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1
SANTOS, ALEXANDRE JOSE DOS. "TREE-STRUCTURE SMOOTH TRANSITION VECTOR AUTOREGRESSIVE MODELS – STVAR-TREE." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=15888@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>Esta dissertação tem como objetivo principal introduzir uma formulação de
modelo não-linear multivariado, a qual combina o modelo STVAR (Smooth
Transition Vector Autoregressive) com a metodologia CART (Classification and
Regression Tree) a fim de utilizá-lo para geração de cenários e de previsões. O
modelo resultante é um Modelo Vetorial Auto-Regressivo com Transição Suave
Estruturado por Árvores, denominado STVAR-Tree e tem como base o conceito
de múltiplos regimes, definidos por árvore binária. A especificação do modelo é
feita através do teste LM. Desta forma, o crescimento da árvore é condicionado à
existência de não-linearidade nas séries, que aponta a divisão do nó e a variável de
transição correspondente. Em cada divisão, são estimados os parâmetros lineares,
por Mínimos Quadrados Multivariados, e os parâmetros não-lineares, por
Mínimos Quadrados Não-Lineares. Como forma de avaliação do modelo STVARTree,
foram realizados diversos experimentos de Monte Carlo com o objetivo de
constatar a funcionalidade tanto do teste LM quanto da estimação do modelo.
Bons resultados foram obtidos para amostras médias e grandes. Além dos
experimentos, o modelo STVAR-Tree foi aplicado às séries brasileiras de Vazão
de Rios e Preço Spot de energia elétrica. No primeiro estudo, o modelo foi
comparado estatisticamente com o Periodic Autoregressive (PAR) e apresentou
um desempenho muito superior ao concorrente. No segundo caso, a comparação
foi com a modelagem Neuro-Fuzzy e ganhou em uma das quatro séries. Somando
os resultados dos experimentos e das duas aplicações conclui-se que o modelo
STVAR-Tree pode ser utilizado na solução de problemas reais, apresentando bom
desempenho.<br>The main goal of the dissertation is to introduce a nonlinear multivariate
model, which combines the model STVAR (Smooth Transition Vector
Autoregressive) with the CART (Classification and Regression Tree) method and
use it for generating scenarios and forecasting. The resulting model is a Tree-
Structured Vector Autoregressive model with Smooth Transition, called STVARTree,
which is based on the concept of multiple regimes, defined by binary tree.
The model specification is based on Lagrange Multiplier tests. Thus, the growth
of the tree is conditioned on the existence of nonlinearity in the time series, which
indicates the node to be split and the corresponding transition variable. In each
division, linear parameters are estimated by Multivariate Least Squares, and
nonlinear parameters by Non-Linear Least Squares. As a way of checking the
STVAR-Tree model, several Monte Carlo experiments were performed in order to
see the functionality of both the LM test and the model estimation. Best results
were obtained with medium and large samples. Besides, the STVAR-Tree model
was applied to Brazilian time series of Rivers Flow and electricity spot price. In
the first study, the model was statistically compared to the Periodic
Autoregressive (PAR) model and had a much higher performance than the
competitor. In the second case, the model comparison was with Neural-Fuzzy
Modeling and the STVAR-Tree model won in one of the four series. Adding both
the experiments and the two applications results we conclude that the STVARTree
model may be applied to solve real problems, having good results.
2
Clayton, Maya. "Econometric forecasting of financial assets using non-linear smooth transition autoregressive models." Thesis, University of St Andrews, 2011. http://hdl.handle.net/10023/1898.
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Following the debate by empirical finance research on the presence of non-linear predictability in stock market returns, this study examines forecasting abilities of nonlinear STAR-type models. A non-linear model methodology is applied to daily returns of FTSE, S&P, DAX and Nikkei indices. The research is then extended to long-horizon forecastability of the four series including monthly returns and a buy-and-sell strategy for a three, six and twelve month holding period using non-linear error-correction framework. The recursive out-of-sample forecast is performed using the present value model equilibrium methodology, whereby stock returns are forecasted using macroeconomic variables, in particular the dividend yield and price-earnings ratio. The forecasting exercise revealed the presence of non-linear predictability for all data periods considered, and confirmed an improvement of predictability for long-horizon data. Finally, the present value model approach is applied to the housing market, whereby the house price returns are forecasted using a price-earnings ratio as a measure of fundamental levels of prices. Findings revealed that the UK housing market appears to be characterised with asymmetric non-linear dynamics, and a clear preference for the asymmetric ESTAR model in terms of forecasting accuracy.
3
Zhou, Jia. "SMOOTH TRANSITION AUTOREGRESSIVE MODELS : A STUDY OF THE INDUSTRIAL PRODUCTION INDEX OF SWEDEN." Thesis, Uppsala University, Department of Statistics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-126752.
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<p>In this paper, we study the industrial production index of Sweden from Jan, 2000 to latest Feb, 2010. We find out there is a structural break at time point Dec, 2007, when the global financial crisis burst out first in U.S then spread to Europe. To model the industrial production index, one of the business cycle indicators which may behave nonlinear feature suggests utilizing a smooth transition autoregressive (STAR) model. Following the procedures given by Teräsvirta (1994), we carry out the linearity test against the STAR model, determine the delay parameter and choose between the LSTAR model and the ESTAR model. The results from the estimated model suggest the STAR model is better performing than the linear autoregressive model.</p>
4
Wang, Yuefeng. "Essays on modelling house prices." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/16242.
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Housing prices are of crucial importance in financial stability management. The severe financial crises that originated in the housing market in the US and subsequently spread throughout the world highlighted the crucial role that the housing market plays in preserving financial stability. After the severe housing market crash, many financial institutions in the US suffered from high default rates, severe liquidity shortages, and even bankruptcy. Against this background, researchers have sought to use econometric models to capture and forecast prices of homes. Available empirical research indicates that nonlinear models may be suitable for modelling price cycles. Accordingly, this thesis focuses primarily on using nonlinear models to empirically investigate cyclical patterns in housing prices. More specifically, the content of this thesis can be summarised in three essays which complement the existing literature on price modelling by using nonlinear models. The first essay contributes to the literature by testing the ability of regime switching models to capture and forecast house prices. The second essay examines the impact of banking factors on house price fluctuations. To account for house price characteristics, the regime switching model and generalised autoregressive conditionally heteroscedastic (GARCH) in-mean model have been used. The final essay investigates the effect of structural breaks on the unit root test and shows that a time-varying GARCH in-mean model can be used to estimate the housing price cycle in the UK.
5
Jobe, Ndey Isatou. "Nonlinearity In Exchange Rates : Evidence From African Economies." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297055.
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In an effort to assess the predictive ability of exchange rate models when data on African countries is sampled, this paper studies nonlinear modelling and prediction of the nominal exchange rate series of the United States dollar to currencies of thirty-eight African states using the smooth transition autoregressive (STAR) model. A three step analysis is undertaken. One, it investigates nonlinearity in all nominal exchange rate series examined using a chain of credible statistical in-sample tests. Significantly, evidence of nonlinear exponential STAR (ESTAR) dynamics is detected across all series. Two, linear models are provided another chance to make it right by shuffling to data on African countries to investigate their predictive power against the tough random walk without drift model. Linear models again failed significantly. Lastly, the predictive ability of nonlinear models against both the random walk without drift and the corresponding linear models is investigated. Nonlinear models display useful forecasting gains over all contending models.
6
Yildirim, Dilem. "Star Models: An Application To Turkish Inflation And Exchange Rates." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12605735/index.pdf.
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The recent empirical literature has shown that the dynamic generating mechanism of macroeconomic variables can be asymmetric. Inspiring from these empirical results, this thesis uses a class of nonlinear models called smooth transition autoregressive models to investigate possible asymmetric dynamics in inflation and nominal exchange rate series of Turkey. Estimation results imply that variables under consideration contain strong nonlinearities and these can be modeled by STAR models.
