Relevant bibliographies by topics / Markov switching regime model / Dissertations / Theses
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Dissertations / Theses on the topic 'Markov switching regime model'

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Published: 4 June 2021
Last updated: 12 February 2022

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1

Stockel, Jakob, and Niklas Skantz. "Regime shifts in the Swedish housing market - A Markov-switching model analysis." Thesis, KTH, Fastigheter och byggande, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-190178.

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Problem statement: Accurate and reliable forecasts of trends in the housing market can be useful information for market participants as well as policy makers. This information may be useful to minimize risk related to market uncertainty. Since the burst of the housing bubble in the early 1990s the price level of single-family houses has risen sharply in Sweden. The Swedish housing market has experienced an unusually long period of high growth rates in transaction prices which has opened up for discussions about the risk of another housing bubble. Business and property cycles have shown to cont
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2

Koh, You Beng, and 辜有明. "Bayesian analysis in Markov regime-switching models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48521644.

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van Norden and Schaller (1996) develop a standard regime-switching model to study stock market crashes. In their seminal paper, they use the maximum likelihood estimation to estimate the model parameters and show that a two-regime speculative bubble model has significant explanatory power for stock market returns in some observed periods. However, it is well known that the maximum likelihood estimation can lead to bias if the model contains multiple local maximum points or the estimation starts with poor initial values. Therefore, a better approach to estimate the parameters in the regime-swi
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3

Cheung, Ka-chun. "Optimal asset allocation problems under the discrete-time regime-switching model." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B31311234.

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4

Spagnolo, Fabio. "Nonlinear error-correction models with regime switching." Thesis, Birkbeck (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368915.

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5

Chen, Ping. "Asset-liability management under regime-switching models." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43223928.

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6

Cheung, Ka-chun, and 張家俊. "Optimal asset allocation problems under the discrete-time regime-switching model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B31311234.

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7

Karadag, Mehmet Ali. "Analysis Of Turkish Stock Market With Markov Regime Switching Volatility Models." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12609787/index.pdf.

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In this study, both uni-regime GARCH and Markov Regime Switching GARCH (SW-GARCH) models are examined to analyze Turkish Stock Market volatility. We investigate various models to find out whether SW-GARCH models are an improvement on the uni-regime GARCH models in terms of modelling and forecasting Turkish Stock Market volatility. As well as using seven statistical loss functions, we apply Superior Predictive Ability (SPA) test of Hansen (2005) and Reality Check test (RC) of White (2000) to compare forecast performance of various models.
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8

Zhu, Jinxia. "Ruin theory under Markovian regime-switching risk models." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/b40203980.

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9

Chen, Ping, and 陈平. "Asset-liability management under regime-switching models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43223928.

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Zhu, Jinxia, and 朱金霞. "Ruin theory under Markovian regime-switching risk models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B40203980.

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11

Schwendener, Alvin. "Regime-Switching Modell für die Schätzung von Marktdynamiken." St. Gallen, 2006. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/01654086001/$FILE/01654086001.pdf.

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12

Spagnolo, Nicola. "Nonlinearity testing, model selection and forecasting in the prescence of Markov regime switching." Thesis, Birkbeck (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368914.

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13

Blöchlinger, Lea. "Power Prices - A Regime-Switching Spot/Forward Price Model with Kim Filter Estimation." kostenfrei, 2008. http://www.biblio.unisg.ch/www/edis.nsf/wwwDisplayIdentifier/3442.

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14

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 y
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15

Wu, Yanan. "ON THE PREDICTIVE PERFORMANCE OF THE STOCK RETURNS BY USING THE MARKOV-SWITCHING MODELS." Thesis, Uppsala universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412930.

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This paper proposes the basic predictive regression and Markov Regime-Switching regression to predict the excess stock returns in both US and Sweden stock markets. The analysis shows that the Markov Regime-Switching regression models out perform the linear ones in out-of-sample forecasting, which is due to the fact that the regime-switching models capture the economic expansion and recession better.
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16

Yang, Zijian. "Application of Regime Switching Model to Equity Market and Portfolio Selection." Thesis, University of Essex, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.517406.

