摘要翻译：
本文研究了从历史数据中估计扩散市场模型参数的问题。这些模型隐含波动率的标准定义将其价值表示为包括无风险利率在内的几个参数的隐函数。在现实中，由于期权价格依赖于其未来曲线，无风险利率是未知的，需要对其进行预测。因此，标准隐含波动率是有条件的：它取决于无风险利率的未来值。我们研究了两个隐含参数：隐含波动率和隐含平均累积无风险利率。它们可以无条件地从两个方程组中找到。我们发现具有随机挥发度的非常简单的模型（例如，具有两点分布）用这种方法会产生各种波动微笑和倾斜。
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英文标题：
《Two unconditionally implied parameters and volatility smiles and skews》
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作者：
Nikolai Dokuchaev
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最新提交年份：
2013
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Pricing of Securities        证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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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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英文摘要：
  The paper studies estimation of parameters of diffusion market models from historical data. The standard definition of implied volatility for these models presents its value as an implicit function of several parameters, including the risk-free interest rate. In reality, the risk free interest rate is unknown and need to be forecasted, because the option price depends on its future curve. Therefore, the standard implied volatility is {\it conditional}: it depends on the future values of the risk free rate. We study two implied parameters: the implied volatility and the implied average cumulative risk free interest rate. They can be found unconditionally from a system of two equations. We found that very simple models with random volatilities (for instance, with two point distributions) generate various volatility smiles and skews with this approach.
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PDF链接：
https://arxiv.org/pdf/1303.4847