Relevant bibliographies by topics / Vector autoregressive process

Academic literature on the topic 'Vector autoregressive process'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Vector autoregressive process"

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Tovstik, T. M. "Vector autoregression process. Stationarity and simulation." Journal of Physics: Conference Series 2099, no. 1 (November 1, 2021): 012068. http://dx.doi.org/10.1088/1742-6596/2099/1/012068.

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Abstract For vector discrete-parameter random autoregressive processes and for a mixed autoregression/moving-average model, we obtain conditions which should be satisfied by the correlation functions or the model coefficients in order that the process be weakly stationary. Fairly simple tests are used. Algorithms for modeling such vector stationary processes are given. Examples are presented clarifying testing criteria for stationarity of models defned in terms of the coefficients or the correlation functions of the process.
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Cheng, Tsung-Chi, Ping-Hung Hsieh, and Su-Fen Yang. "Process Control for the Vector Autoregressive Model." Quality and Reliability Engineering International 30, no. 1 (December 17, 2012): 57–81. http://dx.doi.org/10.1002/qre.1477.

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Grynkiv, Galyna, and Lars Stentoft. "Stationary Threshold Vector Autoregressive Models." Journal of Risk and Financial Management 11, no. 3 (August 5, 2018): 45. http://dx.doi.org/10.3390/jrfm11030045.

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This paper examines the steady state properties of the Threshold Vector Autoregressive model. Assuming that the trigger variable is exogenous and the regime process follows a Bernoulli distribution, necessary and sufficient conditions for the existence of stationary distribution are derived. A situation related to so-called “locally explosive models”, where the stationary distribution exists though the model is explosive in one regime, is analysed. Simulations show that locally explosive models can generate some of the key properties of financial and economic data. They also show that assessing the stationarity of threshold models based on simulations might well lead to wrong conclusions.
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Brockwell, Peter J., Richard A. Davis, and A. Alexandre Trindade. "Asymptotic properties of some subset vector autoregressive process estimators." Journal of Multivariate Analysis 90, no. 2 (August 2004): 327–47. http://dx.doi.org/10.1016/j.jmva.2003.10.001.

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Bodnar, T., and T. Zabolotskyy. "Estimation and inference of the vector autoregressive process under heteroscedasticity." Theory of Probability and Mathematical Statistics 83 (2011): 27–45. http://dx.doi.org/10.1090/s0094-9000-2012-00839-9.

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Gourieroux, Christian, and Joann Jasiak. "Noncausal vector autoregressive process: Representation, identification and semi-parametric estimation." Journal of Econometrics 200, no. 1 (September 2017): 118–34. http://dx.doi.org/10.1016/j.jeconom.2017.01.011.

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Dufour, Jean-Marie. "Unbiasedness of Predictions from Etimated Vector Autoregressions." Econometric Theory 1, no. 3 (December 1985): 387–402. http://dx.doi.org/10.1017/s0266466600011270.

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Forecasts from a univariate autoregressive model estimated by OLS are unbiased, irrespective of whether the model fitted has the correct order; this property only requires symmetry of the distribution of the innovations. In this paper, this result is generalized to vector autoregressions and a wide class of multivariate stochastic processes (which include Gaussian stationary multivariate stochastic processes) is described for which unbiasedness of predictions holds: specifically, if a vector autoregression of arbitrary finite order is fitted to a sample from any process in this class, the fitted model will produce unbiased forecasts, in the sense that the prediction errors have distributions symmetric about zero. Different numbers of lags may be used for each variable in each autoregression and variables may even be missing, without unbiasedness being affected. This property is exact in finite samples. Similarly, the residuals from the same autoregressions have distributions symmetric about zero.
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la Cour, Lisbeth. "A PARAMETRIC CHARACTERIZATION OF INTEGRATED VECTOR AUTOREGRESSIVE (VAR) PROCESSES." Econometric Theory 14, no. 2 (April 1998): 187–99. http://dx.doi.org/10.1017/s0266466698142020.

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This paper provides a polynomial factorization theorem that is then used to extend the characterization parts of the parametric representation theorems of Johansen (1992, Econometric Theory 8, 188–202) for vector autoregressive processes integrated of up to order 2. A characterization theorem is provided in the general case of an I(d) process. For the discussion of the complicated polynomial cointegration properties of such processes, the case of an I(3) process is considered as an example.
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Gallego, Jose L. "The exact likelihood function of a vector autoregressive moving average process." Statistics & Probability Letters 79, no. 6 (March 2009): 711–14. http://dx.doi.org/10.1016/j.spl.2008.10.030.

