Forecasting local currency bond risk premia of emerging markets: The role of cross-country macrofinancial linkages

被引:3
作者
Cepni, Oguzhan [1 ]
Gupta, Rangan [2 ]
Guney, I. Ethem [1 ]
Yilmaz, M. [1 ]
机构
[1] Cent Bank Republ Turkey, Haci Bayram Mah Istiklal Cad 10, TR-06050 Ankara, Turkey
[2] Univ Pretoria, Dept Econ, Pretoria, South Africa
关键词
bond risk premia; emerging markets; factor extraction methods; out-of-sample forecasting; TERM STRUCTURE; RETURNS; STOCK; PREDICTABILITY; INFORMATION; SAMPLE; NUMBER;
D O I
10.1002/for.2669
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this paper, we forecast local currency debt of five major emerging market countries (Brazil, Indonesia, Mexico, South Africa, and Turkey) over the period January 2010 to January 2019 (with an in-sample period: March 2005 to December 2009). We exploit information from a large set of economic and financial time series to assess the importance not only of "own-country" factors (derived from principal component and partial least squares approaches), but also create "global" predictors by combining the country-specific variables across the five emerging economies. We find that, while information on own-country factors can outperform the historical average model, global factors tend to produce not only greater statistical and economic gains, but also enhance market timing ability of investors, especially when we use the target variable (bond premium) approach under the partial least squares method to extract our factors. Our results have important implications not only for fund managers but also for policymakers.
引用
收藏
页码:966 / 985
页数:20
相关论文
共 48 条
[1]   Predictability of Emerging Market Local Currency Bond Risk Premia [J].
Akgiray, Vedat ;
Baronyan, Sayad ;
Sener, Emrah ;
Yilmaz, Osman .
EMERGING MARKETS FINANCE AND TRADE, 2016, 52 (07) :1627-1646
[2]  
[Anonymous], 2019, MANAGEMENT SCI
[3]  
Bai Jushan, 2008, Foundations and Trends in Econometrics, V3, P89, DOI 10.1561/0800000002
[4]  
Bai J., 2010, 475 FED RES BANK NEW
[5]   Determining the number of factors in approximate factor models [J].
Bai, JS ;
Ng, S .
ECONOMETRICA, 2002, 70 (01) :191-221
[6]  
Bianchi D., 2019, 1911 USCINET
[7]   Are more data always better for factor analysis? [J].
Boivin, Jean ;
Ng, Serena .
JOURNAL OF ECONOMETRICS, 2006, 132 (01) :169-194
[8]   Macroeconomic factors and equity premium predictability [J].
Buncic, Daniel ;
Tischhauser, Martin .
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE, 2017, 51 :621-644
[9]   Correlations in emerging market bonds: The role of local and global factors [J].
Bunda, Irina ;
Hamann, A. Javier ;
Lall, Subir .
EMERGING MARKETS REVIEW, 2009, 10 (02) :67-96
[10]   Getting the most out of macroeconomic information for predicting excess stock returns [J].
Cakmakli, Cem ;
van Dijk, Dick .
INTERNATIONAL JOURNAL OF FORECASTING, 2016, 32 (03) :650-668