7
Chun, Winston Seung Hyun. "Estrutura a termo de taxa de juros brasileira: investigando a presença de não linearidade." reponame:Repositório Institucional do FGV, 2011. http://hdl.handle.net/10438/8585.
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Previous issue date: 2011-08-08<br>Esta dissertação tem com objetivo avaliar uma das implicações da hipótese de expectativas para a estrutura a termo de taxa de juros brasileira. Utilizando testes lineares tradicionais e através da reprodução de testes não lineares TAR de Enders e Granger (1998) e ESTAR Kapetanios e Shin (2003) conclui-se que a hipótese de expectativas não é totalmente válida para a ETTJ do Brasil, além disso, são encontradas evidências de não linearidade nas séries de spreads que demandam mais pesquisa sobre o assunto.<br>This dissertation has the aim to evaluate one of the implications of expectation hypothesis in Brazilian term structure of interests. Using traditional linear tests and through the reproduction of nonlinear Threshold Autoregressive (TAR) tests of Enders and Granger (1998) and Exponential Smooth Transition Autoregressive (ESTAR) of Kapetanios and Shin (2003) the conclusion is that expectation hypothesis is not totally valid for Brazil, besides that, some evidences of non-linearity in spreads series were found then more research is needed on the subject.
8
Beugnot, Julie. "Chômage et politique économique dans un contexte d'équilibres multiples." Thesis, Montpellier 1, 2010. http://www.theses.fr/2010MON10012.
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Cette thèse étudie les performances du marché du travail dans une économie susceptible de présenter plusieurs équilibres, et les implications d’une telle configuration pour la politique économique. Elle comporte quatre essais, traitant chacun d’un aspect spécifique de cette problématique. En premier lieu, l’analyse économétrique des séries temporelles de taux de chômage de quelques pays de l’OCDE, permettant notamment l’identification des changements de régimes et de leurs caractéristiques, apporte des évidences significatives à l’appui de l’hypothèse d’une multiplicité d’équilibres. En second lieu, on étudie les effets de l’introduction d’un salaire minimum obligatoire et d’une hausse de celui-ci dans un modèle statique de concurrence imparfaite avec négociations salariales au niveau de la firme, le facteur travail étant hétérogène. Si la hausse du salaire minimum est défavorable à l’emploi,l’introduction d’un salaire minimum en présence d’une multiplicité d’équilibres permet d’éliminer l’équilibre Pareto-inférieur. En troisième lieu, on étudie également les implications de l’existence d’équilibres multiples pour les politiques économiques, du fait de l’altération des propriétés dynamiques de l’économie, à travers l’analyse complète d’un modèle dynamique de concurrence imparfaite avec des négociations salariales individuelles et des frictions d’appariement sur le marché du travail. Enfin, on montre grâce à l’outil expérimental dans quelle mesure l’introduction d’une variable dite de tâche solaire, peut être source de défaut de coordination et d’inefficience dans une économie possédant deux équilibres Pareto-ordonnés<br>This thesis analyzes the performances of labor market in an economy subject to multiple equilibria and the implications of such a configuration for economic policy. It contains four pieces of research, each dealing with a particular aspect of the general setting. First, the econometric analysis of the unemployment time series for several OECD countries,which allows the identification of regime switches and their characteristics, brings forth some significant evidence that the multiple equilibria framework is relevant. Second, the effect of the implementation and of the rise of the minimum wage are investigated through a static model, assuming imperfect competition, heterogeneous labor input and wage negotiations at the firm level. Though minimum wage hikes have an adverse effect on employment, the implementation of a binding minimum wage turns out to be an efficient tool for excluding the Pareto- inferior equilibrium. Third economic policy conditions are also affected because the existence of multiple equilibria alters the dynamic properties of the economy. This case has been investigated in the framework of a fully dynamic model assuming imperfect competition individual wage negotiations and matching frictions. Finally, a coordination game experiment confirms that the introduction of a sunspot can be a source of coordination failure and inefficiency in an economy with two Pareto-ranked equilibria
9
Nur, Darfiana. "Parameter estimation of smooth threshold autoregressive models." Curtin University of Technology, School of Mathematics and Statistics, 1998. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=10781.
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This thesis is mainly concerned with the estimation of parameters of a first-order Smooth Threshold Autoregressive (STAR) model with delay parameter one. The estimation procedures include classical and Bayesian methods from a parametric and a semiparametric point of view.As the theoretical importance of stationarity is a primary concern in estimation of time series models, we begin the thesis with a thorough investigation of necessary or sufficient conditions for ergodicity of a first-order STAR process followed by the necessary and sufficient conditions for recurrence and classification for null-recurrence and transience.The estimation procedure is started by using Bayesian analysis which derives posterior distributions of parameters with a noninformative prior for the STAR models of order p. The predictive performance of the STAR models using the exact one-step-ahead predictions along with an approximation to multi-step-ahead predictive density are considered. The theoretical results are then illustrated by simulated data sets and the well- known Canadian lynx data set.The parameter estimation obtained by conditional least squares, maximum likelihood, M-estimator and estimating functions are reviewed together with their asymptotic properties and presented under the classical and parametric approaches. These estimators are then used as preliminary estimators for obtaining adaptive estimates in a semiparametric setting. The adaptive estimates for a first-order STAR model with delay parameter one exist only for the class of symmetric error densities. At the end, the numerical results are presented to compare the parametric and semiparametric estimates of this model.
10
Skalin, Joakim. "Modelling macroeconomic time series with smooth transition autoregressions." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 1998. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-650.
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Among the parametric nonlinear time series model families, the smooth transition regression (STR) model has recently received attention in the literature. The considerations in this dissertation focus on the univariate special case of this model, the smooth transition autoregression (STAR) model, although large parts of the discussion can be easily generalised to the more general STR case. Many nonlinear univariate time series models can be described as consisting of a number of regimes, each one corresponding to a linear autoregressive parametrisation, between which the process switches. In the STAR models, as opposed to certain other popular models involving multiple regimes, the transition between the extreme regimes is smooth and assumed to be characterised by a bounded continuous function of a transition variable. The transition variable, in turn, may be a lagged value of the variable in the model, or another stochastic or deterministic observable variable. A number of other commonly discussed nonlinear autoregressive models can be viewed as special or limiting cases of the STAR model. The applications presented in the first two chapters of this dissertation, Chapter I: Another look at Swedish Business Cycles, 1861-1988 Chapter II: Modelling asymmetries and moving equilibria in unemployment rates, make use of STAR models. In these two studies, STAR models are used to provide insight into dynamic properties of the time series which cannot be be properly characterised by linear time series models, and which thereby may be obscured by estimating only a linear model in cases where linearity would be rejected if tested. The applications being of interest in their own right, an important common objective of these two chapters is also to develop, suggest, and give examples of various methods that may be of use in discussing the dynamic properties of estimated STAR models in general.Chapter III, Testing linearity against smooth transition autoregression using a parametric bootstrap, reports the result of a small simulation study considering a new test of linearity against STAR based on bootstrap methodology.<br><p>Diss. Stockholm : Handelshögskolan, 1999</p>
11
MOREIRA, RODRIGO PINTO. "SMOOTH TRANSITION LOGISTIC REGRESSION MODEL TREE." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13437@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>FUNDAÇÃO DE APOIO À PESQUISA DO ESTADO DO RIO DE JANEIRO<br>Este trabalho tem como objetivo principal adaptar o modelo STR-Tree, o qual é a combinação de um modelo Smooth Transition Regression com Classification and Regression Tree (CART), a fim de utilizá-lo em Classificação. Para isto algumas alterações foram realizadas em sua forma estrutural e na estimação. Devido ao fato de estarmos fazendo classificação de variáveis dependentes binárias, se faz necessária a utilização das técnicas empregadas em Regressão Logística, dessa forma a estimação dos parâmetros da parte linear passa a ser feita por Máxima Verossimilhança. Assim o modelo, que é paramétrico não-linear e estruturado por árvore de decisão, onde cada nó terminal representa um regime os quais têm seus parâmetros estimados da mesma forma que em uma Regressão Logística, é denominado Smooth Transition Logistic Regression-Tree (STLR-Tree). A inclusão dos regimes, determinada pela divisão dos nós da árvore, é feita baseada em testes do tipo Multiplicadores de Lagrange, que em sua forma para o caso Gaussiano utiliza a Soma dos Quadrados dos Resíduos em suas estatísticas de teste, aqui são substituídas pela Função Desvio (Deviance), que é equivalente para o caso dos modelos não Gaussianos, cuja distribuição da variável dependente pertença à família exponencial. Na aplicação a dados reais selecionou-se dois conjuntos das variáveis explicativas de cada uma das duas bases utilizadas, que resultaram nas melhores taxas de acerto, verificadas através de Tabelas de Classificação (Matrizes de Confusão). Esses conjuntos de variáveis foram usados com outros métodos de classificação existentes, são eles: Generalized Additive Models (GAM), Regressão Logística, Redes Neurais, Análise Discriminante, k-Nearest Neighbor (K-NN) e Classification and Regression Trees (CART).<br>The main goal of this work is to adapt the STR-Tree model, which is the combination of a Smooth Transition with Regression model with Classi cation and Regression Tree (CART), in order to use it in Classification. Some changes were made in its structural form and in the estimation. Due to the fact we are doing binary dependent variables classification, is necessary to use the techniques employed in Logistic Regression, so the estimation of the linear part will be made by Maximum Likelihood. Thus the model, which is nonlinear parametric and structured by a decision tree, where each terminal node represents a regime that have their parameters estimated in the same way as in a Logistic Regression, is called Smooth Transition Logistic Regression Tree (STLR-Tree). The inclusion of the regimes, determined by the splitting of the tree's nodes, is based on Lagrange Multipliers tests, which for the Gaussian cases uses the Residual Sum-of-squares in their test statistic, here are replaced by the Deviance function, which is equivalent to the case of non-Gaussian models, that has the distribution of the dependent variable in the exponential family. After applying the model in two datasets chosen from the bibliography comparing with other methods of classi cation such as: Generalized Additive Models (GAM), Logistic Regression, Neural Networks, Discriminant Analyses, k-Nearest Neighbor (k-NN) and Classification and Regression Trees (CART). It can be seen, verifying in the Classification Tables (Confusion Matrices) that STLR-Tree showed the second best result for the overall rate of correct classification in three of the four applications shown, being in all of them, behind only from GAM.
