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Dissertations / Theses on the topic 'Multivariate conditional autoregressive model'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Silvennoinen, Annastiina. "Essays on autoregressive conditional heteroskedasticity." Doctoral thesis, Stockholm : Economic Research Institute, Stockholm School of Economics (EFI), 2006. http://www2.hhs.se/EFI/summary/711.htm.

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2

RAPOSO, GUSTAVO SANTOS. "HIGH FREQUENCY DATA AND PRICE-MAKING PROCESS ANALYSIS: THE EXPONENTIAL MULTIVARIATE AUTOREGRESSIVE CONDITIONAL MODEL - EMACM." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8620@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>A modelagem de dados que qualificam as transações de ativos financeiros, tais como, preço, spread de compra e venda, volume e duração, vem despertando o interesse de pesquisadores na área de finanças, levando a um aumento crescente do número de publicações referentes ao tema. As primeiras propostas se limitaram aos modelos de duração. Mais tarde, o impacto da duração sobre a volatilidade instantânea foi analisado. Recentemente, Manganelli (2002) incluiu dados referentes aos volumes transacionados dentro de um modelo vetori

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3

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

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4

Liu, Yingying. "Bayesian hierarchical normal intrinsic conditional autoregressive model for stream networks." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6606.

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Water quality and river/stream ecosystems are important for all living creatures. To protect human health, aquatic life and the surrounding ecosystem, a considerable amount of time and money has been spent on sampling and monitoring streams and rivers. Water quality monitoring and analysis can help researchers predict and learn from natural processes in the environment and determine human impacts on an ecosystem. Measurements such as temperature, pH, nitrogen concentration, algae and fish count collected along the network are all important factors in water quality analysis. The main purposes o

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5

Somal, Harsimran S. "Heterogeneous computing for the Bayesian hierarchical normal intrinsic conditional autoregressive model with incomplete data." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2145.

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A popular model for spatial association is the conditional autoregressive (CAR) model, and generalizations exist in the literature that utilize intrinsic CAR (ICAR) models within spatial hierarchical models. One generalization is the class of Bayesian hierarchical normal ICAR models, abbreviated HNICAR. The Bayesian HNICAR model can be used to smooth areal or lattice data, estimate the directional strength of spatio-temporal associations, and make posterior predictions at each point in space or time. Furthermore, the Bayes

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Cho, Jang Hyung. "An Autoregressive Conditional Filtering Process to remove Intraday Seasonal Volatility and its Application to Testing the Noisy Rational Expectations Model." FIU Digital Commons, 2008. http://digitalcommons.fiu.edu/etd/60.

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We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statisticall

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7

Lu, Cheng. "A new approach to calculate and forecast dynamic conditional correlation : the use of a multivariate heteroskedastic mixture model." Thesis, University of Southampton, 2010. https://eprints.soton.ac.uk/172585/.

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Much research in finance has been directed towards forecasting time varying volatility of unidimensional macroeconomic variables such as stock index, exchange rate and interest rate. However, comparatively little is devoted to modelling time varying correlation. In this research, we extend the current literature on correlation modelling by reviewing existing time-series tools, performing empirical analysis and developing two new conditional heteroscedastic models based on mixture techniques. Specifically, Engle’s standard DCC is augmented with an asymmetric factor and then modified so that dis

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8

Nakatani, Tomoaki. "Four Essays on Building Conditional Correlation GARCH Models." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-952.

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This thesis consists of four research papers. The main focus is on building the multivariate Conditional Correlation (CC-) GARCH models. In particular, emphasis lies on considering an extension of CC-GARCH models that allow for interactions or causality in conditional variances. In the first three chapters, misspecification testing and parameter restrictions in these models are discussed. In the final chapter, a computer package for building major variants of the CC-GARCH models is presented. The first chapter contains a brief introduction to the CC-GARCH models as well as a summary of each re

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Tong, Zhigang. "Statistical Inference for Heavy Tailed Time Series and Vectors." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/35649.