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Yang, Minxian. "SOME PROPERTIES OF VECTOR AUTOREGRESSIVE PROCESSES WITH MARKOV-SWITCHING COEFFICIENTS." Econometric Theory 16, no. 1 (February 2000): 23–43. http://dx.doi.org/10.1017/s026646660016102x.

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Some statistical properties of a vector autoregressive process with Markov-switching coefficients are considered. Sufficient conditions for this nonlinear process to be covariance stationary are given. The second moments of the process are derived under the conditions. The autocovariance matrix decays at exponential rate, permitting the application of the law of large numbers. Under the stationarity conditions, although sharing the “mean-reverting” property with conventional linear stationary processes, the process offers richer short-run dynamics such as conditional heteroskedasticity, asymmetric responses, and occasional nonstationary behavior.
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Dissertations / Theses on the topic "Vector autoregressive process"

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Pradat, Yannick. "Retraite et risque financier." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLED022/document.

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Le premier chapitre examine les caractéristiques statistiques à long terme des rendements financiers en France et aux USA. Les propriétés des différents actifs font apparaître qu’à long terme les actions procurent un risque sensiblement moins élevé. En outre, les propriétés de retour à la moyenne des actions justifient qu’elles soient utilisées dans une stratégie de cycle de vie comme « option par défaut » de plans d’épargne retraite. Le chapitre deux fournit une explication au débat sur l'hypothèse d’efficience des marchés. La cause du débat est souvent attribuée à la petite taille des échantillons et à la faible puissance des tests statistiques dédiés. Afin de contourner ce problème, nous utilisons l'approche développée par Campbell et Viceira (2005) qui utilisent une méthode VAR pour mettre en évidence l’existence de retour vers la moyenne dans le cours des actifs risqués.Le troisième chapitre évalue la vitesse de convergence des cours des actions. Un moyen classique pour caractériser la vitesse de retour vers la moyenne est la « demi-vie ». En comparant les indices boursiers de quatre pays développés (États-Unis, Royaume-Uni, France et Japon) sur la période 1950-2014, nous établissons une vitesse de convergence significative, avec une demi-vie entre 4,0 et 5,8 ans.Le dernier chapitre présente les résultats d'un modèle conçu pour étudier les interactions entre la démographie et les régimes de retraite. Afin d’étudier les risques inhérents à l’utilisation des revenus du capital pour financer les retraites, nous utilisons un « Trending OU process » au lieu d’un MBG classique pour modéliser les rendements. Pour un épargnant averse au risque le marché pourrait concurrencer les régimes par répartition
Chapter one examines the long run statistical characteristics of financial returns in France and the USA for selected assets. This study clearly shows that the returns’ distributions diverge from the Gaussian strategy as regards longholding periods. Thereafter we analyze the consequences of the non-Gaussian nature of stock returns on default-option retirement plans.Chapter two provides a reasonable explanation to the strong debate on the Efficient Market Hypothesis. The cause of the debate is often attributed to small sample sizes in combination with statistical tests for mean reversion that lackpower. In order to bypass this problem, we use the approach developed by Campbell and Viceira (2005) who have settled a vectorial autoregressive methodology (VAR) to measure the mean reversion of asset returns.The third chapter evaluates the speed of convergence of stock prices. A convenient way to characterize the speed of mean reversion is the half-life. Comparing the stock indexes of four developed countries (US, UK, France and Japan) during the period 1950-2014, we establish significant mean reversion, with a half-life lying between 4,0 and 5,8 years.The final chapter provides some results from a model built in order to study the linked impacts of demography and economy on the French pension scheme. In order to reveal the risks that are contained in pension fund investment, we use a Trending Ornstein-Uhlenbeck process instead of the typical GBM for modeling stock returns. We find that funded scheme returns, net of management fees, are slightly lower thanthe PAYG internal rate of return
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Nemšáková, Alena. "Fundamentálna analýza akciového titulu akciového titulu RWE AG." Master's thesis, Vysoká škola ekonomická v Praze, 2008. http://www.nusl.cz/ntk/nusl-3929.