12
Lee, Yee-nin, and 李綺年. "On a double smooth transition time series model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31215555.
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Korhonen, M. (Marko). "Nonlinearities in exchange rate: evidence from smooth transition regression model." Doctoral thesis, University of Oulu, 2005. http://urn.fi/urn:isbn:9514279468.
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Abstract
The purchasing power parity puzzle, exchange rate disconnection to macroeconomic fundamentals and pricing to market are central issues of international macroeconomics. Recent research has suggested that these issues can be presented by nonlinear behaviour. In this dissertation, we examine and explain the nonlinearities in the form of regime switching behaviour in real exchange rate series, exchange rate and macroeconomic fundamentals relation and exchange rate pass-through into consumer and import prices. Overall, we find evidence that nonlinearities are important in analysing empirical exchange rate models. The dissertation consists of four self-contained empirical studies.
In chapter 2 we examine whether the Markov switching models and exponential smooth transition autoregressive models can give any additional insights into real exchange rate behaviour for several OECD countries. The results show that there are long swings in the real exchange rate series, which can be characterize as a depreciation and an appreciation regime. These regimes are very persistent, although the processes are eventually mean reverting.
We estimate a multivariate smooth transition autoregressive model for the euro/dollar exchange rate in chapter 3. The significant point of our analysis is the possibility that a nonlinear specification for the exchange rate series might reveal aspects of the exchange rate dynamics that cannot be picked up by linear models. We find that the euro/dollar exchange rate may display random walk or near random walk behaviour within a certain range but the ability of the exchange rate to wander without any bound is limited by long-term government bond interest rate differentials.
In chapter 4 we examine nonlinear relationships between macroeconomic fundamentals and exchange rate for G-7 countries. We estimate a smooth transition error correction model that allows for parameter variation in the error correction form and interest rate differentials. The nonlinearity is determined by the inflation rate differentials between countries. We find significant error correction terms in monetary models. Our findings suggest the importance of nonlinear dynamics for examining deviations from the long-run equilibrium.
We examine whether the degree of exchange rate pass-through is dependent on importing country inflation rate in chapter 5. Our model shows that import prices respond differently to exchange rate changes when we are in a high inflation regime compared to a low inflation regime. We also present empirical evidence by estimating pass-through elasticises for several OECD countries. We find that consumer prices are not very sensitive to exchange rate changes. For aggregate import prices, we find partial or full exchange rate pass-throughs.
The tested nonlinear regime specific models proved appropriate for testing exchange rate dynamics for several currency pairs. Furthermore, we were able to present that macroeconomic fundamentals are important predictors of exchange rates.
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Oztek, Mehmet Fatih. "Modeling Co-movements Among Financial Markets: Applications Of Multivariate Autoregressive Conditional Heteroscedasticity With Smooth Transitions In Conditional Correlations." Phd thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615713/index.pdf.
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The main purpose of this thesis is to assess the potential of emerging stock markets and commodity markets in attracting the attention of international investors who utilize various portfolio diversification strategies to reduce the cumulative risk of their portfolio. A successful portfolio diversification strategy requires low correlation among financial markets. However, it is now well documented that the correlations among financial markets in developed countries are very high and hence the benefits of international portfolio diversification among these markets have been very limited. This fact suggests that investors should look for alternative markets whose correlations with developed markets are low (or even negative if possible) and which have high growth potentials. In this thesis, two emerging countries'<br>stock markets and two commodity markets are considered as alternative markets. Among emerging countries, Turkey and China are chosen due to their promising growth performance since the mid-2000s. As commodity markets, agricultural commodity and precious metal markets are selected because of the outstanding performance of the former and the "<br>safe harbor"<br>property of the latter. The structures and properties of dependence between these markets and stock markets in developed countries are examined by modeling the conditional correlation in the dynamic conditional correlation framework. The results reveal that upward trend hypothesis is valid for almost all correlations among market pairs and market volatility plays significant role in time varying structures of correlations.
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AMARAL, LUIZ FELIPE MOREIRA DO. "A SMOOTH TRANSITION PERIODIC AUTO REGRESSIVE MODEL FOR SHORT TERM ELECTRICITY LOAD FORECAST." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9916@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Essa tese considera um modelo não linear para se obter
previsões de curto
prazo de carga de energia elétrica. O modelo combina um
modelo de múltiplos
regimes auto-regressivo com transição suave com um
periódico auto-regressivo
criando o modelo de múltiplos regimes periódico com
transição suave (STPAR).
Um método de construção do modelo é desenvolvido com
métodos estatísticos
simples e um teste de linearidade contra a hipótese de
modelo periódico autoregressivo
com transição suave. Outros dois destes foram elaborados
para se
avaliar o modelo estimado: um teste de Multiplicador de
Lagrange (LM) para a
hipótese de auto-correlação serial dos resíduos e outro
teste LM para a hipótese de
não linearidade remanescente. Um experimento de Monte
Carlo foi implementado
para avaliar a performance dos testes propostos. Estimação
por mínimos
quadrados não lineares é considerado. Finalmente, dados de
carga de energia
elétrica do estado de New South Wales na Austrália são
apresentados e foram
usados como exemplo real. Outros modelos foram utilizados
para comparar a
performance do modelo.<br>This thesis considers a non linear approach to obtain
short term forecast for
electricity load. The model combines a smooth transition
autoregressive process
with a periodic autoregressive time series model, creating
the Smooth Transition
Periodic Autoregressive (STPAR) model. A model-building
procedure is
developed and a linearity test against smooth transition
periodic auto-regressive is
proposed. Other two tests were created to evaluate the
model: a Lagrange
multiplier (LM) test for the hypothesis of no error
autocorrelation and LM-type
test for the hypothesis of no remaining non-linearity. A
Monte Carlo experiment
was implemented to evaluate the performance of the
proposed tests. Estimation by
nonlinear least squares is considered. Finally, load data
from New South Wales
State in Australia`s electricity retail market is
presented and will be used as a real
example. Other models were used to compare the performance
of the proposes
model.
