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  <titleInfo>
    <title>Handbook of Modeling High-Frequency Data in Finance</title>
  </titleInfo>
  <name type="personal">
    <namePart>Viens, Frederi G.</namePart>
  </name>
  <name type="personal">
    <namePart>Mariani, Maria C.</namePart>
  </name>
  <name type="personal">
    <namePart>Florescu, Ionut.</namePart>
  </name>
  <name type="corporate">
    <namePart>Wiley InterScience (Online service)</namePart>
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  <genre authority="">Electronic books.</genre>
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    <place>
      <placeTerm type="text">Hoboken, NJ</placeTerm>
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    <publisher>Wiley</publisher>
    <dateIssued>2012</dateIssued>
    <dateIssued encoding="marc">2011</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>1 online resource (xiv, 441 pages) : illustrations</extent>
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  <abstract>This exciting volume presents cutting-edge developments in high frequency financial econometrics, spanning a diverse range of topics: stochastic modeling, statistical analysis of high-frequency data, models in econophysics, applications to the analysis of high-frequency data, systems and complex adaptive systems in finance, among a host of others. Written, in part, on the outgrowth of several recent conferences in the subject matter and in concert with over two-dozen experts in the field, the main purpose of the handbook is to mathematically illustrate the fundamental implementation of high-frequency models in the banking and financial industries, both at home and abroad, through use of real-world, time-sensitive applications. By using examples derived from consulting projects, current research and course instruction, each chapter in the book offers a systematic understanding of the recent advances in high-frequency modeling related to real-world situations. Every effort is made to present a balanced treatment between theory and practice, as well as to showcase how accuracy and efficiency in implementing various methods can be used as indispensable tools. To by-pass tedious computation, software illustrations are presented in an assortment of packages, ranging from R, C++, EXCEL-VBA, Minitab, to JMP/SAS. Shedding light on some of the most relevant open questions in the analysis of high-frequency data, this volume will be of interest to graduate students, researchers and industry professionals.</abstract>
  <tableOfContents>Frontmatter -- Analysis of Empirical Data. Estimation of NIG and VG Models for High Frequency Financial Data / Još E Figueroa-L̤pez, Steven R Lancette, Kiseop Lee, Yanhui Mi -- A Study of Persistence of Price Movement Using High Frequency Financial Data / Dragos Bozdog, Ionut Florescu, Khaldoun Khashanah, Jim Wang -- Using Boosting for Financial Analysis and Trading / Germ̀n Creamer -- Impact of Correlation Fluctuations on Securitized Structures / Eric Hillebrand, Ambar N Sengupta, Junyue Xu -- Construction of Volatility Indices Using a Multinomial Tree Approximation Method / Dragos Bozdog, Ionut Florescu, Khaldoun Khashanah, Hongwei Qiu -- Long Range Dependence Models. Long Correlations Applied to the Study of Memory Effects in High Frequency (TICK) Data, the Dow Jones Index, and International Indices / Ernest Barany, Maria Pia Beccar Varela -- Risk Forecasting with GARCH, Skewed Distributions, and Multiple Timescales / Alec N Kercheval, Yang Liu -- Parameter Estimation and Calibration for Long-Memory Stochastic Volatility Models / Alexandra Chronopoulou -- Analytical Results. A Market Microstructure Model of Ultra High Frequency Trading / Carlos A Ulibarri, Peter C Anselmo -- Multivariate Volatility Estimation with High Frequency Data Using Fourier Method / Maria Elvira Mancino, Simona Sanfelici -- The ₃Retirement₄ Problem / Cristian Pasarica -- Stochastic Differential Equations and Levy Models with Applications to High Frequency Data / Ernest Barany, Maria Pia Beccar Varela -- Solutions to Integro-Differential Parabolic Problem Arising on Financial Mathematics / Maria C Mariani, Marc Salas, Indranil Sengupta -- Existence of Solutions for Financial Models with Transaction Costs and Stochastic Volatility / Maria C Mariani, Emmanuel K Ncheuguim, Indranil Sengupta -- Index.</tableOfContents>
  <note type="statement of responsibility">edited by Frederi G. Viens, Maria C. Mariani, Ionut Florescu.</note>
  <note>Includes index.</note>
  <subject authority="lcsh">
    <topic>Finance</topic>
    <topic>Econometric models</topic>
  </subject>
  <subject authority="fast">
    <topic>Finance</topic>
    <topic>Econometric models</topic>
  </subject>
  <classification authority="lcc">HG106 .H36 2012</classification>
  <classification authority="ddc" edition="23">332.01/5195</classification>
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    <identifier type="local">(OCoLC)724644259</identifier>
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  <identifier type="isbn">9781118204580</identifier>
  <identifier type="isbn">1118204581</identifier>
  <identifier type="stock number">10.1002/9781118204580 Wiley InterScience</identifier>
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