Download or read book Deterministic and Stochastic Methods for Estimation of Intra Day Seasonal Components with High Frequency Data written by Claudio Morana and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We introduce a model for the analysis of intraday volatility of exchange rates returns, based on the structural time series methodology. The stochastic seasonal component is useful to model intra-day effects which may be different from one day to the other. The model is estimated with high frequency data for the Deutsche mark-U.S. dollar exchange rates for 1993 and 1996. The structural time series model performs well in terms of coherence with the theoretical aggregation properties of GARCH models, it is effective both in terms of one-period and multi-period forecasting ability and in terms of describing reactions to announcements of US employment reports.
Download or read book Using Self Organizing Maps to Adjust Intra Day Seasonality written by Walid Ben Omrane and published by . This book was released on 2013 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: The existence of an intra-day seasonality component within financial market variables (volatility, volume, activity,. . .), has been highlighted in many previous works. To adjust raw data from their cyclical component, many studies start by implementing the intra-daily average observations model (IAOM) and/or some smoothing techniques (e.g. the kernel method) in order to remove the day of the week effect. When seasonality involves only a deterministic component, IAOM method succeed in estimating periodicity almost without estimation error. However, when seasonality contains both deterministic and stochastic components (e.g. closed days), we show that either the IAOM or the kernel method fail to capture it. We introduce the use of the self-organizing maps (SOM) as a solution. SOM are based on neural network learning and nonlinear projections. Their flexibility allows capturing seasonality even in thepresence of stochastic cycles.
Download or read book High Frequency Financial Econometrics written by Luc Bauwens and published by Springer Science & Business Media. This book was released on 2007-12-31 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shedding light on some of the most pressing open questions in the analysis of high frequency data, this volume presents cutting-edge developments in high frequency financial econometrics. Coverage spans a diverse range of topics, including market microstructure, tick-by-tick data, bond and foreign exchange markets, and large dimensional volatility modeling. The volume is of interest to graduate students, researchers, and industry professionals.
Download or read book Seasonal Adjustment Methods and Real Time Trend Cycle Estimation written by Estela Bee Dagum and published by Springer. This book was released on 2016-06-20 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.
Download or read book The Econometric Analysis of Seasonal Time Series written by Eric Ghysels and published by Cambridge University Press. This book was released on 2001-06-18 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent developments in the econometric analysis of seasonal economic time series, summarizing a decade of theoretical advances in the area. The authors discuss the asymptotic distribution theory for linear nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with its implications for estimation and hypothesis testing. Moreover, a comprehensive analysis of periodic models is provided, including stationary and nonstationary cases. The book concludes with a discussion of some nonlinear seasonal and periodic models. The treatment is designed for an audience of researchers and advanced graduate students.
Download or read book Seasonal Analysis of Economic Time Series written by Arnold Zellner and published by . This book was released on 1978 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book International Financial Markets written by Julien Chevallier and published by Routledge. This book was released on 2019-06-28 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields of commodities finance, mathematics & stochastics, international macroeconomics and financial econometrics. International Financial Markets: Volume I provides a key repository on the current state of knowledge, the latest debates and recent literature on international financial markets. Against the background of the "financialization of commodities" since the 2008 sub-primes crisis, section one contains recent contributions on commodity and financial markets, pushing the frontiers of applied econometrics techniques. The second section is devoted to exchange rate and current account dynamics in an environment characterized by large global imbalances. Part three examines the latest research in the field of meta-analysis in economics and finance. This book will be useful to students and researchers in applied econometrics; academics and students seeking convenient access to an unfamiliar area. It will also be of great interest established researchers seeking a single repository on the current state of knowledge, current debates and relevant literature.
Download or read book Macroeconomic Fundamentals Price Discovery and Volatility Dynamics in Emerging Markets written by and published by . This book was released on 2009 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Is the Diurnal Pattern Sufficient to Explain Intraday Variation In Volatility A Nonparametric Assessment written by Kim Christensen and published by . This book was released on 2018 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we propose a nonparametric way to test the hypothesis that time-variation in intraday volatility is caused solely by a deterministic and recurrent diurnal pattern. We assume that noisy high-frequency data from a discretely sampled jump-diffusion process are available. The test is then based on asset returns, which are deflated by the seasonal component and therefore homoskedastic under the null. To construct our test statistic, we extend the concept of pre-averaged bipower variation to a general Itô semimartingale setting via a truncation device. We prove a central limit theorem for this statistic and construct a positive semi-definite estimator of the asymptotic covariance matrix. The t-statistic (after pre-averaging and jump-truncation) diverges in the presence of stochastic volatility and has a standard normal distribution otherwise. We show that replacing the true diurnal factor with a model-free jump- and noise-robust estimator does not affect the asymptotic theory. A Monte Carlo simulation also shows this substitution has no discernable impact in finite samples. The test is, however, distorted by small infinite-activity price jumps. To improve inference, we propose a new bootstrap approach, which leads to almost correctly sized tests of the null hypothesis. We apply the developed framework to a large cross-section of equity high-frequency data and find that the diurnal pattern accounts for a rather significant fraction of intraday variation in volatility, but important sources of heteroskedasticity remain present in the data.