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Eliasson, Ann-Charlotte. "Smooth transitions in macroeconomic relationships." Doctoral thesis, Stockholm : Economic Research Institute, Stockholm School of Economics (Ekonomiska forskningsinstitutet vid Handelshögsk.) (EFI), 1999. http://www.hhs.se/efi/summary/516.htm.
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Rocha, Jordano Vieira. "Forecast comparison with nonlinear methods for Brazilian industrial production." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/13661.
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Previous issue date: 2015-04-07<br>This work assesses the forecasts of three nonlinear methods — Markov Switching Autoregressive Model, Logistic Smooth Transition Autoregressive Model, and Autometrics with Dummy Saturation — for the Brazilian monthly industrial production and tests if they are more accurate than those of naive predictors such as the autoregressive model of order p and the double differencing device. The results show that the step dummy saturation and the logistic smooth transition autoregressive can be superior to the double differencing device, but the linear autoregressive model is more accurate than all the other methods analyzed.<br>Este trabalho avalia as previsões de três métodos não lineares — Markov Switching Autoregressive Model, Logistic Smooth Transition Autoregressive Model e Autometrics com Dummy Saturation — para a produção industrial mensal brasileira e testa se elas são mais precisas que aquelas de preditores naive, como o modelo autorregressivo de ordem p e o mecanismo de double differencing. Os resultados mostram que a saturação com dummies de degrau e o Logistic Smooth Transition Autoregressive Model podem ser superiores ao mecanismo de double differencing, mas o modelo linear autoregressivo é mais preciso que todos os outros métodos analisados.
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Strikholm, Birgit. "Essays on nonlinear time series modelling och hypothesis testing." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-535.
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There seems to be a common understanding nowadays that the economy is nonlinear. Economic theory suggests features that can not be incorporated into linear frameworks, and over the decades a solid body of empirical evidence of nonlinearities in economic time series has been gathered. This thesis consists of four essays that have to do with various forms of nonlinear statistical inference. In the first chapter the problem of determining the number regimes in a threshold autoregressive (TAR) model is considered. Typically, the number of regimes (or thresholds) is assumed unknown and has to be determined from the data. The solution provided in the chapter first uses the smooth transition autoregressive (STAR) model with a fixed and rapid transition to approximate the TAR model. The number of thresholds is then determined using sequential misspecification tests developed for the STAR model. The main characteristic of the proposed method is that only standard statistical inference is used, as opposed to non-standard inference or computation intensive bootstrap-based methods. In the second chapter a similar idea is employed and the structural break model is approximated with a smoothly time-varying autoregressive model. By making the smooth changes in parameters rapid, the model is able to closely approximate the corresponding model with breaks in the parameter structure. This approximation makes the misspecification tests developed for the STR modelling framework available and they can be used for sequentially determining the number of breaks. Again, the method is computationally simple as all tests rely on standard statistical inference. There exists literature suggesting that business cycle fluctuations affect the pattern of seasonality in macroeconomic series. A question asked in the third chapter is whether other factors such as changes in institutions or technological change may have this effect as well. The time-varying smooth transition autoregressive (TV- STAR) models that can incorporate both types of change are used to model the (possible) changes in seasonal patterns and shed light on the hypothesis that institutional and technological changes (proxied by time) may have a stronger effect on seasonal patterns than business cycle. The TV-STAR testing framework is applied to nine quarterly industrial production series from the G7 countries, Finland and Sweden. These series display strong seasonal patterns and also contain the business cycle fluctuations. The empirical results of the chapter suggest that seasonal patterns in these series have been changing over time and, furthermore, that the business cycle fluctuations do not seem to be the main cause for this change. The last chapter of the thesis considers the possibility of testing for Granger causality in bivariate nonlinear systems when the exact form of the nonlinear relationship between variables is not known. The idea is to linearize the testing problem by approximating the nonlinear system by its Taylor expansion. The expansion is linear in parameters and one gets round the difficulty caused by the unknown functional form of the relationship under investigation.<br><p>Diss. Stockholm : Handelshögskolan, 2004</p>
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Okumu, Emmanuel Latim. "Non-linear prediction in the presence of macroeconomic regimes." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297222.
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This paper studies the predictive performance and in-sample dynamics of three regime switching models for Swedish macroeconomic time series. The models discussed are threshold autoregressive (TAR), Markov switching autoregressive (MSM-AR), and smooth-transition autoregressive (STAR) regime switching models. We perform recursive out-of-sample forecasting to study the predictive performance of the models. We also assess the in-sample dynamics correspondence to the forecast performance and find that there is not always a relationship. Furthermore, we seek to explore if these unrestricted models yield interpretable results regarding the regimes from an macroeconomic standpoint. We assess GDP-growth, the unemployment rate, and government bond yields and find evidence of Teräsvirta's claims that even when the data has non-linear dynamics, non-linear models might not improve the forecast performance of linear models when the forecast window is linear.
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Strobel, Felix. "Three Essays on the Role of Fiscal Stress for the Size of the Government Spending Multiplier." Doctoral thesis, Humboldt-Universität zu Berlin, 2017. http://dx.doi.org/10.18452/18063.
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Gegenstand dieser Dissertation ist die Rolle fiskalischen Stresses auf die Größe des Staatsausgabenmultiplikators. Hierbei werden zuerst die Folgen von empirisch identifizierten Staatsausgabenschocks in Italien untersucht. Dies geschieht sowohl in einem Zustand mit hohen Risikospreads auf Staatsanleihen, als auch in einem Zustand mit niedrigen Risikospreads. Das Resultat ist, dass kumulative Multiplikatoren kleiner sind, wenn das Ausfallrisiko von Staatsanleihen hoch ist. Zweitens erklärt die Dissertation dieses empirische Resultat im Rahmen eines DSGE Models. Im Model verdrängt ein Anstieg der Staatsausgaben private Investitionen. Der Verdrängungseffekt wird durch fragile Banken und die Rolle aggregierten Risikos ausreichend verstärkt, so dass fiskalischer Stress zu sehr kleinen oder sogar negativen Multiplikatoren führen kann.
Zuletzt untersuche ich die Rolle fiskalischen Stresses auf den Staatsausgabenmultiplikator unter der Nebenbedingung, dass die nominale Zinsuntergrenze bei null bindet. In diesem Szenario kann sich der Effekt fiskalischen Stresses ins Gegenteil verkehren und der Staatsausgabenmultiplikator groß werden.<br>This thesis examines the role of fiscal stress on the size of the government spending multiplier. First, it explores the dynamic consequences of empirically identified government spending shocks in Italy in a regime with high sovereign bond yield spreads and a regime with low spreads. It finds that cumulative multipliers are lower when sovereign risk spreads are high. Secondly, the thesis explains the empirical result of small government spending multipliers in times of high levels of fiscal stress in the context of a DSGE Model. In this model, an increase in government spending crowds out private investment. A fragile banking sector and aggregate risk amplify the crowding out of investment sufficiently to imply small multipliers in the presence of fiscal stress.
Finally, I analyze the role of fiscal stress on the multiplier, when the economy is at the zero lower bound for nominal interest rates and find that in this scenario, the effect of fiscal stress is reversed and the government spending multiplier is large.
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Chiang, Yu-Yun, and 江昱昀. "Bayesian Inference for Smooth Transition Autoregressive Model." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/9a7duw.
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碩士<br>中原大學<br>應用數學研究所<br>106<br>The Bayesian statistics have been successfully commonly applied in many fields. The BUGS project, including OpenBUGS and its Windows version WinBUGS, has been one of the popular Bayesian soft. In BUGS language, users specify a statistical model by simply stating the likelihood function and the prior distributions of the corresponding parameters, then OpenBUGS computationally approximates the estimates of the empirical distribution by the MCMC methods.