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The goal of the diploma thesis: "Fundamental analysis of RWE AG title" is to determine an intrinsic value of the RWE AG share using detail analysis. The first -- theoretical -- part deals with financial environment where the title is being traded and quoted. This part characterised german indices, mainly index DAX 30, because its component is also RWE AG share. The electronic system Xetra is described here as well. Fundamental analysis itself - including global, sector and enterprise analysis - is the subject of the second section. At the end of this work, the intrinsic value is evaluated and subsequently the forecast is outlined.
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Kuckuck, Jan. "Essays on Government Growth, Fiscal Policy and Debt Sustainability." Doctoral thesis, 2015. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2015042913161.

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The financial crisis of 2007/8 has triggered a profound debate about public budget finance sustainability, ever-increasing government expenditures and the efficiency of fiscal policy measures. Given this context, the following dissertation provides four contributions that analyze the long-run growth of government spending throughout economic development, discuss potential effects of fiscal policy measures on output, and provide new insights into the assessment of debt sustainability for a variety of industrialized countries. Since the breakout of the European debt crisis in 2009/2010, there has been a revival of interest in the long-term growth of government expenditures. In this context, the relationship between the size of the public sector and economic growth - often referred to as Wagner's law - has been in the focus of numerous studies, especially with regard to public policy and fiscal sustainability. Using historical data from the mid-19th century, the first chapter analyzes the validity of Wagner's law for five industrialized European countries and links the discussion to different stages of economic development. In line with Wagner's hypothesis, our findings show that the relationship between public spending and economic growth has weakened at an advanced stage of development. Furthermore, all countries under review support the notion that Wagner's law may have lost its economic relevance in recent decades. As a consequence of the 2007/8 financial crisis, there has been an increasing theoretical and empirical debate about the impact of fiscal policy measures on output. Accordingly, the Structural Vector Autoregression (SVAR) approach to estimating the fiscal multipliers developed by Blanchard and Perotti (2002) has been applied widely in the literature in recent years. In the second chapter, we point out that the fiscal multipliers derived from this approach include the predicted future path of the policy instruments as well as their dynamic interaction. We analyze a data set from the US and document that these interactions are economically and statistically significant. In a counterfactual simulation, we report fiscal multipliers that abstract from these dynamic responses. Furthermore, we use our estimates to analyze the recent fiscal stimulus of the American Recovery and Reinvestment Act (ARRA). The third chapter contributes to the existing empirical literature on fiscal multipliers by applying a five-variable SVAR approach to a uniform data set for Belgium, France, Germany, and the United Kingdom. Besides studying the effects of expenditure and tax increases on output, we additionally analyze their dynamic effects on inflation and interest rates as well as the dynamic interaction of both policy instruments. By conducting counterfactual simulations, which abstract from the dynamic response of key macroeconomic variables to the initial fiscal shocks, we study the importance of these channels for the transmission of fiscal policy on output. Overall, the results demonstrate that the effects of fiscal shocks are limited and rather different across countries. Further, it is shown that the inflation and interest rate channel are insignificant for the transmission of fiscal policy. In the field of public finances, governmental budgetary policies are among the most controversial and disputed areas of political and scientific controversy. The sustainability of public debt is often analyzed by testing stationarity conditions of government's budget deficits. The fourth chapter shows that this test can be implemented more effectively by means of an asymmetric unit root test. We argue that this approach increases the power of the test and reduces the likelihood of drawing false inferences. We illustrate this in an application to 14 countries of the European Monetary Union as well as in a Monte Carlo simulation. Distinguishing between positive and negative changes in deficits, we find consistency with the intertemporal budget constraint for more countries, i.e. lower persistence of positive changes in some countries, compared to the earlier literature.
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Petras, Petr. "Propojenost vysokofrekvenčních dat." Master's thesis, 2016. http://www.nusl.cz/ntk/nusl-352785.