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17

Tillmann, Peter. "Uncertainty and the stability of financial markets in open economies : empirical evidence from regime-switching models /." Aachen : Shaker, 2003. http://www.gbv.de/dms/zbw/369153375.pdf.

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18

Dias, Gustavo Fruet. "Uma estimativa da taxa de câmbio real com mudança de regime markoviano : uma análise para o Brasil 1994 a 2005." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2006. http://hdl.handle.net/10183/8785.

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A presente dissertação de conclusão de mestrado tem por objetivo contribuir com a literatura existente que versa acerca da estimação da Taxa de Câmbio Real (RER) através de fundamentos econômicos. O objetivo deste trabalho é utilizar o instrumental teórico de modelos com mudança de regime (Markov Switching) aplicado sobre os fundamentos que determinam a RER em um modelo de Cointegração. O modelo teórico utilizado para a estimação foi o proposto por Montiel (1999), modelo este que é mais indicado para países em desenvolvimento, para o período de 1994 até 2005. Os resultados obtidos na estimação
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19

Andersson, Sebastian. "On the Specification of Local Models in a Global Vector Autoregression: A Comparison of Markov-Switching Alternatives." Thesis, Uppsala universitet, Statistiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-226918.

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In this paper, focus is on the global vector autoregressive (GVAR) model. Its attractiveness stems from an ability to incorporate global interdependencies when modeling local economies. The model is based on a collection of local models, which in general are estimated as regular VAR models. This paper examines alternative specifications of the local models by estimating them as regime-switching VAR models, where transition probabilities between different states are studied using both constant and time-varying settings. The results show that regime-switching models are appealing as they yield i
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20

Spungin, Giles Edmund. "Essays on applications of Markov regime switching and time-varying volatility models in finance and macroeconomics." Thesis, Queen Mary, University of London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.497250.

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21

Duran, William Gonzalo Rojas. "Modelo GARCH com mudança de regime markoviano para séries financeiras." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-02072014-122143/.

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Neste trabalho analisaremos a utilização dos modelos de mudança de regime markoviano para a variância condicional. Estes modelos podem estimar de maneira fácil e inteligente a variância condicional não observada em função da variância anterior e do regime. Isso porque, é razoável ter coeficientes variando no tempo dependendo do regime correspondentes à persistência da variância (variância anterior) e às inovações. A noção de que uma série econômica possa ter alguma variação na sua estrutura é antiga para os economistas. Marcucci (2005) comparou diferentes modelos com e sem mudança de regime em
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22

Perl, Robert. "Die Erwartungstheorie der Zinsstruktur : variable Zeitprämien, Regimeunsicherheit und Markov-Switching-Modelle ; eine empirischen Analyse für den deutschen Rentenmarkt /." Frankfurt am Main [u.a.] : Lang, 2003. http://www.gbv.de/dms/zbw/362547947.pdf.

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23

Abdelbaky, Mahmoud. "Exchange rate regimes in Middle East and North Africa (MENA) : a Markov switching model approach /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1251858811&sid=26&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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24

Rotta, Pedro Nielsen. "Análise de contágio a partir do modelo de correlação condicional constante com mudança de regime Markoviana." reponame:Repositório Institucional do FGV, 2012. http://hdl.handle.net/10438/10402.