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In this thesis we deal with statistical inference related to extreme value phenomena. Specifically, if X is a random vector with values in d-dimensional space, our goal is to estimate moments of ψ(X) for a suitably chosen function ψ when the magnitude of X is big. We employ the powerful tool of regular variation for random variables, random vectors and time series to formally define the limiting quantities of interests and construct the estimators. We focus on three statistical estimation problems: (i) multivariate tail estimation for regularly varying random vectors, (ii) extremogram e

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Grego, Simone. "Modelos para relacionar variáveis de solos e área basal de espécies florestais em uma área de vegetação natural." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-03122014-142123/.

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O padrão espacial de ocorrência de atributos de espécies florestais, tal como a área basal das árvores, pode fornecer informações para o entendimento da estrutura da comunidade vegetal. Uma vez que fatores ambientais podem influenciar tanto o padrão espacial de ocorrência quanto os atributos das espécies em florestas nativas. Desse modo, investigar a relação entre as características ambientais e o padrão espacial de espécies florestais pode ajudar a entender a dinâmica das florestas. Especificamente, neste trabalho, o objetivo é avaliar métodos estatísticos que permitam identificar quais atrib

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Král, Ondřej. "Phillipsova křivka z pohledu analýzy časových řad v České republice a Německu." Master's thesis, Vysoká škola ekonomická v Praze, 2017. http://www.nusl.cz/ntk/nusl-360701.

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Government fiscal and monetary policy has long been based on the theory that was neither proven nor refuted since its origination. The original form of the Phillips curve has undergone significant modifications but its relevance remains questionable. This thesis examines the correlation between inflation and unemployment observed in the Czech Republic and Germany over the last twenty years. The validity of the theory is tested by advanced methods of time series analysis in the R environment. All the variables are gradually tested which results in the assessment of the correlation between the t

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Cespedes, Marcela I. "Detection of longitudinal brain atrophy patterns consistent with progression towards Alzheimer's disease." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/118289/1/Marcela_Cespedes_Thesis.pdf.

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This thesis develops and applies statistical methodologies to model brain atrophy in humans among multiple brain regions and how this may change over time. Throughout this work, Bayesian multilevel models are progressively developed for single and multiple regions at a given time point as well as modelling how connectivity between multiple regions evolves over time in conjunction with region level estimates. The application of these models provide insight into the detection of longitudinal brain atrophy patterns consistent with healthy ageing or progression towards Alzheimer's disease, and sho

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13

Arotiba, Gbenga Joseph. "Pricing American Style Employee Stock Options having GARCH Effects." Thesis, University of the Western Cape, 2010. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_3057_1298615964.

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<p>We investigate some simulation-based approaches for the valuing of the employee stock options. The mathematical models that deal with valuation of such options include the work of Jennergren and Naeslund [L.P Jennergren and B. Naeslund, A comment on valuation of executive stock options and the FASB proposal, Accounting Review 68 (1993) 179-183]. They used the Black and Scholes [F. Black and M. Scholes, The pricing of options and corporate liabilities, Journal of Political Economy 81(1973) 637-659] and extended partial differential equation for an option that includes the early exercise. Som

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Silva, Marília Gabriela Elias da. "Análise das cotações e transações intradiárias da Petrobrás utilizando dados irregularmente espaçados." reponame:Repositório Institucional do FGV, 2014. http://hdl.handle.net/10438/12034.

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Submitted by Marília Gabriela Elias da Silva (marilia.gabriela.es@gmail.com) on 2014-09-18T19:07:04Z No. of bitstreams: 1 Marilia_Gabriela_tese.pdf: 512980 bytes, checksum: 8ab7fc0b5b89fa1bd8f99a705ae51920 (MD5)<br>Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2014-09-18T19:43:45Z (GMT) No. of bitstreams: 1 Marilia_Gabriela_tese.pdf: 512980 bytes, checksum: 8ab7fc0b5b89fa1bd8f99a705ae51920 (MD5)<br>Made available in DSpace on 2014-09-18T19:51:23Z (GMT). No. of bitstreams: 1 Marilia_Gabriela_tese.pdf: 512980 bytes, checksum: 8ab7fc0b5b89fa1bd8f99a

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15

McGarry, Gregory John. "Model-based mammographic image analysis." Thesis, Queensland University of Technology, 2002.