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This work combines discrete and continuous methods while modeling connect- edness of financial tick data. As discrete method we are using vector autore- gression. For continuous domain Hawkes process is used, which is special case of point process. We found out that financial assets are connected in non- symmetrical fashion. By using two methodologies we were able to model bet- ter how are the series connected. We confirmed existence of price leader in our three stock portfolio and modeled connectedness of jumps between stocks. As conclusion we state that both methods yields important results about price nature on the market and should be used together or at least with awareness of second approach. JEL Classification C32, G11, G14 Keywords Vector Autoregression, Hawkes process, High- frequency analysis, Connectedness Author's e-mail petr.petras@email.cz Supervisor's e-mail krehlik@utia.cas.cz
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Oliveira, Pedro Miguel Domingos Duarte de. "Aplicação da teoria da cointegração ao teste da hipótese de expectativas racionais na estrutura por prazo das taxas de juro." Master's thesis, 1997. http://hdl.handle.net/10400.5/12868.

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Mestrado em Matemática Aplicada à Economia e à Gestão
A formulação da hipótese de expectativas racionais no contexto da estrutura por prazo das taxas de jure possui diversas variantes que, num cenário de neutralidade face ao risco por parte dos investidores, sao mutuamente exclusivas. Demonstra-se, no entanto, que quando se admite a existência de aversão ao risco e possível compatibilizar as diversas abordagens, proporcionando uma expressao universal para exprimir a hlpótese em causa. Com base quer nessa expressão, quer na constatação de que as taxas de juro à vista nos EUA revelam uma trajectória comum durante o período compreendido entre Dezembro de 1946 e Fevereiro de 1991, aplicamos os testes de cointegração de Johansen por forma a testar a hipótese de expectativas racionais. Embora OS testes a priori lhe sejam favoráveis, o facto e que o sistema autoregressivo de suporte sofre de rna especificação(detectam-se fortes indícios de autocorrelação nos termos de perturbação de cada equação) colocando em causa a inferência estatística efectuada. Dado que o nosso objectivo central é averiguar a validade empirica da hipótese supra mencionada, procuramos contornar este problema introduzindo variáveis artificiais que captem possiveis alterações nos processes de geração dos dados e aplicando testes de raízes unitarias e de cointegração de acordo com a abordagem de Engle e Granger mas robustos a ocorrência de uma quebra de estrutura no comportamento estocastico das variáveis em causa. Os respectivos resultados apontam no sentido de não se rejeitar a hipótese de expectativas racionais, além de que permitem estimar de forma consistente os efeitos sobre os prémios de risco decorrentes da mudança de regime de política monetária em Outubro de 1979.
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Books on the topic "Vector autoregressive process"

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Cha, Baekin. The influence of the exchange rate on the U.S. wage process: A vector autoregression approach. Kowloon, Hong Kong: City Polytechnic of Hong Kong, Department of Economics and Finance, 1993.

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Book chapters on the topic "Vector autoregressive process"

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Gates, Kathleen M., Sy-Miin Chow, and Peter C. M. Molenaar. "Vector Autoregression (VAR)." In Intensive Longitudinal Analysis of Human Processes, 73–101. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9780429172649-4.

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Herbst, Edward P., and Frank Schorfheide. "Turning a DSGE Model into a Bayesian Model." In Bayesian Estimation of DSGE Models. Princeton University Press, 2015. http://dx.doi.org/10.23943/princeton/9780691161082.003.0002.

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This chapter considers the turning of DSGE models into Bayesian versions by specifying a probability distribution for the innovations of the exogenous shock processes. There exists a wide variety of numerical techniques to solve DSGE models, but the chapter elaborates on a technique that involves the log-linearization of the equilibrium conditions and the solution of the resulting linear rational expectations difference equations. The approximate solution takes the form of a vector autoregressive process for the model variables, which is driven by the innovations to the exogenous shock processes, and is used as a set of state-transition equations in the state–space representation of the DSGE model. Under the assumption that these innovations are normally distributed, the log-linearized DSGE model takes the form of a linear Gaussian state–space model.
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Hansen, Lars Peter, and Thomas J. Sargent. "Statistical Representations." In Recursive Models of Dynamic Linear Economies. Princeton University Press, 2013. http://dx.doi.org/10.23943/princeton/9780691042770.003.0008.

