摘要翻译:
金融计量经济学已成为一个日益热门的研究领域。在本文中,我们回顾了几个参数和非参数模型和方法在这一领域的应用。在介绍了几种常用的连续时间模型和离散时间模型的基础上,详细研究了离散样本的相关结构,包括马尔可夫性质、隐马尔可夫结构、污染观测值和随机样本。然后讨论了几种常用的参数和非参数估计方法。为了避免模型的错误描述,模型验证在财务建模中起着关键的作用。我们讨论了几种模型验证技术,包括伪似然比检验、基于非参数曲线回归的检验、基于残差的检验、广义似然比检验、同时建立置信带和基于密度的检验。最后,我们简要地谈到研究大样本性质的工具。
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英文标题:
《Parametric and nonparametric models and methods in financial
econometrics》
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作者:
Zhibiao Zhao
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最新提交年份:
2008
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类:Statistics 统计学
二级分类:Methodology 方法论
分类描述:Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计,调查,模型选择,多重检验,多元方法,信号和图像处理,时间序列,平滑,空间统计,生存分析,非参数和半参数方法
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英文摘要:
Financial econometrics has become an increasingly popular research field. In this paper we review a few parametric and nonparametric models and methods used in this area. After introducing several widely used continuous-time and discrete-time models, we study in detail dependence structures of discrete samples, including Markovian property, hidden Markovian structure, contaminated observations, and random samples. We then discuss several popular parametric and nonparametric estimation methods. To avoid model mis-specification, model validation plays a key role in financial modeling. We discuss several model validation techniques, including pseudo-likelihood ratio test, nonparametric curve regression based test, residuals based test, generalized likelihood ratio test, simultaneous confidence band construction, and density based test. Finally, we briefly touch on tools for studying large sample properties.
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PDF链接:
https://arxiv.org/pdf/0801.1599