inflation news as a source for variations in nominal bond yield shocks. We develop and estimate a model featuring inflation nonneutrality and preference shocks. The stochastic volatility of inflation and consumption govern bond risk premiums movements, whereas preference shocks generate fluctuations in real rates. The model accounts for key bond market features without resorting to an overly dominating expected inflation channel. The estimation shows that preference shocks are strongly negatively correlated with market distress factors and that real rate news is the dominant driver of nominal yield shocks.


2018 ◽  
Vol 11 (4) ◽  
pp. 60 ◽  
Author(s):  
Constantino Hevia ◽  
Martin Sola

Researchers who estimate affine term structure models often impose overidentifying restrictions (restrictions on parameters beyond those necessary for identification) for a variety of reasons. While some of those restrictions seem to have minor effects on the extracted factors and some measures of risk premia, such as the forward risk premium, they may have a large impact on other measures of risk premia that is often ignored. In this paper, we analyze how apparently innocuous overidentifying restrictions imposed on affine term structure models can lead to large differences in several measures of risk premiums.


Author(s):  
Daniele Bianchi ◽  
Matthias Büchner ◽  
Andrea Tamoni

Abstract We show that machine learning methods, in particular, extreme trees and neural networks (NNs), provide strong statistical evidence in favor of bond return predictability. NN forecasts based on macroeconomic and yield information translate into economic gains that are larger than those obtained using yields alone. Interestingly, the nature of unspanned factors changes along the yield curve: stock- and labor-market-related variables are more relevant for short-term maturities, whereas output and income variables matter more for longer maturities. Finally, NN forecasts correlate with proxies for time-varying risk aversion and uncertainty, lending support to models featuring both channels.


2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Paul J.J. Welfens ◽  
Fabian Baier ◽  
Samir Kadiric ◽  
Arthur Korus ◽  
Tian Xiong

Abstract Key aspects covered refer to the cost of leaving the EU and in particular the implications for corporate bond risk premiums in the UK and the Eurozone: The gap between the interest rates of corporate bonds and government bonds could increase in the UK and Eurozone, respectively, as a result of BREXIT where the 2016 BREXIT referendum itself is considered to be a first BREXIT event (see the empirical findings), followed by the main BREXIT event, namely the day of officially leaving the EU – possibly as a No-deal BREXIT. It is as yet not clear what type of BREXIT will be implemented – hard versus soft – and it is also unclear what type of free trade agreement the EU and the UK could accomplish post-BREXIT. However, it is obviously necessary to carefully consider the background of the BREXIT dynamics and to then refer to various versions of BREXIT if one is to understand the inherent politico-economic dynamics of BREXIT – with a No-deal case representing an analytical benchmark which most politicians in the British Parliament obviously would want to avoid; a simple way to indeed avoid this case, with obvious high costs for the British economy, is not easy to discern as the UK’s political system is fractured. If the safe-haven status of the UK should be impaired by BREXIT, the rise of government bond interest rates by 0.3 percent would stand for the same burden as the net UK contribution to the EU.


2010 ◽  
Vol 66 (4) ◽  
pp. 67-82 ◽  
Author(s):  
Gerardo Palazzo ◽  
Stefano Nobili
Keyword(s):  

2018 ◽  
Vol 64 (3) ◽  
pp. 1413-1439 ◽  
Author(s):  
Bruno Feunou ◽  
Jean-Sébastien Fontaine

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