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16

Van, Heerden Petrus Marthinus Stephanus. "The relationship between the forward– and the realized spot exchange rate in South Africa / Petrus Marthinus Stephanus van Heerden." Thesis, North-West University, 2010. http://hdl.handle.net/10394/4511.

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The inability to effectively hedge against unfavourable exchange rate movements, using the current forward exchange rate as the only guideline, is a key inhibiting factor of international trade. Market participants use the current forward exchange rate quoted in the market to make decisions regarding future exchange rate changes. However, the current forward exchange rate is not solely determined by the interaction of demand and supply, but is also a mechanistic estimation, which is based on the current spot exchange rate and the carry cost of the transaction. Results of various studies, inclu

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17

Charlot, Philippe. "Structures Markoviennes cachées et modèles à corrélations conditionnelles dynamiques : extensions et applications aux corrélations d'actifs financiers." Phd thesis, Université de la Méditerranée - Aix-Marseille II, 2010. http://tel.archives-ouvertes.fr/tel-00614498.

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L'objectif de cette thèse est d'étudier le problème de la modélisation des changements de régime dans les modèles à corrélations conditionnelles dynamiques en nous intéressant plus particulièrement à l'approche Markov-switching. A la différence de l'approche standard basée sur le modèle à chaîne de Markov caché (HMM) de base, nous utilisons des extensions du modèle HMM provenant des modèles graphiques probabilistes. Cette discipline a en effet proposé de nombreuses dérivations du modèle de base permettant de modéliser des structures complexes. Cette thèse se situe donc à l'interface de deux di

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18

"High frequency data and price-making process analysis: the exponential multivariate autoregressive conditional model emacm." Tese, MAXWELL, 2006. http://www.maxwell.lambda.ele.puc-rio.br/cgi-bin/db2www/PRG_0991.D2W/SHOW?Cont=8620:pt&Mat=&Sys=&Nr=&Fun=&CdLinPrg=pt.

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19

Dzikiti, Weston. "Banking sector, stock market development and economic growth in Zimbabwe : a multivariate causality framework." Diss., 2017. http://hdl.handle.net/10500/22818.

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The thesis examined the comprehensive causal relationship between the banking sector, stock market development and economic growth in a multi-variate framework using Zimbabwean time series data from 1988 to 2015. Three banking sector development proxies (total financial sector credit, banking credit to private sector and broad money M3) and three stock market development proxies (stock market capitalization, value traded and turnover ratio) were employed to estimate both long and short run relationships between banking sector, stock market and economic growth in Zimbabwe. The study employs the

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20

Chan, Ya-chu, and 詹雅竹. "Conditional autoregressive Value-at-Risk model estimates in financial markets." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/47728487765504579564.

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碩士<br>逢甲大學<br>統計與精算所<br>95<br>Value-at-Risk (VaR) forecasting is required by all financial institutions (Basel II). For better VaR estimation, Engle and Manganelli (2004) proposed quantile regression to model VaR directly instead of modeling the underlying volatility generating process. They introduced the conditional autoregressive value at risk (CAViaR) model. Recent work shows that the nonparametric solution is a special case of the Skewed-Laplace distribution. This will allow development of likelihood/Bayesian to more rigorously estimate VaR. However, VaR may exhibit substatistical nonline

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Wen, Wan-Ching, and 溫婉菁. "Assessing Value at Risk by the Expectile Conditional Autoregressive model." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/74467606814691626375.

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碩士<br>國立臺北大學<br>統計學系<br>100<br>In financial markets, one of the major factors which will cause risk is due to the fluctuation of assets price. When a Investor faces risk, he/she should evaluate how much losses will happen, and thus to propose the corresponding strategies. Therefore, how to properly measure the downside risk is a very important issue. Value at risk (VaR) has become an important tool for predicting and managing risk. VaR is a measure of market risk which can be used by an investor to evaluate how much a portfolio could lose. Recently, the use of quantitative risk measures has be

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22

Garcia, Carlos Diogo Monteiro. "Predictive accuracy of alternative autoregressive conditional heteroskedasticity models." Master's thesis, 2010. http://hdl.handle.net/10071/3493.