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This chapter describes links between competitive equilibria and autoregressive representations. It shows how to obtain an autoregressive representation for observable variables that are error-ridden linear functions of state variables. In describing how to deduce an autoregressive representation from a competitive equilibrium and parameters of measurement error processes, it completes a key step that facilitates econometric estimation of free parameters. An autoregressive representation is naturally affiliated with a recursive representation of a likelihood function for the observable variables. More precisely, a vector autoregressive representation implements a convenient factorization of the joint density of a complete history of observables (i.e., the likelihood function) into a product of densities of time t observables conditioned on histories of those observables up to time t−1. The chapter also treats two other topics intimately related to econometric implementation: aggregation over time and the theory of approximation of one model by another.
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Conference papers on the topic "Vector autoregressive process"

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Kvas, Andreas, and Torsten Mayer-Gürr. "Regularization of the Gravity Field Inversion Process with High-Dimensional Vector Autoregressive Models." In International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. Basel Switzerland: MDPI, 2021. http://dx.doi.org/10.3390/psf2021003007.

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Cheng, T. C., P. H. Hsieh, and S. F. Yang. "On the Hotelling T2 control chart for the vector autoregressive process." In 2011 IEEE International Conference on Quality and Reliability (ICQR). IEEE, 2011. http://dx.doi.org/10.1109/icqr.2011.6031725.

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Gholamhossein, Maryam, Ameneh Vatani, Najmeh Daroogheh, and K. Khorasani. "Prediction of the Jet Engine Performance Deterioration." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-87936.

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This paper deals with performance deterioration modelling of a single spool gas turbine engine based on time-series methods. Towards this end, two univariate and multivariate methods, namely the Autoregressive Integrated Moving Average (ARIMA) and the Vector Autoregressive (VAR) schemes are applied to predict the Turbine Entry Temperature (TET) evolution during the flight cycles for maintenance purposes. In the VAR scheme, two engine process parameters i.e. the Turbine Entry Temperature (TET) and the Compressor Temperature are employed to achieve this prediction goal. The results show that employing multivariate modelling methods lead to better prediction horizons. For each method two scenarios are considered to demonstrate the effectiveness of the models.
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Larbi, N., and J. Lardies. "Modal Parameters Estimation and Model Order Selection of a Structure Excited by a Random Force." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/vib-8095.

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Abstract A multivariate maximum likelihood procedure for the estimation of modal parameters is presented. The vibrating system is excited by a random force and sensors output only are used to estimate the natural frequencies and damping coefficients of the system. The method works in time domain and a vector autoregressive moving average (VARMA) process is used. The information about modal parameters is contained in the multivariate AR part, which is estimated using an iterative maximum likelihood algorithm. This algorithm uses a score technique and output data only. The order of the AR part is obtained via the Minimum Description Length associated with an instrumental variable procedure. Experimental results show the effectiveness of the method for model order selection and modal parameters estimation.
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Chen, Jinwei, Huisheng Zhang, and Shilie Weng. "Study on Nonlinear Identification SOFC Temperature Model Based on Particle Swarm Optimization-Least Squares Support Vector Regression." In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-56236.

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A nonlinear autoregressive network with exogenous inputs (NARX) identification model is employed for predicting the Solid oxide fuel cell (SOFC) operating temperature dynamics fast and accurately in a Solid oxide fuel cell–gas turbine (SOFC-GT) hybrid system. At the same time, the least squares support vector regression (LSSVR) method with radial basis kernel function (RBF) which uses particle swarm optimization (PSO) to optimize the LSSVR’s parameters is applied to establish the NARX model. The major factors which affect the cathode and anode outlet temperature of the SOFC-GT hybrid system are the inlet flow rate of cathode and anode. Therefore, the inlet flow rates of cathode and anode are taken as inputs of the NARX model, cathode and anode outlet temperature as outputs. With the training data sampled from the mechanism model which is derived from conservation laws, a SOFC temperature the NARX model based on the LSSVR is established. Investigations are conducted to analyze the effects of training data size and fitness function of PSO on the accuracy of the NARX model. And by comparing the temperature behaviors with the results collected form the mechanism model, the accuracy of the NARX model based on the LSSVR is verified with enough accuracy in predicting the dynamic performance of the SOFC temperature. Furthermore, in the aspect of simulation speed, the NARX model is much faster than the mechanism model because the NARX model avoids the internal complex computation process. For large size training data, the training time of the NARX model is only about 1.2s. For running all 20,000s of simulation, the predicting time of the NARX model is only about 0.2s, while the mechanism model is about 36s. In consideration of the high speed and accuracy of the NARX model, it can be applied to design valid multivariable model predictive control (MPC) schemes with high reputation.
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