Robust term structure estimation in developed and emerging markets

Name: Robust term structure estimation in developed and emerging markets
Author: Ahi, Emrah, Akgiray, V., Şener, Emrah

İsim	Robust term structure estimation in developed and emerging markets
Yazar	Ahi, Emrah, Akgiray, V., Şener, Emrah
Basım Tarihi:	2018-01
Basım Yeri	- Springer Nature
Konu	Term structure, Nelson–Siegel–Svensson, Particle swarm optimization, Robust estimation
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0254-5330
Kayıt Numarası	342b0932-1c6a-4f1a-8cdd-f0995b1b8a0e
Lokasyon	Business Administration
Tarih	2018-01
Örnek Metin	Despite powerful advances in interest rate curve modeling for data-rich countries in the last 30 years, comparatively little attention has been paid to the key practical problem of estimation of the term structure of interest rates for emerging markets. This may be partly due to limited data availability. However, emerging bond markets are becoming increasingly important and liquid. It is, therefore, important to be understand whether conclusions drawn from developed countries carry over to emerging markets. We estimate model parameters of fully flexible Nelson–Siegel–Svensson term structures model which has become one of the most popular term structure model among academics, practitioners, and central bankers. We investigate four sets of bond data: U.S. Treasuries, and three major emerging market government bond data-sets (Brazil, Mexico and Turkey). By including both the very dense U.S. data and the comparatively sparse emerging market data, we ensure that are results are not specific to a particular data-set. We find that gradient and direct search methods perform poorly in estimating term structures of interest rates, while global optimization methods, particularly the hybrid particle swarm optimization introduced in this paper, do well. Our results are consistent across four countries, both in- and out-of-sample, and for perturbations in prices and starting values. For academics and practitioners interested in optimization methods, this study provides clear evidence of the practical importance of choice of optimization method and validates a method that works well for the NSS model.
DOI	10.1007/s10479-016-2282-5
Cilt	260

Kaynağa git Özyeğin Üniversitesi

Aramaya Dön

Özyeğin Üniversitesi

Kaynağa git

Robust term structure estimation in developed and emerging markets

Yazar Ahi, Emrah, Akgiray, V., Şener, Emrah

Basım Tarihi 2018-01

Basım Yeri - Springer Nature

Konu Term structure, Nelson–Siegel–Svensson, Particle swarm optimization, Robust estimation

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0254-5330

Kayıt Numarası 342b0932-1c6a-4f1a-8cdd-f0995b1b8a0e

Lokasyon Business Administration

Tarih 2018-01

Örnek Metin Despite powerful advances in interest rate curve modeling for data-rich countries in the last 30 years, comparatively little attention has been paid to the key practical problem of estimation of the term structure of interest rates for emerging markets. This may be partly due to limited data availability. However, emerging bond markets are becoming increasingly important and liquid. It is, therefore, important to be understand whether conclusions drawn from developed countries carry over to emerging markets. We estimate model parameters of fully flexible Nelson–Siegel–Svensson term structures model which has become one of the most popular term structure model among academics, practitioners, and central bankers. We investigate four sets of bond data: U.S. Treasuries, and three major emerging market government bond data-sets (Brazil, Mexico and Turkey). By including both the very dense U.S. data and the comparatively sparse emerging market data, we ensure that are results are not specific to a particular data-set. We find that gradient and direct search methods perform poorly in estimating term structures of interest rates, while global optimization methods, particularly the hybrid particle swarm optimization introduced in this paper, do well. Our results are consistent across four countries, both in- and out-of-sample, and for perturbations in prices and starting values. For academics and practitioners interested in optimization methods, this study provides clear evidence of the practical importance of choice of optimization method and validates a method that works well for the NSS model.

DOI 10.1007/s10479-016-2282-5

Cilt 260