Structural Bond Return Predictability Tests

2012 ◽  
Author(s):  
Guoshi Tong
Keyword(s):  
Return Predictability ◽  
Structural Bond ◽  
Bond Return

Bond Risk Premiums with Machine Learning

2020 ◽  
Author(s):  
Daniele Bianchi ◽  
Matthias Büchner ◽  
Andrea Tamoni
Keyword(s):  
Machine Learning ◽  
Yield Curve ◽  
Return Predictability ◽  
Time Varying ◽  
Short Term ◽  
Risk Premiums ◽  
Machine Learning Methods ◽  
Yield Information ◽  
Bond Return ◽  
Bond Risk

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.

Residual Equity Momentum Spillover in Global Corporate Bond Markets

2019 ◽  
Keyword(s):  
Return Predictability ◽  
Bond Market ◽  
Corporate Bond ◽  
Bond Markets ◽  
Corporate Bond Market ◽  
Pricing Factors ◽  
Bond Return ◽  
Abnormal Pattern ◽  
Additional Support ◽  
Investment Grade

This article presents an improved equity momentum measure for corporate bonds, using the euro-denominated global investment-grade corporate bond market from 2000 to 2016. The author documents economically meaningful and statistically significant corporate bond return predictability. In contrast to the widely used total equity return, momentum as measured by the residual (idiosyncratic) equity return appears to further enhance risk-adjusted performance of corporate bond investors. Additional support for this conjecture is obtained from tests for various asset pricing factors and transaction costs, as exposure to these risk factors cannot explain this abnormal pattern in returns.

scholarly journals Predicting Bond Return Predictability

2020 ◽  
Author(s):  
Daniel Borup ◽  
Jonas Nygaard Eriksen ◽  
Mads Markvart Kjær ◽  
Martin Thyrsgaard
Keyword(s):  
Return Predictability ◽  
Bond Return

Bond Return Predictability: An Investigation for the European Market

2003 ◽  
Author(s):  
Florinda Silva ◽  
Maria Ceu Cortez ◽  
Manuel J. Rocha Armada
Keyword(s):  
Return Predictability ◽  
European Market ◽  
Bond Return

Bond Return Predictability and its Economic Value: The Case of China

2019 ◽  
Author(s):  
Yunpeng Su ◽  
Baochen Yang ◽  
zhou Fangzhao ◽  
Yunbi An
Keyword(s):  
Economic Value ◽  
Return Predictability ◽  
Bond Return

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.

scholarly journals Bond Return Predictability: Economic Value and Links to the Macroeconomy

2019 ◽  
Vol 65 (2) ◽  
pp. 508-540 ◽  
Author(s):  
Antonio Gargano ◽  
Davide Pettenuzzo ◽  
Allan Timmermann
Keyword(s):  
Economic Value ◽  
Return Predictability ◽  
Bond Return
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