针对现有衍生品定价研究对离散时间模型关注不足、数据频率偏低且信息源单一的现状，本项目结合近年来波动建模及隐含信息提取方面的最新成果，研究基于已实现测度和隐含信息期限结构定价衍生品的理论与应用问题。本项目通过对已实现测度、动态高阶矩和隐含信息期限结构的建模研究，为代表性衍生品给出经实证检验的定价方法。研究的主要内容包括：基于已实现信息建模波动率和高阶矩的方法；风险中性化与建模隐含信息期限结构的方法；结合隐含信息估计模型参数并为期权及波动衍生品定价的方法；基于市场数据对模型统计意义和经济价值进行评价等。与以往研究不同，本项目从已实现测度与隐含信息期限结构相结合的角度，使用统一的模型框架充分发掘历史数据和风险中性数据对参数估计与定价提供的信息。除为衍生品定价提供新的方法外，本项目对提高已实现测度和隐含信息建模能力等有重要意义。相关结果将为我国快速发展的衍生品市场的定价和信息提取提供技术基础。

The current literature on derivative pricing pays less attention to discrete time models. Data they used are relatively low frequency with limited information source. This project, based on new developments on volatility modeling and implied information extraction, will investigates the theoretical and practical issues on pricing derivatives with realized measures as well as the term structure of implied information. This project aims to provide empirically tested pricing method for representative derivatives based on the modelling research on realized measures, dynamic higher moments and the term structure of implied information. Main research topics are: modelling volatility and higher moments with realized measures, risk neutralization and modelling technique of the term structure of implied information, parameter estimation based on implied information and the pricing method for options as well as volatility derivatives, evaluating model’s statistic and economic value using real market data. Unlike previous researches, through the angle of combination of realized measures and the term structure of implied information with a unified framework, this project investigates the information provided in estimation and pricing issues by extract historical as well as implied information. Other than provides new pricing methods, this project will also enhance our modeling ability of realized measures and implied information. Results also provide technical support on pricing and information extraction to China’s fast developing derivative markets.