In this thesis, we consider to analyze the simulated data from smooth transition autoregressive (STAR) model using a newly developed R NIMBLE package, which is also defined in BUGS language and is much faster than OpenBUGS. Finally, the mean squared error of the estimates are computed to demonstrate the effectiveness of the MCMC method.
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Chang, Hsin-Fang, and 張馨方. "Dynamics of Sovereign Credit Default Swaps:Evidence from Smooth Transition Autoregressive Model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/50035188747294642022.
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碩士<br>元智大學<br>財務金融學系<br>98<br>This paper investigate the dynamics behavior of sovereign five year credit default swaps employing nonlinear smooth transition autoregressive (STAR) framework to observe the shock of financial crisis. Daily CDS data is analyzed from January 1, 2004 to September 1, 2009. Consider the previous one period with CDS, stock index, and bond separately as independent variable to examine the time series of sovereign CDS. From our study, several empirical results are found as follows: First, the nonlinear models have been proved to outperform the linear ones. Second, the important result of STAR point out that the break point of the regime shift occurs from the beginning of the financial crisis. Third, when using the previous one period with stock index to examine the time series of sovereign CDS, the results of the threshold value are consistency in each developed market. Finally, the emerging market reflects smaller on the financial shock than the developed market.
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Chang, Chun-Ju, and 張君如. "Arbitrage in the exchange market - Analysis by smooth transition autoregressive model." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/09420464654873968838.
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碩士<br>國立臺灣大學<br>國際企業學研究所<br>101<br>Interest rate parity (IRP) is a basic theory in the economic knowledge. The goal in my research is to prove that theory is true or not. I set Japanese Yen (JPY) is the funding currency. And the target currency is USD、TWD、AUD 、NZD and EURO. To determine whether arbitrage exists or not by analyzing of the datum between 2000 and 2012.
In the first, the result demonstrates that in the cases of Australia against Japan、New Zealand against Japan and Euro zone against Japan, the forecast value is almost the same with the actual value, but the forecast value is delay. Secondly, the averages of these datum don’t surpass 0.1. So I think arbitrage doesn’t exist. In the other hand, after 2007, In the case of Taiwan against Japan is not stable, and the forecast value is not related to the actual value. I guess some economic things happened so that this two values are not the same. But I can find the average of this data is about 0.0283, arbitrage doesn’t exist.
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Lee, Yu-Han, and 李宥翰. "The Empirical Study of Stock Market Returns in Smooth Transition Autoregressive Model." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/71844158646906873414.
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碩士<br>淡江大學<br>財務金融學系碩士班<br>95<br>This paper examines the nonlinear dynamics in stock returns which includes Taiwan、 South Korea、Singapore、Honk Kong、Japan、United States of America and China by using Smooth Transition Autoregressive Model (STAR) and using the lag of stock return as the transition variable.
Under the STAR model made by Teräsvirta (1992), we have several results. First, the lags of stocks return are different in each country. Meanwhile, all countries have two thresholds and three regimes. Moreover, all stock returns can be explained by Quadratic Logistic Smooth Transition Autoregressive Model (QLSTAR). By crossing the thresholds fastest and smoothest, the stock returns will have different nonlinear dynamics behaviors. Furthermore, the faster and smoothness regime change is the Shanghai Composite Index; the slowest is the Straits Times Index. Finally, the Shanghai Composite Index has the largest distance between two thresholds; the TSEC weighted index has the smallest distance between the two thresholds.
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Liu, Kun-Chao, and 劉坤肇. "Explore the Underwriting Cycle on Property/Liability Reinsurance in Taiwan by Smooth Transition Autoregressive Model." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/29830915417498275191.
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碩士<br>國立高雄第一科技大學<br>風險管理與保險研究所<br>99<br>The presence of underwriting profit cycle in property/liability insurance has become a well-known feature. The main purpose of this study is to examine the presence of underwriting cycle of the property/liability reinsurance’s in Taiwan, and to discuss which variables actually influence the underwriting cycle by Second-Order Autoregressive model at first, and it turns out there is no AR(2) underwriting cycle exists. And then we apply the Smooth Transition Autoregressive Model (STAR) to test for a regime shift, since we have evidence that there are non-linear relationships between the capacity ratios and the profit ratios, and also between interest rate and the profit ratios, which imply that the insurance market is dominated by two regimes. The results of our empirical analysis suggest the interest rate and the capacity ratios of the industry would cause the underwriting cycles.
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Chen, Li-Yu, and 陳麗玉. "Nonlinear Dynamics between ADRs and the Underlying Stock- An Evaluation of the Smooth Transition Autoregressive Model." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/u4f5we.
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碩士<br>淡江大學<br>財務金融學系碩士在職專班<br>97<br>Abstract：
Because of factors such as transaction costs, the prices of ADRs and their underlying shares converge within a non-linear framework. This paper selected the STAR（smooth transition autoregressive）model, proposed by Teräsvirta（1994）to model the convergence. We used the STAR model and a sample of 6 dually listed shares（listed in Taiwan and on the NYSE and NASDAQ）to investigate the convergence between the prices of ADRs and the prices of the Taiwanese-traded shares. These 6 dually listed shares are TSM, UMC, ASX, SPIL, AUO and CHT.
We found that the convergence of the ADRs and their underlying shares was non- linear except for ASX.
Because the market is imperfect, it exhibits non-linear convergence, where the actual price deviates from price parity. In this study we offer investors in ADRs and their underlying shares information and knowledge about the market price convergence of ADRs and their underlying shares.
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Li, Chi-Hung, and 李奇鴻. "A Study of the Underwriting Cycle on Fire Insurance in Taiwan:An Application of Smooth Transition Autoregressive Model." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/84548832181501501184.
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碩士<br>國立高雄第一科技大學<br>風險管理與保險研究所<br>99<br>The thesis focuses on the research of the underwriting cycle of the profit index of fire insurance in Taiwan from 1970 to 2009. Above all, we utilize second-order autoregressive model to analyze the profit rate of fire insurance and the economic profit rate in Taiwan. We find that the payoff index would not be affected by the interest rate and there is no underwriting cycle under the fire insurance in Taiwan.
However, there might be some nonlinearity characteristics in the profit index. Therefore, we use the smooth transition autoregressive nonlinearity (STAR) model to analyze this issue. By implementing the tests of linearity, we find that the cause of profit index conversion might be taking the log of the self- retained premium on the owner’s equity before taking 1st difference.
The results under the STAR model estimate are as below. First, we find that the nonlinearity characteristic of profit index actually exists and the STAR model is superior to the AR(2) model. Second, when the capacity changes in a great range, this will lead to a fast state transition but it just lasts only for few years, and the rest of time period would always stay in the lower regime. Third, the change of interest rate has a positive effect on the profit index. Fourth, same as the AR(2) model, it also suggests that there is no underwriting cycle of the fire insurance in Taiwan.
In this study, we find that the insurance premium paid and the interest rate have the phenomenon of cointegration. Therefore, we use the smooth transition autoregressive error correction model to analyze the fire insurance premium paid in Taiwan. The result suggests that there are only a few short period when the change of the interest rate and the rate of the change of the premium are positively correlated; however, in the rest of the time, they have a negative correlation.
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Lu, Yun-Ju, and 盧韻如. "The study on the impact of macroeconomic environment to IPOs volumes-application of smooth transition autoregressive model." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/58535013310161137139.
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碩士<br>淡江大學<br>國際貿易學系國際企業學碩士班<br>96<br>This article adopted Taiwan stock index, discount rate and GDP as representative variables of market environment. It also used nonlinear smooth autoregressive model to research connections between IPOs volumes and market environment over the years. Over the past, what has been used often was looking into linear model as the research template; it is however, that time series data in the long term could cause possible structural transformation without being covered by traditional linear model. Therefore, this article will focused on using nonlinear smooth autoregressive model to attest the effect of the above variables toward IPOs volumes and at the same time testifying whether there is the existence of heterogeneity smooth transition phenomena.
