Download or read book Dynamic Factor Model with Non linearities written by Anna Petronevich and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis is dedicated to the study of a particular class of non-linear Dynamic Factor Models, the Dynamic Factor Models with Markov Switching (MS-DFM). Combining the features of the Dynamic Factor model and the Markov Switching model, i.e. the ability to aggregate massive amounts of information and to track recurring processes, this framework has proved to be a very useful and convenient instrument in many applications, the most important of them being the analysis of business cycles.In order to monitor the health of an economy and to evaluate policy results, the knowledge of the currentstate of the business cycle is essential. However, it is not easy to determine since there is no commonly accepted dataset and method to identify turning points, and the official institutions announce a newturning point, in countries where such practice exists, with a structural delay of several months. The MS-DFM is able to resolve these issues by providing estimates of the current state of the economy in a timely, transparent and replicable manner on the basis of the common component of macroeconomic indicators characterizing the real sector. The thesis contributes to the vast literature in this area in three directions. In Chapter 3, I compare the two popular estimation techniques of the MS-DFM, the one-step and the two-step methods, and apply them to the French data to obtain the business cycle turning point chronology. In Chapter 4, on the basis of Monte Carlo simulations, I study the consistency of the estimators of the preferred technique -the two-step estimation method, and analyze their behavior in small samples. In Chapter 5, I extend the MS-DFM and suggest the Dynamical Influence MS-DFM, which allows to evaluate the contribution of the financial sector to the dynamics of the business cycle and vice versa, taking into consideration that the interaction between them can be dynamic.
Download or read book The Oxford Handbook of Economic Forecasting written by Michael P. Clements and published by OUP USA. This book was released on 2011-07-08 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.
Download or read book Dynamic Linear Models with R written by Giovanni Petris and published by Springer Science & Business Media. This book was released on 2009-06-12 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.
Download or read book Dynamic Factor Models written by Jörg Breitung and published by . This book was released on 2005 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dynamic Factor Models written by Siem Jan Koopman and published by Emerald Group Publishing. This book was released on 2016-01-08 with total page 685 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.
Download or read book Large Dimensional Factor Analysis written by Jushan Bai and published by Now Publishers Inc. This book was released on 2008 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.
Download or read book Nonlinear Dynamic Factor Models written by Gianluca Giudice and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dynamic Factor Trees and Forests written by Daniel Ehmann and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning models are often considered to be "black boxes" that provide only little room for the incorporation of theory (cf. e.g. Mukherjee, 2017; Veltri, 2017). This article proposes so-called Dynamic Factor Trees (DFT) and Dynamic Factor Forests (DFF) for macroeconomic forecasting, which synthesize the recent machine learning, dynamic factor model and business cycle literature within a unified statistical machine learning framework for model-based recursive partitioning proposed in Zeileis, Hothorn and Hornik (2008). DFTs and DFFs are non-linear and state-dependent forecasting models, which reduce to the standard Dynamic Factor Model (DFM) as a special case and allow us to embed theory-led factor models in powerful tree-based machine learning ensembles conditional on the state of the business cycle. The out-of-sample forecasting experiment for short-term U.S. GDP growth predictions combines three distinct FRED-datasets, yielding a balanced panel with over 375 indicators from 1967 to 2018 (FRED, 2019; McCracken & Ng, 2016, 2019a, 2019b). Our results provide strong empirical evidence in favor of the proposed DFTs and DFFs and show that they significantly improve the predictive performance of DFMs by almost 20% in terms of MSFE. Interestingly, the improvements materialize in both expansionary and recessionary periods, suggesting that DFTs and DFFs tend to perform not only sporadically but systematically better than DFMs. Our findings are fairly robust to a number of sensitivity tests and hold exciting avenues for future research.
Download or read book Dynamic Factor Trees and Forests written by Daniel Wochner and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning models are often considered to be "black boxes" that provide only little room for the incorporation of theory (cf. e.g. Mukherjee, 2017; Veltri, 2017). This article proposes so-called Dynamic Factor Trees (DFT) and Dynamic Factor Forests (DFF) for macroeconomic forecasting, which synthesize the recent machine learning, dynamic factor model and business cycle literature within a unified statistical machine learning framework for model-based recursive partitioning proposed in Zeileis, Hothorn and Hornik (2008). DFTs and DFFs are non-linear and state-dependent forecasting models, which reduce to the standard Dynamic Factor Model (DFM) as a special case and allow us to embed theory-led factor models in powerful tree-based machine learning ensembles conditional on the state of the business cycle. The out-of-sample forecasting experiment for short-term U.S. GDP growth predictions combines three distinct FRED-datasets, yielding a balanced panel with over 375 indicators from 1967 to 2018 (FRED, 2019; McCracken & Ng, 2016, 2019a, 2019b). Our results provide strong empirical evidence in favor of the proposed DFTs and DFFs and show that they significantly improve the predictive performance of DFMs by almost 20% in terms of MSFE. Interestingly, the improvements materialize in both expansionary and recessionary periods, suggesting that DFTs and DFFs tend to perform not only sporadically but systematically better than DFMs. Our findings are fairly robust to a number of sensitivity tests and hold exciting avenues for future research.
