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投资风险管理.html
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投资风险管理.html
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<!DOCTYPE html>
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<meta name="author" content="雷欧">
<title>投资风险管理</title>
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<div class="quarto-title"><h1 class="title display-7">投资风险管理</h1></div><div class="quarto-title-meta"><div><div class="quarto-title-meta-heading">Author</div><div class="quarto-title-meta-contents"><div class="quarto-title-authors"><p>雷欧</p></div></div></div></div></header>
<section id="夏普率-sharpe-ratio" class="level2">
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<section id="投资风险价值-var" class="level2">
<h2 class="anchored" data-anchor-id="投资风险价值-var">投资风险价值 (VaR)</h2>
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<h2 class="anchored" data-anchor-id="参考文献">参考文献</h2>
<ol type="1">
<li><a href="http://tecdat.cn/r%e8%af%ad%e8%a8%80%e7%94%a8garch%e6%a8%a1%e5%9e%8b%e6%b3%a2%e5%8a%a8%e7%8e%87%e5%bb%ba%e6%a8%a1%e5%92%8c%e9%a2%84%e6%b5%8b%e3%80%81%e5%9b%9e%e6%b5%8bvar%e5%88%86%e6%9e%90%e8%82%a1%e5%b8%82%e6%94%b6">R语言用GARCH模型波动率建模和预测、回测风险价值 (VAR)分析股市收益率时间序列</a></li>
<li><a href="http://tecdat.cn/r%e8%af%ad%e8%a8%80%e5%9f%ba%e4%ba%8earma-garch-var%e6%a8%a1%e5%9e%8b%e6%8b%9f%e5%90%88%e5%92%8c%e9%a2%84%e6%b5%8b%e5%ae%9e%e8%af%81%e7%a0%94%e7%a9%b6%e5%88%86%e6%9e%90%e6%a1%88%e4%be%8b">R语言基于ARMA-GARCH-VAR模型拟合和预测实证研究分析案例</a></li>
<li><a href="http://tecdat.cn/r%e8%af%ad%e8%a8%80var%e6%a8%a1%e5%9e%8b%e7%9a%84%e4%b8%8d%e5%90%8c%e7%b1%bb%e5%9e%8b%e7%9a%84%e8%84%89%e5%86%b2%e5%93%8d%e5%ba%94%e5%88%86%e6%9e%90">R语言VAR向量自回归模型的不同类型的脉冲响应分析</a></li>
<li><a href="http://tecdat.cn/r%e8%af%ad%e8%a8%80gibbs%e6%8a%bd%e6%a0%b7%e7%9a%84%e8%b4%9d%e5%8f%b6%e6%96%af%e7%ae%80%e5%8d%95%e7%ba%bf%e6%80%a7%e5%9b%9e%e5%bd%92%e4%bb%bf%e7%9c%9f%e5%88%86%e6%9e%90">R语言GIBBS抽样的贝叶斯简单线性回归仿真分析</a></li>
<li><a href="http://tecdat.cn/%e9%9a%8f%e6%9c%ba%e6%90%9c%e7%b4%a2%e5%8f%98%e9%87%8f%e9%80%89%e6%8b%a9ssvs%e4%bc%b0%e8%ae%a1%e8%b4%9d%e5%8f%b6%e6%96%af%e5%90%91%e9%87%8f%e8%87%aa%e5%9b%9e%e5%bd%92%ef%bc%88bvar%ef%bc%89%e6%a8%a1">R语言随机搜索变量选择SSVS估计贝叶斯向量自回归（BVAR）模型</a></li>
<li><a href="http://tecdat.cn/r%e8%af%ad%e8%a8%80%e4%b8%ad%e7%9a%84stan%e6%a6%82%e7%8e%87%e7%bc%96%e7%a8%8bmcmc%e9%87%87%e6%a0%b7%e7%9a%84%e8%b4%9d%e5%8f%b6%e6%96%af%e6%a8%a1%e5%9e%8b">R语言中的STAN概率编程MCMC采样的贝叶斯模型</a></li>
<li><a href="http://tecdat.cn/r%e8%af%ad%e8%a8%80%e4%bc%b0%e8%ae%a1%e6%97%b6%e5%8f%98var%e6%a8%a1%e5%9e%8b%e6%97%b6%e9%97%b4%e5%ba%8f%e5%88%97%e7%9a%84%e5%ae%9e%e8%af%81%e7%a0%94%e7%a9%b6%e5%88%86%e6%9e%90%e6%a1%88%e4%be%8b">R语言估计时变VAR模型时间序列的实证研究分析案例</a></li>
<li><a href="http://tecdat.cn/r%e8%af%ad%e8%a8%80%e4%b8%ad%e7%9a%84stan%e6%a6%82%e7%8e%87%e7%bc%96%e7%a8%8bmcmc%e9%87%87%e6%a0%b7%e7%9a%84%e8%b4%9d%e5%8f%b6%e6%96%af%e6%a8%a1%e5%9e%8b">R语言中的STAN概率编程MCMC采样的贝叶斯模型</a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
<li><a href=""></a></li>
</ol>
</section>
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