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title => 沈雁：中国期货期权市场中的实用波动率模型,
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body => <h1 style="text-align: center;"><strong>中国期货期权市场中的实用波动率模型</strong></h1>
<p style="text-align: center;">沈雁 衍生品交易和风险管理国际资深专家</p>
<p style="text-align: center;"> </p>
<p style="text-indent: 2em;">在全球来讲，商品期货衍生品相对于固收、汇率这两个比较大的品种以外，是小众的产品，在国内更是如此，并且其也存在一些典型的问题。此外，商品期货的交易规模比较小，但是每天的交易量很大，而且在国内没有t+1的限制，所以对喜欢交易的同仁来说是一个不错的选择。目前国内大概有将近70个期货品种，关键是其中有23个品种都有相应的场内期权。</p>
<p style="text-indent: 2em;"> </p>
<h2><strong>一、中国的商品期货市场中典型问题</strong></h2>
<h4 style="text-indent: 1.5em;"><strong>（一）前台问题</strong></h4>
<p style="text-indent: 2em;">在这方面相关工作中，我发现前中后台风险管理都存在比较多的问题。在这23个品种当中，目前国内市场无风险套利的机会是比较多的，但是我们面临着一些困难。由于简单粗暴使用Black-Scholes对波动率进行研究，远端Greeks误差导致慢性流血。期货市场产品相对简单，期限较短，成也是期限，败也是期限，因为期限的限制导致了期货的产品难以做到长期，很达到一些投资机构的此类需求。因此使用Black-Scholes确定波动率够用，但是还存在挑战。</p>
<p style="text-indent: 2em;">第二，对交易误差缺乏量化手段会导致报价的误差，经常遇到的是第一个报价如何去做的问题。凡是具有间歇性的市场，都会导致期权基本上不可能如同理论所说，总是具有一定的联动性，因此大家在Black-Scholes的使用上具有很多的盲区，在进行第一个报价的时候应该用计算机实现，首先确定交易策略、调整的时机、路径的选择等等。任何对冲的结果都是和路径有关系的，尽管我的定价跟路径一点关系没有，但是对冲结果一定是路径的函数。交易员最大的目的就是不亏钱，只要能够保证不亏钱，你就算是完成任务了，如果这个过程中还能赚钱的话，那完全是属于运气。。量化手段在国内甚至在国外使用比例不高，计算机信息系统科技的能力是比较大的挑战，首先是我确定交易策略，然后可以通过运算不同的路径得出可能的交易结果，更重要的是在这个过程中，可以考虑交易成本。因此必须在此系统里面实现量化，国内这方面的能力极其缺乏，而且能够真正做到主控的更是凤毛麟角，另外很多盲目的动态对冲会造成不必要的交易成本。这些金融工程相关的方面，大家都是只限于理论上的理解，很多人没见过真实的交易情况。因此更需要通过系统来实现，人工操作会导致很多的错误判断。因为这些客观的原因，国内的金融工程还提不到议事日程上来，和国外的做法具有一定差距。国外的系统金融工程也不一定是唯一的做法。我希望交易员能够明白，系统金融工程就后面的原理是什么和用什么样的模型来做，因为任何一个模型都有致命的弱点。</p>
<h4 style="text-indent: 1.5em;"><strong>（二）中后台问题</strong></h4>
<p style="text-indent: 2em;">不仅前台的挑战很多，中后台也有一些困难的方面。归根到底是交易员对非线性的盈亏缺乏理解。期货市场里面大部分人对线性期货比较了解，对于任何非线性的产品都是非常陌生的，对行业内的人不仅要讲简单的期权，还要让他们对其有足够深的理解，才能对行业发展有比较好的帮助。同时交易员必须理解模型、系统背后的原理，以及它们是如何运行的。</p>