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Submitted by Pedro Nielsen Rotta (pedro.rotta@gvmail.br) on 2013-01-17T01:23:43Z No. of bitstreams: 1 Dissertação_MPE_Pedro_Nielsen_Rotta.pdf: 1289831 bytes, checksum: e326f8c88be4c40b8581a8dd53dc83a3 (MD5)<br>Approved for entry into archive by Eliene Soares da Silva (eliene.silva@fgv.br) on 2013-01-17T15:46:21Z (GMT) No. of bitstreams: 1 Dissertação_MPE_Pedro_Nielsen_Rotta.pdf: 1289831 bytes, checksum: e326f8c88be4c40b8581a8dd53dc83a3 (MD5)<br>Made available in DSpace on 2013-01-17T16:11:12Z (GMT). No. of bitstreams: 1 Dissertação_MPE_Pedro_Nielsen_Rotta.pdf: 1289831 bytes, checksum: e326
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Athari, Mahtab. "Predictability of International Stock Returns with Sum of the Parts and Equity Premiums under Regime Shifts." ScholarWorks@UNO, 2015. http://scholarworks.uno.edu/td/2053.

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This research consists of two essays. The first essay entitled” Stock Return Forecasting with Sum-of-the-Parts Methodology: Evidence from Around the World”, examines forecasting ability of stock returns by employing the sum-of-the-parts (SOP) modeling technique introduced by Ferreira and Santa-Clara (2011).This approach decomposes return into three components of growth in price-earnings ratio, earnings growth, and dividend-price ratio. Each component is forecasted separately and fitted values are used in forecast model to predict stock return. We conduct a series of one-step ahead recursive fo
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26

Rodrigues, Miguel João de Figueiredo. "Business Cycle Synchronization Between the Euro Area and The Central and Eastearn European Countries Member States of The Eu: A Markov switching Regime Model Approach." Dissertação, Faculdade de Economia da Universidade do Porto, 2008. http://hdl.handle.net/10216/49826.

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27

Rodrigues, Miguel João de Figueiredo. "Business Cycle Synchronization Between the Euro Area and The Central and Eastearn European Countries Member States of The Eu: A Markov switching Regime Model Approach." Master's thesis, Faculdade de Economia da Universidade do Porto, 2008. http://hdl.handle.net/10216/49826.

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28

Berberovic, Adnan, and Alexander Eriksson. "A Multi-Factor Stock Market Model with Regime-Switches, Student's T Margins, and Copula Dependencies." Thesis, Linköpings universitet, Produktionsekonomi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-143715.

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Investors constantly seek information that provides an edge over the market. One of the conventional methods is to find factors which can predict asset returns. In this study we improve the Fama and French Five-Factor model with Regime-Switches, student's t distributions and copula dependencies. We also add price momentum as a sixth factor and add a one-day lag to the factors. The Regime-Switches are obtained from a Hidden Markov Model with conditional Student's t distributions. For the return process we use factor data as input, Student's t distributed residuals, and Student's t copula depend
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29

Varanda, Patrícia Alexandra Pereira Henriques. "Modelos com Alteração de Regime: Uma Aplicação Empírica à Taxa de Juro." Master's thesis, Instituto Superior de Economia e Gestão, 2011. http://hdl.handle.net/10400.5/3174.

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Mestrado em Econometria Aplicada e Previsão<br>Este trabalho analisa empiricamente o desempenho de vários modelos lineares na média condicional (ou seja, de um regime) por comparação com modelos que assumem alterações de regime, do tipo Markov de ordem um. Em termos de variância condicional acomodam-se várias hipóteses, como a dependência do nível da taxa de juro, de efeitos GARCH ou dos dois factores em simultâneo. A variável em estudo é a taxa de juro nominal a 10 anos da Alemanha. A evidência encontrada foi no sentido de que quer a presença de efeitos GARCH, quer a possibilidade de alteraçã
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30

Brannolte, Cord. "Nichtlineare Regimewechselmodelle : theoretische und empirische Evidenz am deutschen Kapitalmarkt /." Berlin : Pro Business, 2002. http://www.gbv.de/dms/zbw/357247493.pdf.

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31

Marodin, Fabrizio Almeida. "Mudança de regime markoviana em modelos DSGE : uma estimação do pass-through de câmbio para inflação brasileira durante o período 2000 a 2015." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/147432.

