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Essays on fine structure of asset returns, jumps, and stochastic volatility.

机译:关于资产收益率,跳跃和随机波动的精细结构的论文。

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摘要

There has been an on-going debate about choices of the most suitable model amongst a variety of model specifications and parameterizations. The first dissertation essay investigates whether asymmetric leptokurtic return distributions such as Hansen's (1994) skewed t-distribution combined with GARCH specifications can outperform mixed GARCH-jump models such as Maheu and McCurdy's (2004) GARJI model incorporating the autoregressive conditional jump intensity parameterization in the discrete-time framework. I find that the more parsimonious GJR-HT model is superior to mixed GARCH jump models. Likelihood-ratio (LR) tests, information criteria such as AIC, SC, and HQ and Value-at-Risk (VaR) analysis confirm that GJR-HT is one of the most suitable model specifications which gives us both better fit to the data and parsimony of parameterization. The benefits of estimating GARCH models using asymmetric leptokurtic distributions are more substantial for highly volatile series such as emerging stock markets, which have a higher degree of non-normality. Furthermore, Hansen's skewed t-distribution also provides us with an excellent risk management tool evidenced by VaR analysis.; The second dissertation essay provides a variety of empirical evidences to support redundancy of stochastic volatility for SP500 index returns when stochastic volatility is taken into account with infinite activity pure Levy jumps models and the importance of stochastic volatility to reduce pricing errors for SP500 index options without regard to jumps specifications. This finding is important because recent studies have shown that stochastic volatility in a continuous-time framework provides an excellent fit for financial asset returns when combined with finite-activity Merton's type compound Poisson jump-diffusion models. The second essay also shows that stochastic volatility with jumps (SVJ) and extended variance-gamma with stochastic volatility (EVGSV) models perform almost equally well for option pricing, which strongly imply that the type of Levy jumps specifications is not important factors to enhance model performances once stochastic volatility is incorporated. In the second essay, I compute option prices via improved Fast Fourier Transform (FFT) algorithm using characteristic functions to match arbitrary log-strike grids with equal intervals with each moneyness and maturity of actual market option prices.
机译:关于在各种模型规范和参数化中选择最合适的模型的争论一直持续。第一篇论文研究了Hansen(1994)的偏t分布与GARCH规范相结合的非对称七阶收益率分布是否能胜过Mahech和McCurdy(2004)的GARJI模型的混合GARCH跳跃模型,该模型将自回归条件跳跃强度参数化离散时间框架。我发现更简约的GJR-HT模型优于混合GARCH跳跃模型。似然比(LR)测试,AIC,SC和HQ等信息标准以及风险价值(VaR)分析证实,GJR-HT是最合适的模型规格之一,这使我们双方都能更好地适应数据和简化的参数化。对于高度波动的序列(例如新兴股票市场,其具有较高的非正态性),使用不对称的七阶分布估计GARCH模型的好处更为可观。此外,汉森的偏态t分布还为我们提供了出色的风险管理工具,这一点已通过VaR分析得到了证明。第二篇论文提供了各种经验证据,当无限活动考虑纯随机波动率模型时,考虑到随机波动率时,SP500指数收益的随机波动率冗余,以及随机波动率对减少SP500指数期权定价误差的重要性跳规格。这一发现很重要,因为最近的研究表明,当与有限活动默顿类型的复合泊松跳跃扩散模型结合使用时,连续时间框架中的随机波动率非常适合金融资产收益。第二篇文章还显示,带有跳跃的随机波动率(SVJ)和带有随机波动率的扩展方差-伽玛(EVGSV)模型在期权定价中的表现几乎相同,这强烈表明征费跳跃规范的类型不是增强模型的重要因素一旦纳入随机波动率的表现。在第二篇文章中,我通过改进的快速傅立叶变换(FFT)算法使用特征函数来计算期权价格,这些特征函数将等间隔的任意对数罢工网格与实际市场期权价格的每笔收益和期限匹配。

著录项

  • 作者

    Yu, Jung-Suk.;

  • 作者单位

    University of New Orleans.;

  • 授予单位 University of New Orleans.;
  • 学科 Economics Finance.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 132 p.
  • 总页数 132
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 财政、金融;
  • 关键词

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