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Study of volatility structures in geophysics and finance using GARCH models.

机译:使用GARCH模型研究地球物理和金融领域的波动结构。

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摘要

This work investigates the underlying volatility processes in earthquake series, high frequency (tick) data, financial indice and explosive series. Furthermore it examines the applicability of a range of GARCH specifications for modeling volatility of these series in order to identify similarities and differences in the volatility structures. The GARCH variants considered include the basic GARCH, IGARCH, ARFIMA (0,d,0)-GARCH and FIGARCH specifications. The methodology is not new, however the major contribution of this work comes in the realm of applications. The methodology is applied to three domains: Geophysics (earthquake data), Finance (high frequency data and indices) and explosives data. In all the applications the methodology provides insight into features of these series volatility.;The results show that the FIGARCH specification is favoured in the DJIA, S&-P500 and the explosives series volatility but in the BAC and JPM high-frequency data and in the earthquake series the ARFIMA-GARCH specification is preferred as it more reliably describes the volatility of these series. The WMT and IBM high-frequency data volatility were best described using the GARCH model.
机译:这项工作调查了地震序列,高频(刻度)数据,金融指数和爆炸序列中的潜在波动过程。此外,它还检查了一系列GARCH规范对这些系列的波动率建模的适用性,以便确定波动率结构的异同。考虑的GARCH变体包括基本的GARCH,IGARCH,ARFIMA(0,d,0)-GARCH和FIGARCH规范。该方法学并不新鲜,但是这项工作的主要贡献在于应用领域。该方法适用于三个领域:地球物理学(地震数据),金融(高频数据和指数)和爆炸物数据。结果表明,FIGARCH规范在DJIA,S&-P500和炸药系列的易变性中受到青睐,但在BAC和JPM高频数据以及首选地震系列ARFIMA-GARCH规范,因为它更可靠地描述了这些系列的波动性。使用GARCH模型可以最好地描述WMT和IBM高频数据的波动性。

著录项

  • 作者

    Biney, Francis.;

  • 作者单位

    The University of Texas at El Paso.;

  • 授予单位 The University of Texas at El Paso.;
  • 学科 Statistics.;Economics Finance.
  • 学位 M.S.
  • 年度 2012
  • 页码 124 p.
  • 总页数 124
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 语言学;
  • 关键词

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