Download or read book Research Handbook on Hedge Funds Private Equity and Alternative Investments written by Phoebus Athanassiou and published by Edward Elgar Publishing. This book was released on 2012-01-01 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique and detailed Handbook provides a comprehensive source of analysis and research on alternative investment funds in the EU, the US and other leading jurisdictions. Expert contributors offer an unparalleled perspective on the contemporary alternative funds industry, the main areas of regulatory policy concern surrounding its activities, and the role that alternative funds have played in recent financial crises, as well as an account of the rules governing their operation in selected jurisdictions. Providing insight and analysis of the contemporary investment funds industry at a time of crisis and transition, the Research Handbook on Hedge Funds, Private Equity and Alternative Investments will be a valuable tool for scholars, practitioners and policymakers alike.
Download or read book Applied Dynamic Factor Modeling in Finance written by Ross Askanazi and published by . This book was released on 2017 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, I study model misspecification in applications of dynamic factor models to finance. In Chapter 1, my co-author Jacob Warren and I examine factors for volatility of equities. Historical literature on the subject decomposes volatility into a factor component and an idiosyncratic remainder. Recent work has suggested that idiosyncratic volatility of US equities data has a factor structure, with the factor highly correlated with, and possibly precisely the market volatility. In this paper we attempt to characterize the underlying factor and find that it can be decomposed into a statistical (PCA) and structural (market volatility) factor. We also show that this feature is not unique to equities, appearing in diverse sets of financial data. Lastly, we find that this dual-factor approach is slightly dominated in forecasting environments by a single statistical factor, suggesting that accurate measurement of the factors provides a direction for future work. In Chapter 2, I explore the use of dynamic factor models in yield curve forecasting and an exploration of the spanning hypothesis--that is, whether all information necessary for forecasting yields is contained in the current yield curve. Only linear tests of the spanning hypothesis are typically conducted in the literature, and the results are subject to substantial disagreement. In this paper, I explore a key modern nonlinearity, namely the zero lower bound (ZLB). I first demonstrate in simulation that only very small nonlinearities in the measurement equation are necessary to break down the assumed linear spanning relationship. Because bond yields are determined by forward-looking behavior of investors, the effect of the ZLB affects spanning results as early as 1995. New nonlinear spanning tests are found to behave appropriately. Using the full set of yields instead of truncating to a small number of principal components is quantitatively important but does not eliminate the omitted nonlinearity effect.
Download or read book Nonlinear Dynamics in Equilibrium Models written by John Stachurski and published by Springer Science & Business Media. This book was released on 2012-01-25 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal growth theory studies the problem of efficient resource allocation over time, a fundamental concern of economic research. Since the 1970s, the techniques of nonlinear dynamical systems have become a vital tool in optimal growth theory, illuminating dynamics and demonstrating the possibility of endogenous economic fluctuations. Kazuo Nishimura's seminal contributions on business cycles, chaotic equilibria and indeterminacy have been central to this development, transforming our understanding of economic growth, cycles, and the relationship between them. The subjects of Kazuo's analysis remain of fundamental importance to modern economic theory. This book collects his major contributions in a single volume. Kazuo Nishimura has been recognized for his contributions to economic theory on many occasions, being elected fellow of the Econometric Society and serving as an editor of several major journals. Chapter “Introduction” is available open access under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License via link.springer.com.
Download or read book Simultaneous Statistical Inference written by Thorsten Dickhaus and published by Springer Science & Business Media. This book was released on 2014-01-23 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.
Download or read book Mathematical Models of Non Linear Excitations Transfer Dynamics and Control in Condensed Systems and Other Media written by Ludmilla A. Uvarova and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: The articles in this book are derived from the Third International Conference of the same name, held June 29-July 3, 1998. Topics include: nonlinear exaltations in condensed systems, evolution of complex systems, dynamics and structure of molecular and biomolecular systems, mathematical models of transfer processes in nonlinear systems and numerical modeling and algorithms.
Download or read book Machine Learning and Knowledge Discovery in Databases written by Wray Buntine and published by Springer Science & Business Media. This book was released on 2009-09-03 with total page 787 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009. The 106 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 422 paper submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Download or read book Dynamic Factor Analysis written by Gy Bánkövi and published by . This book was released on 1986 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dynamic Factor Demand in a Rationing Context written by Werner Smolny and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: A macroeconomic disequilibrium model is developed for the Federal Republic of Germany. Starting with a microeconomic model of firm's behaviour, the optimal dynamic adjustment of employment and investment is derived. The model of the firm is complemented by an explicite aggregation procedure which allows to derive macroeconomic relations. The model is estimated with macroeconomic data for the Federal Republic of Germany. An important feature is the consistent introduction of dynamic adjustment into a model of the firm. A new method is the particular approach of a delayed adjustment of employment and investment. The estimation results show significant underutilizations of labour and capital and indicate the importance of supply constraints for imports and exports. As the most prominent result, they reveal the importance of the slow adjustment of employment and investment for the macroeconomic situation in Germany and especially for the persistence of high unemployment in the eighties.
