英文标题：
《Parameter estimation for stable distributions with application to
commodity futures log returns》
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作者：
Michael Kateregga, Sure Mataramvura and David Taylor
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最新提交年份：
2017
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英文摘要：
This paper explores the theory behind the rich and robust family of {\\alpha}-stable distributions to estimate parameters from financial asset log-returns data. We discuss four-parameter estimation methods including the quantiles, logarithmic moments method, maximum likelihood (ML), and the empirical characteristics function (ECF) method. The contribution of the paper is two-fold: first, we discuss the above parametric approaches and investigate their performance through error analysis. Moreover, we argue that the ECF performs better than the ML over a wide range of shape parameter values, {\\alpha}{\\alpha} including values closest to 0 and 2 and that the ECF has a better convergence rate than the ML. Secondly, we compare the t location-scale distribution to the general stable distribution and show that the former fails to capture skewness which might exist in the data. This is observed through applying the ECF to commodity futures log-returns data to obtain the skewness parameter.
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中文摘要：
本文探讨了{\\alpha}稳定分布的丰富和稳健族背后的理论，以从金融资产对数收益数据估计参数。我们讨论了四种参数估计方法，包括分位数法、对数矩法、最大似然法和经验特征函数法。本文的贡献有两个方面：首先，我们讨论了上述参数化方法，并通过误差分析研究了它们的性能。此外，我们认为ECF在很大范围内的形状参数值{\\alpha}{\\alpha}上的性能优于ML，包括最接近0和2的值，并且ECF比ML具有更好的收敛速度。其次，我们将t位置尺度分布与一般稳定分布进行比较，表明前者无法捕获数据中可能存在的偏斜。这是通过将ECF应用于商品期货日志收益数据以获得偏度参数来观察到的。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Economics 经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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