The final result turned out to be that there is the existence of structural transformation within our IPOs volumes. Among those three variables mentioned above, only GDP and discount rate cause major effect toward IPOs volumes. Under the condition of using GDP as transition variables, the lag of GDP and discount rate did contribute diverse structural transformation.
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Lin, Jang-Ying, and 林瀼縈. "The Nonlinear Relationship Between The Bank Liquidity Risk And Operational Performance-Application of Panel Smooth Transition Autoregressive Model." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/z6z9kd.
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碩士<br>淡江大學<br>財務金融學系碩士班<br>102<br>The 2007 U.S. happened subprime mortgage crisis, coupled with the asset securitization and structured finance products. The financial institutions invest in subprime mortgage–related derivative financial instruments and suffered a shock, loss liquidity. A number of financial institutions went bankrupt, triggering the global financial crisis. To this end, BCBS released “International Framework for Liquidity Risk Measurement, Standards and Monitoring”. BSBC proposed liquidity coverage ratio and net stable funding ratio.
This paper used panel smooth transition autoregressive model to determine whether the liquidity risk to banking performance exist panel smooth transition effect. When liquidity reserves ratio is less than 23.5375%, it is positively relevant between loan-to-deposit ratio and banking performance, while it is negatively relevant between non-performing loans ratio and banking performance, it is negatively relevant between banking size and banking performance. When liquidity reserves ratio is greater than 23.5375%, it is negatively relevant between non-performing loans ratio and banking performance, it is negatively relevant between banking size and banking performance. When liquid assets ratio is less than 0.119%, it is negatively relevant between banking size and banking performance ,but it is positively relevant between BIS ratio and banking performance. When liquid assets ratio is greater than 0.119%, it is negatively relevant between banking size, BIS ratio and banking performance.
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Tsai, Chung-Heng, and 蔡仲恆. "Study on feasibility of carry trade - Validation of interest rate parity based on the smooth transition autoregressive model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/79144449008731123585.
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碩士<br>國立臺灣大學<br>國際企業學研究所<br>98<br>This empirical study of Covered Interest Rate Parity (CIRP) is conducted on the basis of non-linear Smooth Transition Autoregressive Model, focusing on five areas including Japan, the United States, Australia, the United Kingdom, and the Euro zone. When CIRP holds, no abnormal gain can be derived from carry trade; in contrast, when CIRP cannot be supported, capital holders can obtain abnormal profit from carry trade.
The result demonstrates that a linear relationship exists in the difference (D) between interest spread and forward exchange rate discount (or premium) of the Euro zone and Japan. In the cases of Australia against Japan and the UK against Japan, STAR model can be used to describe the process of adjustment for D`s deviation. While the high speed of transition (γ) of the United States against Japan causes STAR model to recede to TAR model. These three non-linear models possess excellent predictive power, according to the root mean square error.
In the forecasted periods, CIRPs of the United States against Japan and the UK against Japan sustain in nearly all periods, suggesting the financial markets and the foreign exchange markets are efficient. Therefore, capital holders cannot obtain abnormal profit from carry trade. In the case of Australia against Japan, CIRP can be supported only in the initial periods. Then it gradually deviates from CIPR equilibrium in the long term, causing inefficiency of the financial markets and the foreign exchange markets. Hence, investors can obtain abnormal profit from carry trade.
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LEE, SONG-SIOU, and 李松修. "The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/54661775463446713392.
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碩士<br>國立臺北大學<br>企業管理學系<br>100<br>This paper attempts to investigate how the TAIEX stock returns were adjusted through time path with and without macroeconomic variables using monthly sample data from June 1996 to June 2011. By employing smooth transition autoregressive model(STAR) and ANSTGARCH model to depict asymmetric and nonlinear behaviors of the TAIEX returns, the findings are listed below.
1. TAIEX returns adjust in non-linear path.
2. The LSTAR model is better than the ESTAR model in measuring TAIEX returns adjustment process.
3. The STAR-ANSTGARCH model could properly estimate the asymmetric and nonlinear behavior of conditional mean and variance of TAIEX returns.
4. The Taiwan Coincident indicator could effectively explain the conditional mean and conditional variance of TAIEX returns.
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Wei, Sin-Han, and 魏新翰. "The Effect of Mortgage Interest Rate and Money Supply on House Price—The Application of Smooth Transition Autoregressive Model." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/4uq55a.
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碩士<br>國立中山大學<br>財務管理學系研究所<br>102<br>The purpose of the research is to find out whether the nonlinear relationship exist between the house price and the financial factors，include mortgage interest rate.and money supply growth rate，which are under the government’s control. Quarterly data on Sin-Yi housing index(1998Q1~2012Q2) and Taipei presale house prices (1971Q1 ~2012Q2) are used for empirical study, which represent presales and existing house prices. The research is essentially constructed by the STAR(Smooth Transition Autoregressive model).In addition, the research also try to examine whether the relationship had changed after Financial Liberalization in 1990.
The major findings are as follows: First,，There is nonlinear relationship between mortgage interest rate、money supply growth rate and house prices，both Sin-Yi housing index and Taipei presale house prices. The effect of mortgage interest rate and money supply growth rate on the Sin-Yi housing index before 2004 is different from after 2004.And in the samples of Taipei presale house prices，the prior house prices growth rate have a positive effect on the current house prices growth rate. Second，under most circumstances，the mortgage interest rates have significant negative effect on house prices，which proves that mortgage interest rates is a important factor for house prices. Third，there is no significant nonlinear relationship between mortgage interest rate、money supply growth rate and Taipei presale house prices after 1990.Simply put，the government can view mortgage interest as an effective tool to adjust the real estate market.
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Huang, Ya-Chi, and 黃雅琦. "A Study of the Underwriting Cycle on Property/Liability Insurance in Japan: An Application of Smooth Transition Autoregressive Model." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/66262482442723936205.
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碩士<br>國立高雄第一科技大學<br>風險管理與保險研究所<br>99<br>The objective of this study is to examine the presence of the property/liability insurance’s underwriting cycle in Japan, and comparing the Smooth Transition Autoregressive Model alternative to Second-Order Autoregressive Model. We test two kinds of Loss ratio data from 1960-2006 and find there’s no cycle when we estimate parameters by Second-Order Autoregressive Model.
Furthermore, this paper discuss the relationship between several variables, i.e., the discount rate, GDP, profits or surplus, Nikkie (index) and loss ratio. When we use some ratio as a transition variable, then estimate parameters by Smooth Transition Autoregressive Model, the results find that the economic environment can explain partly the phenomenon of underwriting cycle.
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Hsueh, Yen-An, and 薛晏安. "A Study of the Underwriting Cycle on Property/Liability Insurance in Taiwan: An Application of Smooth Transition Autoregressive Model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/08520931831352712067.
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碩士<br>國立高雄第一科技大學<br>風險管理與保險所<br>98<br>The objective of this study is to examine the presence of the property/liability insurance’s underwriting cycle in Taiwan, and comparing the Smooth Transition Autoregressive Model alternative to Second-Order Autoregressive Model. We test three aggregate profit ratio data from 1970-2005 and find there’re no cycle when we estimate parameters by Second-Order Autoregressive Model. But, when we use some ratio represent the capacity as a transition variable and choose appropriate one, then estimate parameters by Smooth Transition Autoregressive Model, the cycle are present in particular regime which length about 4.5 years.
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Wang, Sheng-hsiung, and 王聖雄. "Estimating and Forecasting the Behavior of Real Effective Exchange Rate with Asymmetric Smooth Transition Autoregressive Model─Evidence from Taiwan Market." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/4gzv8u.
