Modelling Irregularly Spaced Transactions in Financial Markets
Author: Christopher John Ulph
Publisher:
Published: 1999
Total Pages: 259
ISBN-13:
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Author: Christopher John Ulph
Publisher:
Published: 1999
Total Pages: 259
ISBN-13:
DOWNLOAD EBOOKAuthor: Nikolaus Hautsch
Publisher: Springer Science & Business Media
Published: 2011-01-07
Total Pages: 297
ISBN-13: 3642170153
DOWNLOAD EBOOKThis book provides a methodological framework to model univariate and multivariate irregularly spaced financial data. It gives a thorough review of recent developments in the econometric literature, puts forward existing approaches and opens up new directions. The book presents alternative ways to model so-called financial point processes using dynamic duration as well as intensity models and discusses their ability to account for specific features of point process data, like the occurrence of time-varying covariates, censoring mechanisms and multivariate structures. Moreover, it illustrates the use of various types of financial point processes to model financial market activity from different viewpoints and to construct volatility and liquidity measures under explicit consideration of the passing trading time.
Author: Jeffrey R. Russell
Publisher:
Published: 1996
Total Pages: 274
ISBN-13:
DOWNLOAD EBOOKAuthor: Nikolaus Hautsch
Publisher:
Published: 2004-04-06
Total Pages: 304
ISBN-13: 9783642170164
DOWNLOAD EBOOKAuthor: Yong Zeng
Publisher: Springer Science & Business Media
Published: 2013-08-15
Total Pages: 358
ISBN-13: 1461477891
DOWNLOAD EBOOKState-space models as an important mathematical tool has been widely used in many different fields. This edited collection explores recent theoretical developments of the models and their applications in economics and finance. The book includes nonlinear and non-Gaussian time series models, regime-switching and hidden Markov models, continuous- or discrete-time state processes, and models of equally-spaced or irregularly-spaced (discrete or continuous) observations. The contributed chapters are divided into four parts. The first part is on Particle Filtering and Parameter Learning in Nonlinear State-Space Models. The second part focuses on the application of Linear State-Space Models in Macroeconomics and Finance. The third part deals with Hidden Markov Models, Regime Switching and Mathematical Finance and the fourth part is on Nonlinear State-Space Models for High Frequency Financial Data. The book will appeal to graduate students and researchers studying state-space modeling in economics, statistics, and mathematics, as well as to finance professionals.
Author: Torben Gustav Andersen
Publisher: Springer Science & Business Media
Published: 2009-04-21
Total Pages: 1045
ISBN-13: 3540712976
DOWNLOAD EBOOKThe Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
Author: Ingmar Nolte
Publisher:
Published: 2003
Total Pages: 218
ISBN-13:
DOWNLOAD EBOOKAuthor: Marek Musiela
Publisher: Springer Science & Business Media
Published: 2006-01-20
Total Pages: 721
ISBN-13: 3540266534
DOWNLOAD EBOOKA new edition of a successful, well-established book that provides the reader with a text focused on practical rather than theoretical aspects of financial modelling Includes a new chapter devoted to volatility risk The theme of stochastic volatility reappears systematically and has been revised fundamentally, presenting a much more detailed analyses of interest-rate models
Author: Sascha Mergner
Publisher: Universitätsverlag Göttingen
Published: 2009
Total Pages: 235
ISBN-13: 3941875221
DOWNLOAD EBOOKState space models play a key role in the estimation of time-varying sensitivities in financial markets. The objective of this book is to analyze the relative merits of modern time series techniques, such as Markov regime switching and the Kalman filter, to model structural changes in the context of widely used concepts in finance. The presented material will be useful for financial economists and practitioners who are interested in taking time-variation in the relationship between financial assets and key economic factors explicitly into account. The empirical part illustrates the application of the various methods under consideration. As a distinctive feature, it includes a comprehensive analysis of the ability of time-varying coefficient models to estimate and predict the conditional nature of systematic risks for European industry portfolios.
Author: Tze Leung Lai
Publisher: Springer Science & Business Media
Published: 2008-07-25
Total Pages: 363
ISBN-13: 0387778268
DOWNLOAD EBOOKThe idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.