<p style="text-indent: 2em;">因为效率的低下，导致了人员流动性很大的现象，尤其是在中后台的工作员工难以忍受，最后去找了更容易的事做。再者因为期货市场上，薪酬机制不如券商、银行，所以很难有比较好的人才能够进入到这个行业，这是期货行业面临的一个比较大的问题。人才方面无法和券商和银行竞争，但是需要的技能各方面都是有比较大的相似性、本质性。还有就是和IT团队的沟通，因为IT团队对这类业务较为陌生，我甚至怀疑他们做出相关系统的可能性。在很多情况下，都是我自己写系统，从前台的定价到实时的系统，然后结算相关的指标，分析参数。另外风控方面，因为场外交易总有交易对手的问题，而交易对手就有保证金的问题，并且保证金系统是风控做不出来的，最后还是由我们结合前台的要求进行完成。风控很难独立去确认方法以及提出更先进的方法。这些实际情况导致了更高沟通成本的产生。<br />
要解决这些问题，还是需要较好的信息化管理系统。在期货这个行业，计算机取代交易员的可能性是非常大的。其实我们在很多的场外交易中已经实现了完全的自动化，比如根据伽马的方向，策略自动进行调节。但是目前这类系统发展还处于国内行业内比较低端的水平。问题的存在本身也是机会，市场上有很多套利的机会，从交易的角度来说是不错的。我们现在在做基金，该基金是机器进行量化的，从价格到发现到执行完全自动化。对我个人来说这是一个比较大的挑战，对于国内从某种程度上来说，这是未来的一个方向。对于场外方面，我鼓励交易员在有机会的时候——特别是在波动率出现很大倾斜时，可以先做自营，这样才能够保证当我的客户来的时候，可以报出很好的价格，这样在报价方面就会有优势。在保持风险中性下在波动率方面深入来获得具有优势的报价。</p>
<p style="text-indent: 2em;"> </p>
<h2><strong>二、在波动率微笑中静态对冲奇异期权</strong></h2>
<p style="text-indent: 2em;">关于波动率，任何模型都有致命的弱点。波动率归根到底是一个概率，这些模型都是通过物理的方式来描述波动率的形状变化，来表明是否好像是跟市场更加的接近。在这个过程当中，在互动力smile skill很强的情况下，有没有一种方法使得很奇异的期权可以静态对冲，以减轻交易成本。在奇异期权对数正态分布下，可以通过理论推导出一系列的公式，归根到底之所以出现功能的交易形状，就是一个分布函数的问题。那么对于分布函数的问题，宁肯是看分布函数。一个很重要的问题就是说，在对数正态的时候是有期权的对称性，如果你risk reverse的结构，就是买卖货品时中间会有一个点，这个点就是它的价值，不管是任何时间，任何波动率，它的价值总是固定，这是期权的对称性。在有了这个前提以后，很多奇异性期权就可以静态的复制，静态复制是指奇异的期权可以用一组香草型的期权来复制。理论上如此，但是对数正态根本是和实际相差甚远的。 </p>
<p style="text-indent: 2em;">很重要一点就是在我的文章里面证明波动率模型下存在风险的对称原理，以及平值期权点是怎么决定的。有了这个模型后，完全就形成了一个静态对冲，即我做了一个很奇异的期权以后，在市场上再找一些场内接近的香草型期权，基本上可以把风险大部分都给你对冲的，因为我的行权价格在场内挂架的时候都是固定的，可能不一定到精准带小数的状态。从实际的角度来说，风险通过这种复制，可以把原来很多非线性的东西克服八到九成。如果一碰到二元就亏钱，这种头寸用这个来复制以后，其实会发现所有的滑点在这个复制里面甚至可以变成盈利。当期权期限稍微较长的时候，它的波动率优势相对来说是平衡的，程度要比快到期的时候波动率的倾斜，越到期的时候波动率越厉害，这个是很正常的，但是很重要的是它会出现不同的倾斜的角度，模型对称原理照样成立，所以我叫它静态对冲。另外不管期限、平值期的波动率如何变化，风险翻转的结构在点上价值永远不变，这是使得整个静态复制的最终成立的一个理论基础。整个系统基本上由计算机实现，但是如果波动率脱落率的倾斜发生，这个模型就会有一定的弱点。</p>
<p style="text-align: right;">（责任编辑：郭钰阳）</p>
<p style="text-align: right;">来源：TGES2021高级研讨会：金融市场业务与风险管理（8月）</p>
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