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碩士<br>朝陽科技大學<br>財務金融系碩士班<br>92<br>The debate of this paper is to test for, estimating, and model non-linearities in the real effective exchange rate of Taiwan market. To model non-linear behavior in exchange rate, we apply the STAR(Smooth Transition Autoregressive) family of models. STAR models imply the existence of two distinct regimes in exchange rate, with potentially different dynamic characteristics, but the transition between the regimes is smooth. The real exchange rate process is to reject linearity, and there appears to be some evidence of asymmetry. In an out-of-sample
forecasting contest, STAR models overtake AR(1)(autoregressive model)
model.
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Sue, Pei-shuan, and 蘇姵璇. "The dynamic relationship between stock index and index futures-the applications of smooth transitional autoregressive model." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/34337439115924704872.
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碩士<br>國立暨南國際大學<br>國際企業學系<br>97<br>This thesis investigates the behaviors of the basis change mainly in TAIEX and HSI and we chose four indexes from European, including DAX 30, ATX, BEL 20 and IBEX 35. Weekly data are analyzed over the period February 1999 to 2009. Our purpose is to find out if the basis shows the evidence of non-linear property and smooth transition after it deviating from the equilibrium level.
Our findings reveal that the basis of the six markets showing the evidence of non-linearity property and have mean reversion after deviating from the equilibrium level. We also find out that it is better to use ESTAR model in DAX 30 and BEL 20 to illustrate symmetric characteristic and LSTAR model in TAIEX, HSI, ATX and IBEX 35.
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Zhang, Kai. "Does purchasing power parity hold between European countries? : investigation using non-linear STAR model." Master's thesis, 2012. http://hdl.handle.net/10400.14/15429.
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This paper investigates whether purchasing power parity (PPP) holds or not between each European country. PPP is a fundamental building block of international economics. The research of PPP not only can help economist understand exchange rate behaviour, but also assist with monetary maker to establish sensible exchange rate policies. For examining the PPP validity in euro, this paper starts at a general introduction of the exchange rate importance. The following is an in-depth overview of PPP studies and econometric technique developments since 1970s. We applied the non-linear Exponential Smooth Transition Autoregressive (ESTAR) for a new test (KSS test) and ADF test to the real exchange rates between 9 European countries. The results demonstrate the new test giving more support to PPP than that of ADF test. And while the linear ADF test can only reject a unit root in 6 cases, the new test is able to reject in 13 cases out of 36, which are in favour of PPP and offer evidences of non-linear mean reversion in real exchange rate.
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Xu, Wan. "Employment and Business Establishment Growth in the Appalachian Region, 2000-2008: An Application of Smooth Transition Spatial Autoregressive Models." 2011. http://trace.tennessee.edu/utk_gradthes/1039.
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Industry clusters can be important components of regional development. The effects of industry clusters on growth typically vary across geography, which has implications for targeted development strategies. Employment and business establishment growth in the Appalachian region (2000 – 2008) was regressed on industry cluster concentration indexes controlling for local determinants. The hypothesis that local response to growth determinants is geographically heterogeneous was tested using Smooth Transition spatial process models. This class of models exhibiting regime switching behavior is useful for identifying regional clusters, providing another tool for exploring relationships between geographical determinants and economic growth.
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Grégoire, Gabrielle. "Sur les modèles non-linéaires autorégressifs à transition lisse et le calcul de leurs prévisions." Thèse, 2019. http://hdl.handle.net/1866/22550.
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Hejlová, Hana. "Vliv sekuritizace na dynamiku cen bydlení ve Španělsku." Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-338776.
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The thesis tries to explain different nature of the dynamics during the upward and downward part of the last house price cycle in Spain, characterized by important rigidities. Covered bonds are introduced as an instrument which may accelerate a house price boom, while it may also serve as a source of correction to overvalued house prices in downturn. In a serious economic stress, lack of investment opportunities motivates investors to buy the covered bonds due to the strong guarantees provided, which may in turn help to revitalize the credit and housing markets. To address such regime shift, house price dynamics is modelled within a framework of mutually related house price, credit and business cycles using smooth transition vector autoregressive model. Linear behaviour of such system is rejected, indicating the need to model house prices in a nonlinear framework. Also, importance of modelling house prices in the context of credit and business cycles is confirmed. Possible causality from issuance of covered bonds to house price dynamics was identified in this nonlinear structure. Finally, threat to financial stability resulting from rising asset encumbrance both in the upward and downward part of the house price cycle was identified, stressing the need to model impact of the covered bonds on house prices in...
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Tsai, Yu-Jung, and 蔡育蓉. "Nonlinear Smooth Transition Error Correction Model in Exchange Rates." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/66272674641321577010.
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碩士<br>淡江大學<br>財務金融學系碩士班<br>95<br>Recent research has increasingly suggested that exchange rates may be characterized by non-linear behaviors. The purpose of this paper is to investigate the exchange rates in Taiwan. The exchange rates include spot and forward exchange rates, and furthermore the forward rates include 10-days、30-days、60-days、90-days、180-days. We examined whether a series of spot and forward exchange rates exhibit non-linear smooth transition error correcting dynamic behaviors.
The results show that all series of spot and forward exchange rates except 180-days have cointegrating relationship which is predicted by the Expectation Hypothesis. We consider error-correction term as a transition variable for non-linear error correction models. This paper finds that the smooth transition error correction model (STECM) may be appropriate to analyzing the series of spot and forward exchange rates. The evidence propose that the LSTECM model is the best for all series of spot and forward exchange rates, which means the adjustment behaviors from lower regime to upper regime is smooth not jump.
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Hung, Te-Wang, and 洪德旺. "Taiwan Money Demand Function in Smooth Transition Error Correction Model." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/34749653163796570561.
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碩士<br>淡江大學<br>財務金融學系碩士班<br>97<br>Most models of the past research on macroeconomic variables are linear ones. However, since Granger and Teräsvirta proposed the smooth transition regression (STR) methodology, discussing macroeconomic variables by applying nonlinear models are going to be the mainstream. The purpose of this paper is to test and diagnose if the money demand of Taiwan exists any nonlinear forms .
Empirical results indicate that real M2,real GDP, real exchange rate and saving deposit rate have a long term relationship under some specific threshold value. On the selection of choosing models, it is more suitable to select the LSTECM model which has better capacity than other linear models to explain macroeconomic meanings.
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Chen, Kuan-Yu, and 陳冠宇. "Optimal Asset Allocation using Black-Litterman with Smooth Transition Model." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/wyg5qy.
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碩士<br>國立中央大學<br>統計研究所<br>106<br>In fi nancial markets, the model proposed by Markowitz is widely used in investment.However, the sensitive parameters lead to make errors in practice easily that results in poor returns. In this project, we use the Black-Litterman model to establish the portfolio, and the expected rate of return can be corrected by the implied return combined with the investor’s views. In addition, we also use the ST-GARCH model to capture large fl uctuations in the data. The ST model can be used to adjust parameters in the model, making the ST-GARCH model more fl exible than the simple AR-GARCH model. Finally, we use the leading stocks in various industries in Taiwan stock market in empirical analysis.
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蔡蓓婷. "Taiwan Money Demand Function in Smooth Transition Error Correction Model." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/87420003218534739742.
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碩士<br>淡江大學<br>財務金融學系<br>92<br>The article applied nonlinear model to build up the Taiwan money demand function in smooth transition error correction model. The main purpose is to analyze the short-run dynamic adjustment to long-run equilibrium in money demand function. Take Taiwan as a small open economy system, the exchange rate, income and interest rates are the endogeneous variables in money demand function, then estimate the money demand function.
About econometric method, the article applied maximum likelihood test to get a long-run cointegration relation, then build up the linear error correction model. But after error and model test, the linear error correction model isn''t suitable for analyze Taiwan money demand function’s short-run dynamic adjustment behavior. Therefore applied the LM-type test on the linearity. We reconfirm nonlinear logistic smooth transition error correction model for the money demand function in Taiwan. Then through the serial correlation test, the normality test, the conditional heteroscedasticity for error, and the Ramsey’s model specification test, we find that use logistic smooth transition error correction model to analyze the adjustment behavior of money demand function in Taiwan than linear error correction model, and short-run dynamic adjustment have asymmetric smooth transition process.
