英文标题：
《Conditional-Mean Hedging Under Transaction Costs in Gaussian Models》
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作者：
Tommi Sottinen and Lauri Viitasaari
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最新提交年份：
2017
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英文摘要：
We consider so-called regular invertible Gaussian Volterra processes and derive a formula for their prediction laws. Examples of such processes include the fractional Brownian motions and the mixed fractional Brownian motions. As an application, we consider conditional-mean hedging under transaction costs in Black-Scholes type pricing models where the Brownian motion is replaced with a more general regular invertible Gaussian Volterra process.
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中文摘要：
我们考虑了所谓的正则可逆高斯Volterra过程，并推导了其预测规律的公式。这类过程的例子包括分数布朗运动和混合分数布朗运动。作为一个应用，我们在Black-Scholes型定价模型中考虑了交易成本下的条件平均套期保值，其中布朗运动被更一般的正则可逆高斯-Volterra过程所取代。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Mathematical Finance 数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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一级分类：Mathematics 数学
二级分类：Probability 概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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