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Author : Scott T. Murdoch
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (857 download)
Download or read book Three Essays on Forecasting in Nonlinear Models written by Scott T. Murdoch and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Young gui Kim
Publisher :
ISBN 13 :
Total Pages : 212 pages
Book Rating : 4.3/5 (129 download)
Download or read book Three Essays on Nonlinear Models for Fractional Response Variables with Time-varying Individual Heterogeneity written by Young gui Kim and published by . This book was released on 2009 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Zhengfeng Guo
Publisher :
ISBN 13 :
Total Pages : 86 pages
Book Rating : 4.:/5 (846 download)
Download or read book Three Essays on Nonlinear Time Series Econometrics written by Zhengfeng Guo and published by . This book was released on 2011 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jin-Lung Lin
Publisher :
ISBN 13 :
Total Pages : 86 pages
Book Rating : 4.F/5 ( download)
Download or read book Three Essays on Nonlinear Time Series written by Jin-Lung Lin and published by . This book was released on 1991 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Andreas Peter Gottschling
Publisher :
ISBN 13 :
Total Pages : 284 pages
Book Rating : 4.:/5 (318 download)
Download or read book Three Essays in Neural Networks and Financial Prediction written by Andreas Peter Gottschling and published by . This book was released on 1997 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Mario Giacomazzo
Publisher :
ISBN 13 :
Total Pages : 187 pages
Book Rating : 4.:/5 (115 download)
Download or read book Three Essays on Shrinkage Estimation and Model Selection of Linear and Nonlinear Time Series Models written by Mario Giacomazzo and published by . This book was released on 2018 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary objective in time series analysis is forecasting. Raw data often exhibits nonstationary behavior: trends, seasonal cycles, and heteroskedasticity. After data is transformed to a weakly stationary process, autoregressive moving average (ARMA) models may capture the remaining temporal dynamics to improve forecasting. Estimation of ARMA can be performed through regressing current values on previous realizations and proxy innovations. The classic paradigm fails when dynamics are nonlinear; in this case, parametric, regime-switching specifications model changes in level, ARMA dynamics, and volatility, using a finite number of latent states. If the states can be identified using past endogenous or exogenous information, a threshold autoregressive (TAR) or logistic smooth transition autoregressive (LSTAR) model may simplify complex nonlinear associations to conditional weakly stationary processes. For ARMA, TAR, and STAR, order parameters quantify the extent past information is associated with the future. Unfortunately, even if model orders are known a priori, the possibility of over-fitting can lead to sub-optimal forecasting performance. By intentionally overestimating these orders, a linear representation of the full model is exploited and Bayesian regularization can be used to achieve sparsity. Global-local shrinkage priors for AR, MA, and exogenous coefficients are adopted to pull posterior means toward 0 without over-shrinking relevant effects. This dissertation introduces, evaluates, and compares Bayesian techniques that automatically perform model selection and coefficient estimation of ARMA, TAR, and STAR models. Multiple Monte Carlo experiments illustrate the accuracy of these methods in finding the "true" data generating process. Practical applications demonstrate their efficacy in forecasting.
Author : 武亮
Publisher :
ISBN 13 :
Total Pages : 306 pages
Book Rating : 4.:/5 (795 download)
Download or read book Three Essays on Market-based Forecasting Models written by 武亮 and published by . This book was released on 2011 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jin-Lung Lin
Publisher :
ISBN 13 :
Total Pages : 148 pages
Book Rating : 4.:/5 (318 download)
Download or read book Three Essays on Nonlinear Time Series written by Jin-Lung Lin and published by . This book was released on 1991 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Dimitris Korompilis-Magkas
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (141 download)
Download or read book Three Essays in Macroeconomic Forecasting Using Bayesian Model Selection written by Dimitris Korompilis-Magkas and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis explores several aspects of Bayesian model selection in time series forecasting of macroeconomic variables. The contribution is provided in three essays. In the first essay (Chapter 2) I forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coefficients to change over time, but also for the entire forecasting model to change over time. I find that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coefficient models. I also provide evidence on which sets of predictors are relevant for forecasting in each period. In the second essay (Chapter 3) I address the issue of improving the forecasting performance of vector autoregressions (VARs) when the set of available predictors is inconveniently large to handle with methods and diagnostics used in traditional small-scale models. First, I summarize available information from a large dataset into a considerably smaller set of variables through factors estimated using standard principal components. However, even in the case of reducing the dimension of the data the true number of factors may still be large. For that reason I introduce in my analysis simple and efficient Bayesian model selction methods. I conduct model estimation and selection of predictors automatically through a stochastic search variable selection (SSVS) algorithm which requires minimal input by the user. I apply these methods to forecast 8 main U.S. macroeconomic variables using 124 potential predictors. I find improved out of sample fit in high dimensional specifications that would otherwise suffer from the proliferation of parameters. Finally, in the third essay (Chapter 4) I develop methods for automatic selection of variables in forecasting Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I extend the algorithms of Chapter 3 and provide computationally efficient algorithms for stochastic variable selection in generic (linear and nonlinear) VARs. The performance of the proposed variable selection method is assessed in a small Monte Carlo experiment, and in forecasting four short macroeconmic series for the UK using time-varying parameters vector autoregressions (TVP-VARs). I find that restricted models consistently improve upon their unrestricted counterparts in forecasting, showing the merits of variable selection in selecting parsimonious models.