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Ping, Wang Yu, and 王郁萍. "Analysis for Purchasing Power Parity of nonlinear smooth transition switching model." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/21964403414136445287.
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碩士<br>淡江大學<br>財務金融學系碩士班<br>97<br>In this paper, we examine the Purchasing Power Parity(PPP) in Japan, applying linearity tests by Teräsvirta (1994). Our results clearly reject linear model in favor of the nonlinear smooth transition switching model with two thresholds of transition variables. We respectively examine whether the PPP will be hold or not in the band of two thresholds or out of the band of two thresholds. We find if data in the band, the PPP will not be hold. Instead, if data out of the band, the PPP will be hold. We think this phenomenon result in nominal exchange rates exist the neutral band. The obstacles which impede PPP hold is also the main reason for existing the neutral band of nominal exchange rates. These obstacles include in the presence of transaction costs, tariff, heterogeneous expectation and interference by central bank. These obstacles also are called opportunity costs if on the economic views. When market is out of the equilibrium, and the gains from arbitrage are greater than the costs from arbitrage. The activities of arbitrage can bring the market to the equilibrium if activities of arbitrage can normally work. In this case, PPP will hold. By the contraries, if the gains from arbitrage are less than the costs from arbitrage, arbitrager won’t make arbitrage. So the market is still out of the equilibrium, the PPP will not be hold. We use the non-linear smooth transition switching model to examine the PPP, offering another explanation for PPP.
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Lin, Ya-Ping, and 林雅瓶. "Exchange Rate Forecasting-An Application of Panel Smooth Transition Auto-Regression Model." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/94167496038723556433.
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碩士<br>中原大學<br>國際經營與貿易研究所<br>101<br>With the operating of economic liberalization and internationalization, international finance has played an important role in a country’s economic development. Meanwhile, the linkage between a pair of currencies is exchange rate. However, the change in exchange rate is an extremely complex problem. In face of the uncertainty in international financial markets, foreign exchange exposure often erodes huge earnings of multinational enterprises. Therefore, carry out the global layout, the question regarding how to correctly forecast becomes an important task for the enterprises to actively expand their territory.
In literature, some factors are used to forecast exchange rates, including the interest rates, economic growth rates and inflation rates. Based on the considerations of searching costs of the above variable that influencing exchange rates, and the probable biased forecasting of the variables, this research uses the lagged exchange rates as the regressors to forecast current exchange rates. In addition, exchange rates may display a nonlinear time path, therefore, this research employs the panel smooth transition autoregressive model (PSTAR) proposed by González and Teräsvirta (2005) to trace out the dynamic path. In view of interest rate is an important factor that influences the change in exchange rate and can describe the change of monetary policy, the paper uses interest rate as the transition variable in the PSTAR model.
Empirically, we choose the G20 countries as sample objects. After the exclusion of incomplete information in Brazil, Argentina and Saudi Arabia and the Euro countries: Germany, France and Italy, there are 14 countries chosen. There 14 countries form 13 exchange rates used the USD as denominated. Sample period spans from January 2002 to August 2012; therefore, a total of 1664 observations.
Empirical results show that the exchange rates display a nonlinear dynamic path and there are at least one threshold value. Thus, the PSTAR model is more proper used to describe the change in exchange rate. In addition, lagged exchange rates have significant effects on current exchange rates, implying that the persistence of exchange rate is obvious.
Finally, the changes in exchange rates are influenced by interest rate in different regimes. The higher (lower) the interest rates are, the larger (smaller) the persistence of exchange rates would be.
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Lin, Chang-Zih, and 林昶字. "Asymmetric Smooth Transition Quantile Capital Asset Pricing Model with Time-Varying Effect." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/61705253078409625128.
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碩士<br>逢甲大學<br>統計與精算所<br>98<br>Capital asset pricing model (CAPM) has become a fundamental tool in finance for assessing the cost of capital, risk management, portfolio diversification and other financial assets. It is generally believed that the risks of assets should change over time or vary with the market returns. In this study, we propose a time-varying market risk (beta) for CAPM which adds a smooth transition function as a regime switching function, and fit a GARCH model in variance equation to consider the dynamic volatility. We use the quantile regression technique to investigate the change of market risk under various market conditions.
We introduce a smooth transition CAPM that can capture nonlinear behavior both in the mean and volatility in all quantile levels.
The parameter estimation is within the Bayesian framework.
We employ three of stocks from the Dow Jones Industrial Stocks to demonstrate our proposed model. We use deviance information criterion (DIC) in a comparison of our proposed model with the previous models. Our study shows that the proposed model is more appropriate for the data. The proposed model is more general and its coefficients have greater flexibility with a smooth transition function.
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Huang, Tsz-Fang, and 黃慈芳. "The Relationship Between Oil Price and Stock Return-Smooth Transition Regressive Model." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/55124098884800934931.
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碩士<br>國立高雄應用科技大學<br>金融資訊研究所<br>97<br>This paper employs smooth transition regression model, derived in Teräsvirta (1998), to investigate the non-linear relationship between oil prices and stock returns. Using rates of change in oil prices as threshold variable, this research shows whether the influences of oil price change on stock returns are the same between the different oil prices change regimes, researching monthly data of Taiwan from January 1985 to December 2007. The empirical results confirm the nonlinearity of link between oil prices change rates and stock returns. Rates of change in oil prices in the 7.03% threshold interval is divided into two regimes, the Taiwan stock returns in the high oil prices and low oil prices change rates, the extent of impact will be different. In other word, non-linear STR model describes dynamic effect of stock returns better than linear model.
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Wu, Hsin-Hung, and 吳信宏. "Uncovered Interest Rate Parity in a Time-Varying Smooth Transition Regression Model." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/07957192508227530032.
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碩士<br>國立高雄大學<br>經濟管理研究所<br>96<br>There are general findings by many studies criticizing that the linear model proposed by Fama (1984) is unable to validate uncovered interest parity (UIP) hypothesis. Therefore, some scholars presented theoretical motivation, e.g. , the presence of transaction cost (Sercu and Wu, 1992), the limitations to speculation hypothesis (Lyons, 2001) and the behavior of interventions (Mark and Moh, 2007). Baillie and Bollerslev (2000) also show that the magnitude and sigh of the estimated slop coefficient in the forward premium regression appears to be slowly time-varying.
The paper applies the time-varying smooth transition regression model proposed by Lundbergh, Teräsvirta and van Dijk (2003) to describe and distinguish nonlinearity and structural change (time-varying coefficients) simultaneously in modeling the monthly observations of US spot and 1-month forward exchange rate against the UK sterling and Canadaian dollar and Japanese Yen. The main finding of this research is that the nonlinear relationship is supported empirically. The UIP is not rejected all the time, and it can be justified from the dynamics of regime switching caused by time-variation and the behavior of speculation. But the limitation of setting the maximum endogenous breakpoint may not find out all possible structural breaks.
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Kang, Yu-Ming, and 康玉明. "The Relationship Between Derivatives and Firm Value:By using panel smooth transition regression model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/31345823466826032692.
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碩士<br>淡江大學<br>財務金融學系碩士班<br>98<br>This study is to investigate the panel smooth transition effect associated between derivatives and firm value. Utilizing the panel smooth transition regression model developed by Gonza’lez, Teräsvirta and Dijk (2004-2005), we test whether the derivatives use rate (hedge ration) can cause panel smooth transition effect on firm value.
The results showed that a transition period is generated when the hedge ratio falls at 12.7059%. Therefore, hedge ration does affect Tobin Q of firms, and reveal the characteristic of panel smooth transition effect.
We also examine the influence of controlling variables on firm value. For the firms with hight hedge ration, higher debt rate results in increase inTobin Q. On the contrary, it’s reduce of firm size .
Regardless of high or low hedge ration, more institution companies have the firms’ stocks ,the great Tobin Q they have. Therefore, our studies suggest that firms’ managers adopt appropriate control machinery or operating strategies according to different hedge ration, in order to come up with the best policy.