历史波动率

其次，通过对比RBF网络模型与B-S模型、BP模型，发现不论是使用历史波动率还是隐含波动率，RBF网络模型都要优于B-S模型、BP模型。

Secondly , comparing RBF network models and B-S model , BP model , no matter using historical volatility or implied volatility , RBF network models are superior to B-S model and BP model .

首先，我们采用ME、MSE、MAE和MRE四种误差指标对分别使用历史波动率和隐含波动率的基于四种RBF网络算法的定价模型进行评价。

Firstly , we use ME , MSE , MAE and MRE to evaluate the pricing models based on four RBF network algorithms which use historical volatility and implied volatility .

波动率是B-S公式中唯一不能直接观察到的变量，一般通过历史波动率或隐含波动率求取。

Volatility of B-S formula can not be directly observed , through the general history of volatility or implied volatility strike .

通过算法参数和仿真结果的比较发现，利用隐含波动率的RBF网络模型要优于利用历史波动率的RBF网络模型，且前者所选取的神经元个数要多于后者所选取的。

By comparison of algorithm parameters and simulation results , we find that the RBF neural network model with implied volatility is superior to the RBF neural network model with historical volatility . The number of neurons of the latter is less than the former .

在定价过程，同时对历史波动率、隐含波动率、GARCH（1,1）模型下的波动率三种波动率进行了区分，并分别应用于定价模型中比较定价结果。

When we use the three models to price them , we also distinguish volatility as history volatility , implied volatility and volatility in GARCH ( 1,1 ), and use all of them in each pricing model for comparison .

并发现基于时变波动率的统计套利策略要优于基于历史波动率的统计套利策略。

And based on time-varying volatility statistical arbitrage strategy is superior to statistical arbitrage strategies based on historical volatility .

使用每日波动率代替传统中为常数的历史波动率，利用蒙特卡罗模拟结构性存款中期权部分的价格。

Instead of the constant historical volatility , we use daily volatility for Monte Carlo simulation to price the options part of the product .

本文选择股票市场主要指数的历史波动率代表市场风险，研究了不同参数的移动平均指标的年均收益率的均值序列与年均收益率的方差序列与该市场风险的相关性。

The linear correlation coefficient of the indicators ' return series , the standard deviation series of the indicators ' return and the historical volatility of stock indexes is also studied in this thesis .

此外，本章还介绍了权证波动率的估计方法，包括历史波动率、隐含波动率和已实现波动率。

S model can be used to solve the whole warrants pricing of the SSE & SZSE ; More ever , this chapter also gives an introduction of the estimation methods of volatility , including historical volatility , implied volatility and realized volatility .