英文标题：
《Entropy Analysis of Financial Time Series》
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作者：
Stephan Schwill
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最新提交年份：
2018
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英文摘要：
  This thesis applies entropy as a model independent measure to address three research questions concerning financial time series. In the first study we apply transfer entropy to drawdowns and drawups in foreign exchange rates, to study their correlation and cross correlation. When applied to daily and hourly EUR/USD and GBP/USD exchange rates, we find evidence of dependence among the largest draws (i.e. 5% and 95% quantiles), but not as strong as the correlation between the daily returns of the same pair of FX rates. In the second study we use state space models (Hidden Markov Models) of volatility to investigate volatility spill overs between exchange rates. Among the currency pairs, the co-movement of EUR/USD and CHF/USD volatility states show the strongest observed relationship. With the use of transfer entropy, we find evidence for information flows between the volatility state series of AUD, CAD and BRL. The third study uses the entropy of S&P realised volatility in detecting changes of volatility regime in order to re-examine the theme of market volatility timing of hedge funds. A one-factor model is used, conditioned on information about the entropy of market volatility, to measure the dynamic of hedge funds equity exposure. On a cross section of around 2500 hedge funds with a focus on the US equity markets we find that, over the period from 2000 to 2014, hedge funds adjust their exposure dynamically in response to changes in volatility regime. This adds to the literature on the volatility timing behaviour of hedge fund manager, but using entropy as a model independent measure of volatility regime.
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中文摘要：
本文将熵作为一种与模型无关的度量方法来解决金融时间序列的三个研究问题。在第一项研究中，我们将转移熵应用于汇率的提取和提取，以研究其相关性和互相关。当应用于每日和每小时欧元/美元和英镑/美元汇率时，我们发现最大提款之间存在相关性（即5%和95%分位数），但没有同一对外汇汇率的每日收益之间的相关性强。在第二项研究中，我们使用波动的状态空间模型（隐马尔可夫模型）来研究汇率之间的波动溢出。在货币对中，欧元/美元和瑞士法郎/美元波动状态的共同运动显示出最强的观察关系。利用转移熵，我们发现AUD、CAD和BRL波动状态序列之间存在信息流的证据。第三项研究使用标准普尔实际波动率的熵来检测波动率制度的变化，以重新审视对冲基金市场波动时机的主题。采用单因素模型，以市场波动熵为条件，衡量对冲基金股票敞口的动态。在以美国股市为重点的约2500只对冲基金的横截面图上，我们发现，在2000年至2014年期间，对冲基金动态调整其风险敞口，以应对波动机制的变化。这补充了有关对冲基金经理波动性择时行为的文献，但使用熵作为波动性机制的模型独立度量。
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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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