Do Macroeconomic Variables Forecast Bond Returns?

2005 ◽  
Author(s):  
Hwagyun Kim
Keyword(s):  
Macroeconomic Variables ◽  
Bond Returns

Unspanned Global Macro Risks in Bond Returns

2021 ◽  
Author(s):  
Feng Zhao ◽  
Guofu Zhou ◽  
Xiaoneng Zhu
Keyword(s):  
Term Structure ◽  
Predictive Power ◽  
International Markets ◽  
Bond Markets ◽  
Market Prices ◽  
Macroeconomic Variables ◽  
Bond Returns ◽  
Large Panel ◽  
Term Premia ◽  
Macro Finance

We examine the macro-spanning hypothesis for bond returns in international markets. Based on a large panel of real-time macroeconomic variables that are not subject to revisions, we find that global macro factors have predictive power for bond returns unspanned by yield factors. Furthermore, we estimate macro-finance term structure models with the unspanned global macro factors and find that the global macro factors influence the market prices of level and slope risks and induce comovements in forward term premia in global bond markets. This paper was accepted by David Simchi-Levi, finance.

Household Debt and Macroeconomic Variables in Malaysia

2016 ◽  
Author(s):  
Masturah Ma’in ◽  
Nur AmiraIsmarau Tajuddin ◽  
Siti Badariah Saiful Nathan
Keyword(s):  
Household Debt ◽  
Macroeconomic Variables

The causes of poverty in Russia

2020 ◽  
Vol 13 (1) ◽  
pp. 21-36
Author(s):  
I.S. Ivanchenko
Keyword(s):  
Regression Analysis ◽  
Regional Development ◽  
Financial Market ◽  
Russian Federation ◽  
Short Term ◽  
Financial Situation ◽  
Macroeconomic Variables ◽  
Development Plans ◽  
The Russian Federation ◽  
Short Term Forecasting

Subject. This article analyzes the changes in poverty of the population of the Russian Federation. Objectives. The article aims to identify macroeconomic variables that will have the most effective impact on reducing poverty in Russia. Methods. For the study, I used the methods of logical, comparative, and statistical analyses. Results. The article presents a list of macroeconomic variables that, according to Western scholars, can influence the incomes of the poorest stratum of society and the number of unemployed in the country. The regression analysis based on the selected variables reveals those ones that have a statistically significant impact on the financial situation of the Russian poor. Relevance. The results obtained can be used by the financial market mega-regulator to make anti-poverty decisions. In addition, the models built can be useful to the executive authorities at various levels for short-term forecasting of the number of unemployed and their income in drawing up regional development plans for the areas.

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