Financial modelling in an HMM-modulated regime-switching framework

该研究方案的中心主题是金融建模中的制度转换框架。状态的切换由代表“世界状态”的连续时间或离散时间隐马尔可夫链控制。研究了隐马尔可夫模型的新的实际应用和进一步的理论发展。首先，将HMM滤波理论扩展到处理时间序列数据的长范围依赖，说明HMM中的马尔可夫假设并不像它最初出现的那样具有限制性。这导致弱hmm驱动模型参数的随机演化，从而捕获状态切换和记忆特性。其次，将卡尔曼滤波等非线性滤波技术与最优HMM滤波理论相结合，在非线性时间序列中对金融变量等现象的参数估计和建模产生自适应的高性能算法。第三，设计了有效评估年金相关合同和死亡率相关证券的方法，其中金融和人口因素的动态假设是相关的，利率和死亡率都是hmm调节的。第四，考虑了基于hmm的期权定价和债券估值模型的时变参数恢复问题。金融中的这个逆问题可以通过使用一种分析方法来解决，也可以通过将其重新表述为数学分析中的逆斯蒂尔茨矩问题的推广来解决。在某些情况下，例如在债券定价中，将构建生成函数，它可以被视为债券价格解的一个组成部分的转换。虽然所有这些调查都与定量金融和精算科学直接相关，但包括经济学、工程学和应用科学的其他分支在内的其他应用领域也可以从这项研究计划的结果中积极受益。

This research programme centres on the theme of regime-switching frameworks in financial modelling. The switching of regimes is governed by either a continuous- or discrete-time hidden Markov chain representing the "state of the world". New practical applications and further theoretical developments of hidden Markov models (HMM) are investigated. First, HMM filtering theory is extended to deal with the long range dependence of time series data illustrating that the Markovian assumption in HMM is not as restrictive as it first appears. This gives rise to weak HMMs driving the stochastic evolution of model parameters thereby capturing both regime-switching and memory properties. Second, Kalman filtering and other non-linear filtering techniques are coupled with optimal HMM filtering theory to produce adaptive and high performance algorithms in the parameter estimation and modelling of financial variables and other phenomena in nonlinear time series. Third, methodologies are devised for efficient valuation of annuity-linked contracts and mortality-linked securities where the dynamics of both financial and demographic factors are assumed correlated, and both interest and mortality rates are HMM-modulated. Fourth, the recovery of time-varying parameters for HMM-based models in option pricing and bond valuation is considered. This inverse problem in finance may be addressed either by using an ansatz approach or by reformulating it as a generalisation of the inverse Stieltjes moment problem of mathematical analysis. In some cases such as in bond pricing, generating functions, which can be viewed as a transform of one of the components of the bond price solution, will be constructed. Whilst all of these investigations have direct relevance to quantitative finance and actuarial science, other fields of applications including economics, engineering and other branches of applied sciences could also positively benefit from the results of this research programme.