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The main objective of this thesis is to compare some of the most popular volatility models, in terms of their predictive accuracy. Specifically, we will use three autoregressive conditional heteroskedasticity (ARCH) models, GARCH, EGARCH and GJR. In order to compare these models, we will use some of the most recent predictive accuracy tests: Diebold-Mariano (1995), modified Diebold-Mariano (1997), modified Morgan-Granger-Newbold (1997), Harvey-Leybourne-Newbold (1998), Harvey-Newbold (2000) and Hansen (2005). We will consider the CAC40, FTSE100, NIKKEI225 and S&p500 indexes in our analysis, f

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23

Hong, Than Thi, and 申氏鴻. "Bayesian Inference and Quantile Forecasting on the Multivariate Hysteretic Autoregressive Model." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/g7uxf4.

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博士<br>逢甲大學<br>統計學系應用統計博士班<br>107<br>In order to understand and predict sequential dependence of target time series, this study proposes a new class of multivariate hysteretic models to capture asymmetry and more complex dynamic behaviors in multivariate time series. The first part of my thesis proposes a hysteretic vector autoregressive (HVAR) model that provides a new way to understand a nonlinear multivariate model in which the regime switch can be delayed when the hysteresis variable lies in a hysteresis zone. We employ a modified multivariate Student-t distribution in the HVAR model to all

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Gong, Yi Liao. "Analysis of the growth curve model with autoregressive dependence and conditional heteroscedasticity." 2006. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0005-2306200614190000.

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Liao, Gong Yi, and 廖宮毅. "Analysis of the growth curve model with autoregressive dependence and conditional heteroscedasticity." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/28826822244605770094.

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碩士<br>國立中興大學<br>應用數學系所<br>94<br>The growth curve model that the covariance matrix constructed with autoregressive (AR) dependence of degree 1 and autoregressive conditional heteroscedasiticity (ARCH) of degree 1 is studied in the thesis. The specification of the multivariate normal distribution with these two properties is dedicated. I consider both maximum likelihood inference perspective and Bayesian inference perspective for estimation and prediction. An algorithm is introduced for determining maximum likelihood estimates of the unknown parameters, on the other hand, Markov Chain Monte Ca

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Ku, Hsin-Hui, and 古欣卉. "Forecasting Financial Volatilities with Extreme Values: The Conditional Autoregressive Range (CARR) Model." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/35197521974828384566.

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碩士<br>淡江大學<br>財務金融學系碩士班<br>94<br>Volatility plays an important role in finance. If we can capture the characteristics of the motions of assets precisely, we could make good portfolios and control risks efficiently. GARCH models have been used in the forecast of volatilities generally, and performed well in many empirical studies. However, Chou(2005) proposed the CARR model and compared in the CARR model and traditional GARCH model based on the data of S&P 500 index. CARR is better in the volatility forecasting. This paper tests and verifies the forecasting power of the CARR model based on the

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Lin, I.-Chieh, and 林依潔. "Modeling and Forecasting Financial Volatilities:The Application of Conditional Autoregressive Range(WCARRX)Model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/66462076763190810191.

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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>98<br>The main prupose of this study is to apply the Conditional Autoregressive Range model(henceforth CARR)in modeling and forecasting the volatility of the Taiwan Stock Exchange Capitalization Weighted Stock Index(TAIEX). In contrast to the traditional return-based volatility model developed by Chou(2005). The sample used in this study covers 2233 daily observation, collecting from January 1,2001 to December 31, 2009. We define the first 1982 as in-sample data, and the remaining 251 observations are used as out-of-sample forest. In addition, we use the sum of s

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Li-WenChang and 張力文. "Spatial Cox Proportional Hazards Model with Intrinsic Conditional Autoregressive (ICAR) Dependence Modeling." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/qc7mve.