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Esta pesquisa investiga o comportamento não-linear do pass-through de taxa de câmbio na economia brasileira, durante o período de câmbio flutuante (2000-2015), a partir de um modelo de equilíbrio geral dinâmico estocástico com mudança de regime Markoviana (MS-DSGE). Para isso, utilizamos a metodologia proposta por Baele et al. (2015) e um modelo Novo-Keynesiano básico, sobre o qual incluímos novos elementos na curva de oferta agregada e uma nova equação para a dinâmica cambial. Encontramos evidências de existência de dois regimes distintos para o repasse cambial e para a variância dos choques
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32

Kluaymai-Ngarm, Jumpon. "An empirical investigation of bubble and contagion effects in the Thai stock market." Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/23127.

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This thesis examines stock price bubbles in the Stock Exchange of Thailand (SET) from its establishment in April 1975 until December 2012 using regime-switching bubble models, on the main aggregated market index, called the SET Index, and several disaggregated stock indices by industrial sector. The results suggest some evidence of bubble-like behaviour in these indices, most especially when a structural break is included at July 1997, the date when Thailand switched to adopting a managed floating exchange rate system. Given the limitations of published stock price indices in Thailand a new, c
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Bredow, Sabrina Monique Schenato. "O ciclo de alta recente dos preços das commodities e o efeito na entrada de capitais externos no brasil." Universidade do Vale do Rio dos Sinos, 2016. http://www.repositorio.jesuita.org.br/handle/UNISINOS/5196.

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Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-04-25T19:30:00Z No. of bitstreams: 1 Sabrina Monique Schenato Bredow_.pdf: 1816066 bytes, checksum: dfc2fea0a5369d22e5ec14fc8ea0cd5a (MD5)<br>Made available in DSpace on 2016-04-25T19:30:00Z (GMT). No. of bitstreams: 1 Sabrina Monique Schenato Bredow_.pdf: 1816066 bytes, checksum: dfc2fea0a5369d22e5ec14fc8ea0cd5a (MD5) Previous issue date: 2016-02-29<br>CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>Este trabalho analisa a influência do recente ciclo de alta dos preços das commodities sobre
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34

Elhouar, Mikael. "Essays on interest rate theory." Doctoral thesis, Handelshögskolan i Stockholm, Finansiell Ekonomi (FI), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-451.

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35

Sajjad, Rasoul. "Value-at-risk in a Markov regime-switching GARCH framework." Thesis, University of Essex, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438117.

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36

Cergibozan, Raif. "La prévision des périodes de stress fiscal : le rôle des indicateurs fiscaux, financiers et de gouvernance." Thesis, Paris 10, 2018. http://www.theses.fr/2018PA100143/document.

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L’Europe a subi la crise la plus sévère de sa récente histoire à la suite de la crise financière globale de 2008. C’est pourquoi cette thèse a l’objectif d’identifier de façon empirique les déterminants de cette crise dans le cadre de 15 principaux membres de l’UE. Dans ce sens, nous développons d’abord un index de pression fiscale continu, contrairement aux travaux empiriques précédents, afin d’identifier des périodes de crise dans les pays UE-15 de 2003 à 2015. Ensuite, nous utilisons trois différentes techniques d’estimation, à savoir Cartes auto-organisatrices, Logit et Markov. Nos résulta
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37

Check, Adam. "REGIME SWITCHING AND THE MONETARY ECONOMY." Thesis, University of Oregon, 2016. http://hdl.handle.net/1794/20531.

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For the empirical macroeconomist, accounting for nonlinearities in data series by using regime switching techniques has a long history. Over the past 25 years, there have been tremendous advances in both the estimation of regime switching and the incorporation of regime switching into macroeconomic models. In this dissertation, I apply techniques from this literature to study two topics that are of particular relevance to the conduct of monetary policy: asset bubbles and the Federal Reserve’s policy reaction function. My first chapter utilizes a recently developed Markov-Switching model in ord
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38

Shami, Roland G. (Roland George) 1960. "Bayesian analysis of a structural model with regime switching." Monash University, Dept. of Econometrics and Business Statistics, 2001. http://arrow.monash.edu.au/hdl/1959.1/9277.

