Survey Forecasts and the Time-Varying Second Moments of Stock and Bond Returns

2012 ◽  
Author(s):  
Pierluigi Balduzzi ◽  
Chunhua Lan
Keyword(s):  
Time Varying ◽  
Second Moments ◽  
Bond Returns

Term structure determinants of time‐varying risk of 1‐year bond returns

2019 ◽  
Vol 55 (3) ◽  
pp. 365-384
Author(s):  
Revansiddha Basavaraj Khanapure
Keyword(s):  
Term Structure ◽  
Time Varying ◽  
Bond Returns

Time-varying correlations and Sharpe ratios during quantitative easing

2017 ◽  
Vol 22 (1) ◽  
Author(s):  
Paul M. Jones ◽  
Haley O’Steen
Keyword(s):  
Quantitative Easing ◽  
Time Varying ◽  
Bond Returns ◽  
Econometric Methodology ◽  
Sharpe Ratios

AbstractUsing an econometric methodology from [Cappiello, Lorenzo, Robert F. Engle, and Kevin Sheppard. 2006. “Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns.”

Time Varying Behavior of Share Returns in Australia: 1988–2004

2016 ◽  
Vol 19 (01) ◽  
pp. 1650004
Author(s):  
Yew-Choe Lum ◽  
Sardar M. N. Islam
Keyword(s):  
Stock Returns ◽  
Future Research ◽  
Practical Reasons ◽  
Time Varying ◽  
Asymmetric Effect ◽  
Conditional Capm ◽  
Conditional Mean ◽  
Second Moments ◽  
Statistical Sense ◽  
Capm Model

The model in this paper is similar to Brailsford and Faff (1997), using a conditional CAPM model with the GARCH-M framework, but with a significant additional dummy term (in the conditional mean of the share return) that will help explain the models better in both economic and statistical sense. The relatively simpler asymmetric model in this paper is compatible to other more complex asymmetric models and hence should be easier to model and explain for practical purposes. The model in this paper is also a more effective model, in both economical and statistical terms, as compared to some other models in the GARCH family as it captures the asymmetric effect in the modeling process in both the conditional first and second moments. The findings in this paper have contributed in re-evaluating the nature and process of time varying behavior of time series of stock returns and will provide researchers and practitioners additional options and incentives to explore for future research. We have also provided statistical and practical reasons to support these findings.

Risk Premia in the 8:30 Economy

2018 ◽  
Vol 08 (03) ◽  
pp. 1850010 ◽  
Author(s):  
Jon Faust ◽  
Jonathan H. Wright
Keyword(s):  
Risk Premia ◽  
Time Varying ◽  
Excess Returns ◽  
Macroeconomic News ◽  
Asset Risk ◽  
Macroeconomic Announcements ◽  
News Announcements ◽  
Bond Returns ◽  
The Times ◽  
Over Time

Financial asset risk premia are widely agreed to vary over time. This paper decomposes these risk premia into expected excess returns earned in short windows around the times of macroeconomic news announcements (which mostly come out at 8:30[Formula: see text]am) and the expected excess returns that are earned at other times. Using intradaily data, we find that some, but not all, of the time-varying expected excess returns accrue right around macroeconomic announcements. In forecasting six-month cumulative bond returns, there is more predictability in announcement windows than at other times.

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