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2002): “Unit root tests in three-regime SETAR models,” Working Paper wp 465
- Queen Mary, University of London, Department of Economics
, 1992
"... This paper proposes a simple direct testing procedure to distinguish a linear unit root process from a globally stationary three-regime self-exciting threshold autoregres-sive process. Following the threshold cointegration literature and thus assuming that the process follows the random walk in the ..."
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Cited by 15 (0 self)
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This paper proposes a simple direct testing procedure to distinguish a linear unit root process from a globally stationary three-regime self-exciting threshold autoregres-sive process. Following the threshold cointegration literature and thus assuming that the process follows the random walk in the corridor regime, the null of a unit root can be tested by the Wald test for the joint significance of threshold autoregressive parame-ters under the lower and the upper regime. We derive the asymptotic null distribution of the Wald statistic, and show that it does not depend on unknown fixed threshold values. Monte Carlo evidence clearly indicates that the exponential average of the Wald statistic is more powerful than the Dickey-Fuller test that ignores the threshold nature under the alternative.
CISS – A composite indicator of systemic stress in the financial system”. ECB Working Paper Series, forthcoming
, 2010
"... In 2012 all ECB publications feature a motif taken from the €50 banknote. NOTE: This Working Paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the authors and do not necessarily refl ect those of the ECB. Acknowledgements We t ..."
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Cited by 13 (0 self)
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In 2012 all ECB publications feature a motif taken from the €50 banknote. NOTE: This Working Paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the authors and do not necessarily refl ect those of the ECB. Acknowledgements We thank Philipp Hartmann for inspiring and supporting this project throughout all stages. Philipp also invented the indicator’s name and its abbreviation CISS (pronounced like “kiss”). We thank Tommy Kostka for excellent research assistance and for several good ideas which helped improving the CISS. Very helpful comments from Geert Bekaert, Wolfgang Lemke, Simone Manganelli and an anonymous referee are gratefully acknowledged. We finally thank participants at the Euro Area Business Cycle Network conference “Econometric Modelling of Macro-Financial Linkages ” in Florence and the 5th CSDA International Conference on Computational and Financial Econometrics in London for fruitful discussions and comments. However, the views expressed in this paper are those of the authors and do not necessarily reflect those of the European Central Bank, the Eurosystem or the Magyar Nemzeti Bank.
Empirical analysis of stock returns and volatility: Evidence from seven Asian stock markets based on TAR-GARCH model, Review of Quantitative Finance and Accounting 17: 301–318
, 2001
"... Abstract. This paper investigates the time-series behavior of stock returns for seven Asian stock markets. In most cases, higher average returns appear to be associated with a higher level of volatility. Testing the relationship between stock returns and unexpected volatility, the evidence shows tha ..."
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Abstract. This paper investigates the time-series behavior of stock returns for seven Asian stock markets. In most cases, higher average returns appear to be associated with a higher level of volatility. Testing the relationship between stock returns and unexpected volatility, the evidence shows that four out of seven Asian stock markets have significant results. Further analyzing the relationship between stock returns and time-varying volatility by using Threshold Autoregressive GARCH(1,1)-in-mean specification indicates that the null hypothesis of no asymmetric effect on the conditional volatility is rejected for the daily data. However, the null cannot be rejected for the monthly data. Key words: stock returns, volatility, Asian stock markets, asymmetric effect, TAR-GARCH model
Threshold Effects in Multivariate Error Correction Models
, 2005
"... In this paper we propose a testing procedure for assessing the presence of threshold effects in nonstationary Vector autoregressive models with or without cointegration. Our approach involves first testing whether the long run impact matrix characterising the VECM type rep-resentation of the VAR swi ..."
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Cited by 11 (3 self)
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In this paper we propose a testing procedure for assessing the presence of threshold effects in nonstationary Vector autoregressive models with or without cointegration. Our approach involves first testing whether the long run impact matrix characterising the VECM type rep-resentation of the VAR switches according to the magnitude of some threshold variable and is valid regardless of whether the system is purely I(1), I(1) with cointegration or stationary. Once the potential presence of threshold effects is established we subsequently evaluate the cointegrating properties of the system in each regime through a model selection based approach whose asymptotic and finite sample properties are also established. This subsequently allows us to introduce a novel non-linear permanent and transitory decomposition of the vector process of interest.
A Multivariate STAR Analysis of the Relationship Between Money and Output
, 1999
"... Using a standard 4-variable linear vector error correction model (VECM), we rst show that the null hypothesis of linearity can be strongly rejected against the alternative of smooth transition autoregressive nonlinearity. An important result from this stage of the analysis is that the quarterly g ..."