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碩士<br>國立成功大學<br>統計學系<br>106<br>Type 2 diabetes mellitus (T2DM) is a common chronic diseases predisposing to cardio-vascular disease (CVD), which is the principal cause of death among diabetic patients. Due to the physical environment, there is likely to be a spatial component to the time of onset of CVD. This study aims to model the factors that affect the survival time while taking the spatial correlation into account. We develop a spatial Cox model with intrinsic conditional autoregressive (ICAR) dependence for spatial survival data. The proposed model is based on Cox proportional hazards mo

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El, Din Tarek Mohy. "The ARCH Effect : a model of gradual anticipation for autoregressive conditional heteroskedasticity in asset returns /." 1997. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=007618187&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Li, Chian-Jang, and 李乾彰. "The empirical studies : the day-of-the-week effect on foreign exchange market - application of autoregressive conditional heterocedasticity model." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/16022894713199509475.

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碩士<br>國立臺灣大學<br>國際企業學系<br>86<br>THESIS ABSTRACT In this paper, we examine the daily behavior of exchange rate with ARCH model which was developed by Engle in 1982 and GARCH model which was developed by Bollerslev in 1986. We use daily exchange returns of US dollars , Japanese yen , Hong Kong dollars , Deutsche marks , UK pound sterling , South Korean won , Swiss francs spanning from 1988 to 1996 to discuss : (1) the stationarity of exchange rate data , (2) the statistical pr

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Hau, Fung, and 方豪. "The study of effectiveness of price limit changing on stock price--application of generalized autoregressive conditional heteroscedas-ticity model." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/07687426316435538787.

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Szczygielski, Jan Jakub. "An ARCH/GARCH arbitrage pricing theory approach to modelling the return generating process of South African stock returns." Thesis, 2013. http://hdl.handle.net/10539/13035.

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This study investigates the return generating process underlying the South African stock market. The investigation of the return generating process is framed within the Arbitrage Pricing Theory (APT) framework with the APT reinterpreted so as to provide a conceptual framework within which the return generating process can be investigated. In modelling the return generating process, the properties of South African stock returns are taken into consideration and an appropriate econometric framework in the form of Autoregressive Conditional Heteroscedastic (ARCH) and Generalized Autoregress

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Lin, Jiahui, and 林嘉慧. "A New Parametric Approach to Modeling Generalized Autoregressive Conditional Density Model at Higher Order Moments：Evidence on Taiwan''s Stock Return." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/78805612192629352260.

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碩士<br>淡江大學<br>國際貿易學系<br>88<br>(G)ARCH modeling with a leptokurtic distribution has been found useful to account for the condition heterscedasticity and leptokurtosis , but it can''t accommodate other commonly observed stylized effects in high frequency data, like peakedness and skewness. Wang etal (2000) proposed a very general and flexible GARCH-EGB2 model which can accommodate more data characteristics, such as asymmetry, high peakedness, volatility clustering and leptokurtosis. In this paper, we further extended Wang etal''s work to allow the shape parameters following the struct

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Juchelka, Tomáš. "Prediction of Stock Return Volatility Using Internet Data." Master's thesis, 2017. http://www.nusl.cz/ntk/nusl-367646.

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The thesis investigates relationship between daily stock return volatility of Dow Jones Industrial Average stocks and data obtained on Twitter, the social media network. The Twitter data set contains a number of tweets, categorized according to their polarity, i.e. positive, negative and neutral sentiment of tweets. We construct two classes of models, GARCH and ARFIMA, where for either of them we research basic model setting and setting with additional Twitter variables. Our goal is to compare, which of them predicts the one day ahead volatility most precisely. Besides, we provide commentary r

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Voráčková, Andrea. "Modelování durací mezi finančními transakcemi." Master's thesis, 2018. http://www.nusl.cz/ntk/nusl-372948.