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39

Haykal, Vanessa. "Modélisation des séries temporelles par apprentissage profond." Thesis, Tours, 2019. http://www.theses.fr/2019TOUR4019.

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La prévision des séries temporelles est un problème qui est traité depuis de nombreuses années. Dans cette thèse, on s’est intéressé aux méthodes issues de l’apprentissage profond. Il est bien connu que si les relations entre les données sont temporelles, il est difficile de les analyser et de les prévoir avec précision en raison des tendances non linéaires et du bruit présent, spécifiquement pour les séries financières et électriques. A partir de ce contexte, nous proposons une nouvelle architecture de réduction de bruit qui modélise des séries d’erreurs récursives pour améliorer les prévisions.
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40

Meyer, Ferdinand. "Model closure and price formation under switching grain market regimes in South Africa." Thesis, Pretoria : [s.n.], 2006. http://upetd.up.ac.za/thesis/available/etd-12082006-105715.

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Thesis (D.Phil.(Agricultural Economics, Extension, and Rural Development))--University of Pretoria, 2006.<br>Includes summary. Includes bibliographical references. Available on the Internet via the World Wide Web.
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Emery, Martin Banking &amp Finance Australian School of Business UNSW. "Studies into global asset allocation strategies using the markov-switching model." Publisher:University of New South Wales. Banking & Finance, 2008. http://handle.unsw.edu.au/1959.4/43098.

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This thesis presents the potential opportunities of global asset allocation and the possible enhancement of these opportunities from using a Markov Switching Model. The thesis extends upon previous conditional asset pricing studies in global asset allocation, such as those done by Ilamnen (1995), Harvey, Solnik and Zhou (1992) and Bilson (1993), where expected future returns are forecast based on conditional variables. The finding of these studies, and many others, are combined with the works on Markov Switching models and market segmentation theories to create a uniform structure for analys
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42

Ye, Lingyun. "MARKOV REGIME-SWITCHING MODELS." 2012. http://hdl.handle.net/10222/15126.

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A regime-switching model is a time-series model in which parameters change values according to the regime at present time. While regime-switching models have been very popular in applied work, there is a lack of literature for simulation studies. New methods based on regime-switching models are often proposed with neither a proof of convergence nor simulations to demonstrate their basic properties. In this thesis, a detailed simulation study of regime-switching models is conducted. A strategy to generate initial search values in the parameter estimation of regime-switching models is proposed.
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43

Chen, Yi Huei, and 陳怡慧. "Target Redemption Forward Price in Markov Regime Switching Model." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/73630581398051236735.

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碩士<br>國立清華大學<br>計量財務金融學系<br>104<br>Our research focus on Target Redemption Forward in Exotic. We use Markov regime switching model to simulate the exchange price, and compare whether static price is reasonable or not. We assume that there are two regimes(regime0, regime1), and fix one regime and variate the other regime in different probability to find the present price. We also find the price changes in different maturity.
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44

Chen, Lu Yen, and 陳律延. "Markov Regime-Switching Asymmetric GARCH model and Evaluation of TXO." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/00878642324285446502.

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碩士<br>長庚大學<br>企業管理研究所<br>97<br>In this paper we compare the classic Generalized Autoregressive Conditional Heteroscedasticity models with the ones linked Markov Regime switching model together in terms of their goodness of fit of TAIEX and forecastability of price of TXO by B-S model. Not only normal but also fat-tailed leptokurtic conditional distributions for the innovations are assumed, and the degrees of freedom can switch between the different regimes to draw time-varying kurtosis. The goodness of fit of the competing models are evaluated with the value of maximum likelihood function, AIC
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45

An-Chieh, Lee, and 李安傑. "Asset Allocation of Using Economic Indicators and Markov-Regime Switching Model." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/05600966398288940353.