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Cited by 10 (0 self)
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Using a standard 4-variable linear vector error correction model (VECM), we rst show that the null hypothesis of linearity can be strongly rejected against the alternative of smooth transition autoregressive nonlinearity. An important result from this stage of the analysis is that the quarterly growth rate of money is identied as the transition variable, the variable which governs the smooth switching between regimes. This implies there is a nonlinear causal relationship between money and output. A smooth transition VECM (STVECM) is then used to examine whether money nonlinearly Granger causes output in the sense that lagged values of money enter the model's output equation as regressors. We evaluate this type of nonlinear Granger causality with both in-sample and out-of-sample analysis. For the in-sample analysis we compare alternative models using predictive accuracy tests. These results vary strongly across use of the AIC and SIC. Our use of an out-of-sample forecasting exercise to study money-income Granger causality, both linear and nonlinear, we believe is new to the literature. The forecasting results do not suggest that money is nonlinearly Granger causal for output. In fact, they show that by allowing money to nonlinearly Granger cause output, the forecasting performance of the STVECM is signicantly worsened. We thank participants of the Tinbergen Institute/Macroeconomic Dynamics Conference on "Nonlinear Modeling of Multivariate Macroeconomic Relations" for their helpful comments. Rothman's research was supported by an East Carolina University Faculty Senate Summer Research Grant and van Dijk wishes to acknowledge the hospitality of the Department of Economics at the University of Western Australia. y Department of Economics, Brewster Bu...
So (2003), Asymmetrical reaction to US stock-return news: evidence from major stock markets based on a double-threshold model
- Journal of Economics and Business
"... Abstract This paper examines the hypothesis that both stock returns and volatility are asymmetrical functions of past information from the US market. By employing a double-threshold GARCH model to investigate six major index-return series, we find strong evidence supporting the asymmetrical hypothe ..."
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Cited by 10 (3 self)
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Abstract This paper examines the hypothesis that both stock returns and volatility are asymmetrical functions of past information from the US market. By employing a double-threshold GARCH model to investigate six major index-return series, we find strong evidence supporting the asymmetrical hypothesis of stock returns. Specifically, negative news from the US market will cause a larger decline in a national stock return than an equal magnitude of good news. This holds true for the volatility series. The variance appears to be more volatile when bad news impacts the market than when good news does.
Testing a linear MA model against threshold MA models
- Ann. Statistics
, 2005
"... This paper investigates the (conditional) quasi-likelihood ratio test for the threshold in MA models. Under the hypothesis of no threshold, it is shown that the test statistic converges weakly to a function of the centred Gaussian process. Under local alternatives, it is shown that this test has non ..."
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Cited by 9 (2 self)
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This paper investigates the (conditional) quasi-likelihood ratio test for the threshold in MA models. Under the hypothesis of no threshold, it is shown that the test statistic converges weakly to a function of the centred Gaussian process. Under local alternatives, it is shown that this test has nontrivial asymptotic power. The results are based on a new weak convergence of a linear marked empirical process, which is independently of interest. This paper also gives an invertible expansion of the threshold MA models. 1. Introduction. Since Tong [30]
Testing for Nonlinearity in a Vector Time Series
, 1998
"... Tests for detecting general nonlinear behavior in a vector time series are introduced. These tests are multivariate extensions of the univariate tests of Keenan (1985) and Tsay (1986). Simulation results show that, in general, the multivariate tests are more powerful than their univariate counterpar ..."
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Cited by 7 (2 self)
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Tests for detecting general nonlinear behavior in a vector time series are introduced. These tests are multivariate extensions of the univariate tests of Keenan (1985) and Tsay (1986). Simulation results show that, in general, the multivariate tests are more powerful than their univariate counterparts, especially for series having nonlinear structure involving several components of the vector process and process error terms that are weakly or moderately cross-correlated. For illustration, the tests are applied to seasonally adjusted quarterly capital expenditures and appropriations in U.S. manufacturing over the period 1953 to 1974. 1 Introduction Nonlinear time series models have been used extensively in recent years to model complex dynamics not adequately represented using linear models. Their use has been confined mainly to univariate series, due to the additional complexity involved in modeling multivariate correlated systems. Tong (1990) provides a nice review of nonlin- # Jane...
M (2007), “Asymmetric price transmission in the Spanish lamb sector
- European Review of Agricultural Economics
"... This article investigates the non-linear adjustment between farm and retail prices in the lamb sector in Spain, using a three-regime Threshold Autoregressive Model. The results indicate that, in the long run, price transmission is perfect and any supply or demand shocks are fully transmitted along t ..."
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This article investigates the non-linear adjustment between farm and retail prices in the lamb sector in Spain, using a three-regime Threshold Autoregressive Model. The results indicate that, in the long run, price transmission is perfect and any supply or demand shocks are fully transmitted along the marketing chain. In the short run, price adjustments between the farm and the retail levels are asymmetric and reveal a demand-pull transmission mechanism. On the other hand, retailers benefit from any shock, whether positive or negative, that affects supply or demand conditions.
Structural change in macroeconomic time series: A complex systems perspective
- Journal of Macreconomics
"... ABSTRACT We demonstrate that the process of generating smooth transitions can be viewed as a natural result of the filtering operations implied in the generation of discrete time series observations from the sampling of data from an underlying continuous time process that has undergone a process of ..."
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ABSTRACT We demonstrate that the process of generating smooth transitions can be viewed as a natural result of the filtering operations implied in the generation of discrete time series observations from the sampling of data from an underlying continuous time process that has undergone a process of structural change. In order to focus discussion, we utilize the problem of estimating the location of abrupt shifts in some simple time series models. This approach will permit us to address salient issues relating to distortions induced by the inherent aggregation associated with discrete-time sampling of continuous time processes experiencing structural change. We also address the issue of how time irreversible structures may be generated within the smooth transition processes.
