Studies in Nonlinear Dynamics & Econometrics

Published by De Gruyter

Volume 21 Issue 1 - Special issue: Recent developments of switching models for financial data / Guest editors: Gilles Dufrénot and Fredj Jawadi

Issue of Studies in Nonlinear Dynamics & Econometrics

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Contents
Journal Overview

Publicly Available February 16, 2017

Frontmatter

Page range: i-iii

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Editorial

Publicly Available February 16, 2017

Introduction: recent developments of switching models for financial data

Gilles Dufrénot, Fredj Jawadi

Page range: 1-2

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Research Articles

Publicly Available July 7, 2016

On the estimation of regime-switching Lévy models

Julien Chevallier, Stéphane Goutte

Page range: 3-29

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Abstract

The regime-switching Lévy model combines jump-diffusion under the form of a Lévy process, and Markov regime-switching where all parameters depend on the value of a continuous time Markov chain. We start by giving general stochastic results. Estimation is performed following a two-step procedure. The EM-algorithm is extended to this new class of jump-diffusion regime-switching models. Simulations are proposed, alongside an empirical application dedicated to the study of financial and commodity time series. When comparing the results with (i) non regime-switching models, and (ii) continuous regime-switching models (where the Lévy process is replaced by a classic Brownian motion), the Lévy regime-switching model outperforms other competitors.

June 16, 2016

RALS-LM unit root test with trend breaks and non-normal errors: application to the Prebisch-Singer hypothesis

Ming Meng, Junsoo Lee, James E. Payne

Page range: 31-45

Abstract

This study proposes a new unit root test that allows for structural breaks in both the intercept and the slope, and adopts the residual augmented least squares (RALS) procedure to gain improved power when the error term follows a non-normal distribution. The new test using the RALS procedure is more powerful than the usual LM test which does not incorporate information on non-normal errors. Our test is free of nuisance parameters that indicate the locations of structural break. It is also free of the spurious rejection problem. Thus, the rejection of the null hypothesis can be considered as more accurate evidence of stationarity. We apply the new test on the recently extended Grilli and Yang index of 24 commodity series from 1900 to 2007. Our empirical findings provide significant evidence that primary commodity prices are stationary with one or two trend breaks. However, compared with past studies, our findings provide even weaker evidence to support the Prebisch-Singer hypothesis.

October 5, 2016

Modeling threshold effects in stock price co-movements: a vector nonlinear cointegration approach

Souhir Chlibi, Fredj Jawadi, Mohamed Sellami

Page range: 47-63

Abstract

This paper studies the hypothesis of stock price comovements between the US market and three different regions [the G6, BRICS and MENA (Middle East North Africa)] during calm and crisis periods. It extends the study by (Chlibi, S., F. Jawadi, and M. Sellami. 2016. “Analyzing Heterogeneous Stock Price Comovements through Hybrid Approaches.” Open Economies Review 27: 541–559) and models stock price comovements in a nonlinear multivariate framework. In particular, we develop an empirical nonlinear specification to model heterogeneity in stock price comovements, based on the multivariate threshold cointegration framework of (Hansen, B. E., and B. Seo. 2002. “Testing For Two-Regime Threshold Cointegration in Vector Error Correction Models.” Journal of Econometrics 110: 293–318). Our findings point to the presence of significant threshold cointegration relationships that are activated per regime. Specification of these threshold effects in stock price comovements is particularly useful to help investors to rebalance and adjust their portfolios so as to optimize their investment and diversification strategies.

July 2, 2016

Specification analysis in regime-switching continuous-time diffusion models for market volatility

Ruijun Bu, Jie Cheng, Kaddour Hadri

Page range: 65-80

Abstract

We examine model specification in regime-switching continuous-time diffusions for modeling S&P 500 Volatility Index (VIX). Our investigation is carried out under two nonlinear diffusion frameworks, the NLDCEV and the CIRCEV frameworks, and our focus is on the nonlinearity in regime-dependent drift and diffusion terms, the switching components, and the endogeneity in regime changes. While we find strong evidence of regime-switching effects, models with a switching diffusion term capture the VIX dynamics considerably better than models with only a switching drift, confirming the presence and importance of volatility regimes. Strong evidence of nonlinear endogeneity in regime changes is also detected. Meanwhile, we find significant nonlinearity in the regime-dependent diffusion specification, suggesting that the nonlinearity in the VIX dynamics cannot be accounted for by regime-switching effects alone. Finally, we find that models based on the CIRCEV specification are significantly closer to the true data generating process of VIX than models based on the NLDCEV specification uniformly across all regime-switching specifications.