Download or read book Estimating Stochastic Volatility and Jumps Using High Frequency Data and Bayesian Methods written by Milan Fičura and published by . This book was released on 2015 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are comparing two approaches for stochastic volatility and jumps estimation in the EUR/USD time series - the non-parametric power-variation approach using high-frequency returns, and the parametric Bayesian approach (MCMC estimation of SVJD models) using daily returns. We find that both of the methods do identify continuous stochastic volatility similarly, but they do not identify similarly the jump component. Firstly - the jumps estimated using the non-parametric high-frequency estimators are much more numerous than in the case of the Bayesian method using daily data. More importantly - we find that the probabilities of jump occurrences assigned to every day by both of the methods are virtually no rank-correlated (Spearman rank correlation is 0.0148) meaning that the two methods do not identify jumps at the same days. Actually the jump probabilities inferred using the non-parametric approach are not much correlated even with the daily realized variance and the daily squared returns, indicating that the discontinuous price changes (jumps) observed on high-frequencies may not be distinguishable (from the continuous volatility) on the daily frequency. As an additional result we find strong evidence for jump size dependence and jump clustering (based on the self-exciting Hawkes process) of the jumps identified using the non-parametric method (the shrinkage estimator).
Download or read book Forecasting principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Download or read book Econometric Modelling of Stock Market Intraday Activity written by Luc Bauwens and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past 25 years, applied econometrics has undergone tremen dous changes, with active developments in fields of research such as time series, labor econometrics, financial econometrics and simulation based methods. Time series analysis has been an active field of research since the seminal work by Box and Jenkins (1976), who introduced a gen eral framework in which time series can be analyzed. In the world of financial econometrics and the application of time series techniques, the ARCH model of Engle (1982) has shifted the focus from the modelling of the process in itself to the modelling of the volatility of the process. In less than 15 years, it has become one of the most successful fields of 1 applied econometric research with hundreds of published papers. As an alternative to the ARCH modelling of the volatility, Taylor (1986) intro duced the stochastic volatility model, whose features are quite similar to the ARCH specification but which involves an unobserved or latent component for the volatility. While being more difficult to estimate than usual GARCH models, stochastic volatility models have found numerous applications in the modelling of volatility and more particularly in the econometric part of option pricing formulas. Although modelling volatil ity is one of the best known examples of applied financial econometrics, other topics (factor models, present value relationships, term structure 2 models) were also successfully tackled.
Download or read book Aanwinsten van de Centrale Bibliotheek Queteletfonds written by Bibliothèque centrale (Fonds Quetelet) and published by . This book was released on 1999 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Time Series Models written by Andrew C. Harvey and published by Financial Times/Prentice Hall. This book was released on 1993 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: A companion volume to The Econometric Analysis of Time series, this book focuses on the estimation, testing and specification of dynamic models which are not based on any behavioural theory. It covers univariate and multivariate time series and emphasizes autoregressive moving-average processes.
Download or read book Izvestiya written by and published by . This book was released on 2002 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Methods in Finance written by G. S. Maddala and published by . This book was released on 1996-12-11 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive reference work for teaching at graduate level and research in empirical finance. The chapters cover a wide range of statistical and probabilistic methods applied to a variety of financial methods and are written by internationally renowned experts.
Download or read book Analysis of Financial Time Series written by Ruey S. Tsay and published by Wiley-Interscience. This book was released on 2001-11-01 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamental topics and new methods in time series analysis Analysis of Financial Time Series provides a comprehensive and systematic introduction to financial econometric models and their application to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods. Timely topics and recent results include: Value at Risk (VaR) High-frequency financial data analysis Markov Chain Monte Carlo (MCMC) methods Derivative pricing using jump diffusion with closed-form formulas VaR calculation using extreme value theory based on a non-homogeneous two-dimensional Poisson process Multivariate volatility models with time-varying correlations Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance, Analysis of Financial Time Series offers an in-depth and up-to-date account of these vital methods.