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❆❜str❛❝t ❚❤✐s ❞✐♣❧♦♠❛ t❤❡s✐s ❞❡❛❧s ✇✐t❤ ♣r♦♣❡rt✐❡s ♦❢ ❆❈❉ ♣r♦❝❡ss ❛♥❞ ♠❡t❤♦❞s ♦❢ ✐ts ❡st✐♠❛t✐♦♥✳ ❋✐rst✱ t❤❡ ❜❛s✐❝ ❞❡☞♥✐t✐♦♥s ❛♥❞ r❡❧❛t✐♦♥s ❜❡t✇❡❡♥ ❆❘▼❆ ❛♥❞ ●❆❘❈❍ ♣r♦❝❡ss❡s ❛r❡ st❛t❡❞✳ ■♥ t❤❡ s❡❝♦♥❞ ♣❛rt ♦❢ t❤❡ t❤❡s✐s✱ t❤❡ ❆❈❉ ♣r♦❝❡ss ✐s ❞❡☞♥❡❞ ❛♥❞ t❤❡ r❡❧❛t✐♦♥ ❜❡t✇❡❡♥ ❆❘▼❆ ❛♥❞ ❆❈❉ ✐s s❤♦✇♥✳ ❚❤❡♥ ✇❡ s❤♦✇ t❤❡ ♠❡t❤♦❞s ♦❢ ❞❛t❛ ❛❞❥✉st♠❡♥t✱ ❡st✐♠❛t✐♦♥✱ ♣r❡❞✐❝t✐♦♥ ❛♥❞ ✈❡r✐☞❝❛t✐♦♥ ♦❢ t❤❡ ❆❈❉ ♠♦❞❡❧✳ ❆❢t❡r t❤❛t✱ t❤❡ ♣❛rt✐❝✉❧❛r ❝❛s❡s ♦❢ ❆❈❉ ♣r♦❝❡ss✿ ❊❆❈❉✱ ❲❆❈❉✱ ●❆❈❉✱ ●❊❱❆❈❉ ✇✐t❤ ✐ts ♣r♦♣❡rt✐❡s ❛♥❞ t❤❡ ♠♦t✐✈❛t✐♦♥❛❧ ❡①❛♠♣❧❡s ❛r❡ ✐♥tr♦❞✉❝❡❞✳ ❚❤❡ ♥✉♠❡r✐❝❛❧ ♣❛rt ✐s ♣❡r❢♦r♠❡❞ ✐♥ ❘ s♦❢t✇❛r❡ ❛♥❞ ❝♦♥❝❡r♥s t❤❡ ♣r❡

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Hsu, Shih-Chieh, and 徐士傑. "A Study on the Relationships on Conditional Volatility, Economic Growth and its Relations to Stock Index Volatility for Taiwan, US and China: An Application of Multivariate VEC-GARCH-in-Mean Model." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/19303923139381922335.

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碩士<br>國立臺北大學<br>合作經濟學系<br>95<br>The purpose of this study is to detect the relationships on conditional volatility, economic growth and its relations to stock index volatility for Taiwan, US and China. This research has applied multivariate VEC –GARCH –in -Mean model to achieve the purpose by utilizing the quarterly data covering the period 1978:1－2005:4. The major conclusions of this empirical research are as follows: Firstly, the result of cointegration test has shown that there is a long-run equilibrium relationship among economic growth and stock index volatility in Taiwan, US and China

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Mody, Sandeep K. "Computation of Sparse Representations of High Dimensional Time Series Data and Experimental Applications." Thesis, 2017. http://etd.iisc.ac.in/handle/2005/4295.

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Obtaining a sparse representation of high dimensional data is often the first step towards its further analysis. Conventional Vector Autoregressive (VAR) modelling methods applied to such data results in noisy, non-sparse solutions with a too many spurious Coefficients. Computing auxiliary quantities such as the Power Spectrum, Coherence and Granger causality (GC) from such non-sparse models is slow and gives wrong results. Thresholding the distorted values of these quantities as per some criterion, statistical or otherwise, does not alleviate the problem. We propose two sparse Vector A

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Austin, Elizabeth. "Regression Analysis for Ordinal Outcomes in Matched Study Design: Applications to Alzheimer's Disease Studies." 2018. https://scholarworks.umass.edu/masters_theses_2/628.

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Alzheimer's Disease (AD) affects nearly 5.4 million Americans as of 2016 and is the most common form of dementia. The disease is characterized by the presence of neurofibrillary tangles and amyloid plaques [1]. The amount of plaques are measured by Braak stage, post-mortem. It is known that AD is positively associated with hypercholesterolemia [16]. As statins are the most widely used cholesterol-lowering drug, there may be associations between statin use and AD. We hypothesize that those who use statins, specifically lipophilic statins, are more likely to have a low Braak stage in post-mortem

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