Author : Wanbin Wang
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (144 download)
Download or read book Essays on Financial Applications of Nonlinear Models written by Wanbin Wang and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we examine the relationship between news and the stock market. Further, we explore methods and build new nonlinear models for forecasting stock price movement and portfolio optimization based on past stock prices and on one type of big data, news items, which are obtained through the RavenPack News Analytics Global Equities editions. The thesis consists of three essays. In Essay 1, we investigate the relationship between news items and stock prices using the artificial neural network (ANN) model. First, we use Granger causality to ascertain how news items affect stock prices. The results show that news volume is not the Granger cause of stock price change; rather, news sentiment is. Second, we test the semi-strong form efficient market hypothesis, whereas most existing research testing efficient market hypothesis focuses on the weak-form version. Our ANN strategies consistently outperform the passive buy-and-hold strategy and this finding is apparently at odds with the notion of the efficient market hypothesis. Finally, using news sentiment analytics from RavenPack Dow Jones News Analytics, we show positive profitability with out-of-sample prediction using the proposed ANN strategies for Google Inc. (NASDAQ: GOOG). In Essay 2, we expand the utility of the information from news volume and news sentiments to encompass portfolio diversification. For the Dow Jones Industrial Average (DJIA) components, we assign different weights to build portfolios according to their weekly news volumes or news sentiments. Our results show that news volume contributes to portfolio variance both in-sample and out-of-sample: positive news sentiment contributes to the portfolio return in-sample, while negative contributes to the portfolio return out-of-sample, which is a consequence of investors overreacting to the news sentiment. Further, we propose a novel approach to portfolio diversification using the k-Nearest Neighbors (kNN) algorithm based on the idea that news sentiment correlates with stock returns. Out-of-sample results indicate that such strategy dominates the benchmark DJIA index portfolio. In Essay 3, we propose a new model called the Combined Markov and Hidden Markov Model (CMHMM), in which observation is affected by a Markov model and an HMM (Hidden Markov Model) model. The three fundamental questions of the CMHMM are discussed. Further, the application of the CMHMM, in which the news sentiment is one observation and the stock return is the other, is discussed. The empirical results of the trading strategy based on the CMHMM show the potential applications of the proposed model in finance. This thesis contributes to the literature in a number of ways. First, it extends the literature on financial applications of nonlinear models. We explore the applications of the ANNs and kNN in the financial market. Besides, the proposed new CMHMM model adheres to the nature of the stock market and has better potential prediction ability. Second, the empirical results from this dissertation contribute to the understanding of the relationship between news and the stock market. For instance, our research found that news volume contributes to the portfolio return and that investors overreact to news sentiment--a phenomenon that has been discussed by other scholars from different angles.
Author : Niels Haldrup
Publisher : OUP Oxford
ISBN 13 : 0191669547
Total Pages : 393 pages
Book Rating : 4.1/5 (916 download)
Download or read book Essays in Nonlinear Time Series Econometrics written by Niels Haldrup and published by OUP Oxford. This book was released on 2014-06-26 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.
Author : Jason J. Wu
Publisher :
ISBN 13 :
Total Pages : 168 pages
Book Rating : 4.:/5 (89 download)
Download or read book Three Essays on Time Series Inference and Forecasting written by Jason J. Wu and published by . This book was released on 2007 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Clive W. J. Granger
Publisher : Cambridge University Press
ISBN 13 : 9780521796491
Total Pages : 400 pages
Book Rating : 4.7/5 (964 download)
Download or read book Essays in Econometrics written by Clive W. J. Granger and published by Cambridge University Press. This book was released on 2001-07-23 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: These are econometrician Clive W. J. Granger's major essays in causality, integration, cointegration, and long memory.
Author : G. Elliott
Publisher : Elsevier
ISBN 13 : 0444513957
Total Pages : 1071 pages
Book Rating : 4.4/5 (445 download)
Download or read book Handbook of Economic Forecasting written by G. Elliott and published by Elsevier. This book was released on 2006-07-14 with total page 1071 pages. Available in PDF, EPUB and Kindle. Book excerpt: Section headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.
Author : Martin Casdagli
Publisher : Westview Press
ISBN 13 :
Total Pages : 564 pages
Book Rating : 4.:/5 (318 download)
Download or read book Nonlinear Modeling And Forecasting written by Martin Casdagli and published by Westview Press. This book was released on 1992-06-20 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on a Santa Fe Institute and NATO sponsored workshop, this book brings together the ideas of leading researchers in the rapidly expanding, interdisciplinary field of nonlinear modeling in an attempt to stimulate the cross-fertilization of ideas and the search for unifying themes. The central theme of the workshop was the construction of nonlinear models from time-series data. Approaches to this problem have drawn from the disciplines of multivariate function approximation and neural nets, dynamical systems and chaos, statistics, information theory, and control theory. Applications have been made to economics, mechanical engineering, meteorology, speech processing, biology, and fluid dynamics.
Author : Menzie David Chinn
Publisher :
ISBN 13 :
Total Pages : 318 pages
Book Rating : 4.:/5 (33 download)
Download or read book Three Essays in International Finance written by Menzie David Chinn and published by . This book was released on 1991 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Novella Maugeri
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (955 download)
Download or read book Three Essays on Nonlinear Time-series Econometrics written by Novella Maugeri and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
