State-of-the-Art Measurement and 'Early Warning' of Critical Transitions in Financial Markets

复杂系统的特征之一是存在临界转变（“临界点”），这些临界转变将系统行为的相对稳定区域分开。在各种系统中都观察到了这种转变，从冰和液态水等不同物质状态之间的相变到生态系统、国际经济和全球气候的变化。在这个跨学科的项目中，我们将研究金融市场以及金融泡沫和崩溃的出现。这是由交易员的从众心理驱动的，是突然的，但并非完全出乎意料。与此同时，虽然知情的参与者可以观察到泡沫的形成和出现，但由于复杂的非线性相互作用和市场参与者在泡沫存在时的行为变化，预测崩溃-临界点-并非微不足道。通过与为机构客户提供风险服务（风险建模，咨询和管理）的行业合作伙伴合作，我们的目标是了解管理金融市场所代表的复杂系统的关键机制以及其行为中政权变化的可能性。为了实现我们的目标，我们将使用统计物理学开发的模型和工具，例如为描述地震活动而创建的模型，并构建这些模型的新扩展，以解释金融市场中存在的典型反馈机制;在此过程中，我们的目标是开发金融制度和过渡的新特征和测量。这项工作将直接为我们的行业合作伙伴开发的下一代早期预警风险系统提供信息：例如，养老金行业和资产顾问使用此类系统来保护资本。它还将产生适用于更广泛类别的自然复杂系统及其关键过渡的模型（或其分析方法）。

One of the characteristic features of complex systems is the existence of critical transitions ("tipping points") that separate relatively stable regions of system behaviour. Such transitions have been observed in a variety of systems, from phase transitions between different states of matter, such as ice and liquid water, to changes in ecosystems, international economy and global climate. In this interdisciplinary project, we will study financial markets and the emergence of financial bubbles and crashes. These are driven by traders' herd mentality and are sudden but not wholly unexpected. At the same time, while informed participants can observe the build-up and emergence of bubbles, prediction of crashes - the tipping points - is non-trivial due to complex nonlinear interactions and the change in behaviour of market participants if the existence of a bubble becomes known. In collaboration with an industrial partner providing risk services (risk modelling, consulting, and management) to institutional clients, we aim to understand the crucial mechanisms that govern the class of complex systems represented by financial markets and the likelihood of regime changes in their behaviour. In order to achieve our objective, we will use the models and tools developed by statistical physics such as the models created to describe seismic activity and build novel extensions of these to account for the typical feedback mechanisms present in financial markets; in doing so, we aim to develop new characterisations and measurements of financial regimes and transitions. This work will directly inform the next generation of early warning risk systems developed by our industrial partner: such systems are used, for example, by the pensions industry and asset advisors to protect capital. It will also result in models (or methods of their analysis) that are applicable to broader classes of natural complex systems and their critical transitions.