Inference using estimating functions with applications

通过应用程序使用估计函数进行推理

• 批准号: 356038-2008
• 负责人: Ghahramani, Melody
• 金额: $ 0.73万
• 依托单位: University of Winnipeg
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2010
• 资助国家: 加拿大
• 起止时间: 2010-01-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=459712
• 关键词: Inference; using; estimating; functions; applications

Volatility modelling has implications for asset pricing, optimal portfolio theory and risk management. Volatility or the instantaneous rate of return of the underlying security was assumed to be constant up until 1982. Ever since Robert F. Engle recognized the time-varying nature of volatility in 1982, there has been extensive research into extending his class of autoregressive conditional heteroscedastic (ARCH) models to incorporate additional salient features of financial returns data. Engle's recognition of the time-varying nature of volatility has made a significant impact in the theory of economics. However, many statistical properties of the models proposed in volatility modelling research have yet to be studied and provide a wealth of research opportunities.

波动率建模对资产定价、最优投资组合理论和风险管理具有重要意义。直到1982年，标的证券的波动性或瞬时收益率一直被假定为恒定不变。自从1982年罗伯特·F·恩格尔认识到波动性的时变性以来，人们一直在广泛地研究扩展他的自回归条件异方差(ARCH)模型，以纳入金融回报数据的额外显著特征。恩格尔对波动率时变性的认识在经济学理论中产生了重大影响。然而，波动率模型研究中提出的模型的许多统计性质尚未得到研究，并提供了丰富的研究机会。