Journal ArticleDOI
Time series models : in econometrics, finance and other fields
Abstract:
Statistical Aspects of ARCH and Scholastic Volatility Likelihood-Based Inference for Cointegration of Some Non-Stationary Time Series Forecasting in Macroeconomics Longitudinal Panel Data: An Overview of Current Methodologyread more
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Journal ArticleDOI
Analysis of data clusters obtained by self-organizing methods
TL;DR: Using SOM techniques, self-organizing maps (SOM) and group method of data handling (GMDH) algorithms are applied to reveal new structures in stock market behavior of the companies drawing up Dow Jones index.
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Modeling Foreign Exchange Rates with Jumps
John M. Maheu,Thomas H. McCurdy +1 more
TL;DR: In this paper, the authors proposed a new discrete-time model of returns in which jumps capture persistence in the conditional variance and higher-order moments, and used realized volatility to assess out-of-sample variance forecasts.
Book ChapterDOI
Resampling and Subsampling for Financial Time Series
TL;DR: Methods that can be applied to generate pseudo-series of log-returns which mimic closely the essential dependence characteristics of the observed series are discussed and the bootstrap methods applied to financial data are reviewed.
Journal ArticleDOI
Bayesian estimation of stochastic volatility models based on OU processes with marginal Gamma law
TL;DR: In this paper, a Markov chain Monte Carlo (MCMCMC) scheme is proposed to enable multiple updates of the latent point process, and generalizes single updating algorithm used earlier.
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Unpredictability and the Foundations of Economic Forecasting
TL;DR: The authors revisited the concept of unpredictability to explore its implications for forecasting strategies in a non-stationary world subject to structural breaks, where model and mechanism differ, and showed that structural breaks are the key problem, exacerbated by conflicting requirements on forecast error corrections.