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碩士<br>國立臺北商業技術學院<br>財務金融研究所<br>101<br>This research builds two models—vector autoregression and Markov-regime switching—to discuss the effect of economic indicators on Taiwan’s stock market and asset allocation of bull and bear markets. The first model, vector autoregression(VAR), is applied to research how economic indicators affect Taiwan’s stock market. With forecast error variance decomposition of VAR model, the next month’s trend of stock market will be forecasted by decomposed weights of economic indicators. Moreover, by backtesting the signal of forecast error variance decomposition,
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46

Lin, Yi-xian, and 林宜嫻. "Comparisons between the Markov Regime-Switching Model and the Black-Scholes Model: Evidence from TGO." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/90693101123514524698.

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碩士<br>國立高雄第一科技大學<br>金融研究所<br>100<br>Black-Scholes model is famous for pricing , but there are many unrealistic assumptions in this model, such as: the volatility is a constant ,the stock price is a lognormal distribution, and its return is a normal distribution. But in real world, the volatility is not a constant and the return is not a normally distribution, it always has many phenomenon, such as skewed, fat-tail and leptokurtic. Hamilton(1989) proposed the Markov Regime - Switching Model can solve these problems as skewed, fat-tail and leptokurtic effectively. And Hardy (2001) proposed that
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47

Banerjee, Tamal. "Analyzing Credit Risk Models In A Regime Switching Market." Thesis, 2012. http://etd.iisc.ernet.in/handle/2005/2517.

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Recently, the financial world witnessed a series of major defaults by several institutions and investment banks. Therefore, it is not at all surprising that credit risk analysis have turned out to be one of the most important aspect among the finance community. As credit derivatives are long term instruments, it is affected by the changes in the market conditions. Thus, it is a appropriate to take into consideration the effects of the market economy. This thesis addresses some of the important issues in credit risk analysis in a regime switching market. The main contribution in this thesis are
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48

Chiu, Tien-Yu, and 邱天禹. "Regime-switched volatility of Brent crude oil futures using Markov-switching ARCH model." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/05492789626590926235.

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碩士<br>國立政治大學<br>國際貿易研究所<br>94<br>This paper investigates the volatility of the Brent crude oil futures markets using Markov-switching ARCH (SWARCH) model. The SWARCH model allows the conditional disturbances to change as time passes and even to switch in different regimes. The empirical evidence shows that the SWARCH (3,3) model performs the best goodness of fit and the best forecast performance between different fitting models. The estimation of smoothing probabilities of data under different regimes facilitates to capture the characteristics of data, and the high-volatility regime is associa
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49

Chou, Yi-chun, and 周怡君. "Taiwan's Financial Holding Companies Stock Price Behaviour Based on Markov Regime-Switching Model." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/37859451492046952275.

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碩士<br>世新大學<br>財務金融學研究所(含碩專班)<br>94<br>In the trend of financial grouping, the Financial Holding Company Act has been allowing different financial institutions to promote their market competitiveness through cross-ownership of holding companies. This study mainly discussed the behavior of the stock price around the financial holding companies established by the Markov switching model. This thesis focused on the TSE & OTC financial holding companies, including HuaNan, Fubon, Cathay, China development, Esun, Fuhwa, Mega, Taishin, ShinKong, Waterland, Sinopac, Chinatrust, First, and Jihsun.Return.
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50

Jian, Yu Shi, and 簡育昰. "The Information Content of CBOE SKEW Index - Trading Strategy Under Markov Regime Switching Model." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/pn7z3a.

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碩士<br>國立政治大學<br>金融研究所<br>104<br>This paper divided into two parts to investigate on the information content of CBOE SKEW Index. For the first part, we do time series analysis to observe the relationship between SKEW Index and other variables. First, we found that SKEW index is totally different from VIX index. VIX index is a proxy for the standard deviation of the returns. The standard deviation describes the average spread of the distribution of returns around its mean. This is not a sufficient measure of risk because the distribution of S&P 500 log returns is not normal. SKEW Index captures
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