June 3, 2016

A semiparametric nonlinear quantile regression model for financial returns

Krenar Avdulaj, Jozef Barunik

Page range: 81-97

Abstract

Accurately measuring and forecasting value-at-risk (VaR) remains a challenging task at the heart of financial economic theory. Recently, quantile regression models have been used successfully to capture the conditional quantiles of returns and to forecast VaR accurately. In this paper, we further explore nonlinearities in data and propose to couple realized measures with the nonlinear quantile regression framework to explain and forecast the conditional quantiles of financial returns. The nonlinear quantile regression models are implied by the copula specifications and allow us to capture possible nonlinearities, tail dependence, and asymmetries in the conditional quantiles of financial returns. Using high frequency data that covers most liquid US stocks in seven sectors, we provide ample evidence of asymmetric conditional dependence with different levels of dependence, which are characteristic for each industry. The backtesting results of estimated VaR favour our approach.

May 31, 2016

A model of the euro-area yield curve with discrete policy rates

Jean-Paul Renne

Page range: 99-116

Abstract

This paper presents a no-arbitrage yield-curve model that explicitly incorporates the central-bank policy rate. This model is consistent with the existence of a lower bound for nominal interest rates, which makes it particularly relevant in the current context of extremely low interest rates. Changes in the policy rates depend on the monetary-policy phase, that can be either in an easing, status quo or tightening mode. The estimation of the model, based on daily euro-area yield data, reveals the strong influence of the monetary-policy phases on the shape of the yield curve. This relationship can, in turn, be exploited to estimate the probabilities of being in the different monetary-policy phases. The model is also used to compute term premiums, that are the parts of the yields reflecting the aversion of investors to interest rate risk. The results point to the existence of statistically significant premiums for many dates, even for short horizons.

About this journal

Objective
A peer-reviewed journal since 1996, Studies in Nonlinear Dynamics & Econometrics (SNDE) is at the forefront of statistical and theoretical approaches to economics. The journal studies ways in which econometrics and dynamical systems theory increase our understanding of economic and financial markets. The journal disseminates authors' algorithms, programs, and data sets, allowing other scholars to replicate empirical results. Authors include econometricians such as Clive Granger, James Hamilton, and Halbert White, and theorists Jess Benhabib, Alan Kirman, and Kazuo Nishimura.

Best Paper Award
Since 2015, the Society has awarded $500 each year to the best paper published in the Society’s journal: Studies in Nonlinear Dynamics and Econometrics.

The Best Paper in 2022 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Szabolcs Blazsek, Alvaro Escribano and Adrian Licht. for their paper: "Multivariate Markov-switching score-driven models: an application to the global crude oil market" Studies in Nonlinear Dynamics & Econometrics, vol. 26, no. 3, 2022, pp. 313-335.

The Best Paper in 2021 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Eric Mark Aldrich and Howard Kung for their paper: “Computational Methods for Production-Based Asset Pricing Models with Recursive Utility”, published in Volume 25, Issue 1.

The Best Paper in 2020 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Gregor Bäurle, Daniel Kaufmann, Sylvia Kaufmann and Rodney Strachan for their paper: “Constrained interest rates and changing dynamics at the zero lower bound”, published in Volume 24, Issue 2.

The Best Paper in 2019 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Chang-Jin Kim and Yunmi Kim for their paper: “A unified framework jointly explaining business conditions, stock returns, volatility and “volatility feedback news” effects”, published in Volume 23, Issue 2.

The Best Paper in 2018 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Luiggi Donayre, Yunjong Eo and James Morley for their paper: “Improving likelihood-ratio-based confidence intervals for threshold parameters in finite samples”,published in Volume 22, Issue 1 (Feb 2018)

The Best Paper in 2017 for Studies in Nonlinear Dynamics and Econometrics has been awarded to Julien Chevallier and Stephane Goutte for their paper: “On the estimation of regime-switching Levy models”, published in Volume 21, Issue 1 (Feb 2017).

The Best Paper in 2016 for Studies in Nonlinear Dynamics and Econometrics has been awarded to Mark J. Jensen for his paper: “Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility?”, published in Volume 20, Issue 4 (Sept. 2016).

The Best Paper in 2015 for Studies in Nonlinear Dynamics and Econometrics has been awarded to Markus Jochmann and Gary Koop for their paper: “Regime-switching cointegration?”, published in Volume 19, Issue 1 (Feb 2015).

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Probability
Statistics
Macroeconomics
Finance
Forecasting
Econometrics

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