The financial crisis that caught the world by surprise has left economists searching for causes and rethinking economic models. The EU-funded project HETEROVOL (Heterogeneity and the volatility of financial assets) proposed a new approach for analysing the volatility of financial assets. It looked at creating a novel framework for modelling heterogeneity in economics – i.e. variation across individual units of observations – in order to further analyse volatility. To achieve its aims the interdisciplinary project team identified specific stochastic processes used in mathematical biology that can also be used to study genetic heterogeneity of a population. It then developed a new micro-founded stochastic volatility model that is capable of overcoming limitations of current models. The project successfully combined finance, economics and mathematics to create a new approach for modelling heterogeneity in economics. More specifically, the research involved comprehensive studies on measure-valued processes and their application in economics, particularly in asset pricing. This supported the emergence of the new approach, which was effective in analysing how heterogeneity evolved and what impact it had on asset prices. The methodology integrates aspects such as future consumption, risk attributes and changing beliefs that drive the economy. While traditional economic models for stochastic processes have been satisfactory where a small number of agents interact in the economy, the new methodology is better at handling multiple agents and variables. A key paper published by the project paves the way for future research on capturing heterogeneity in the economy. The topic involved developing and proposing a mechanism that supports more accurate macroeconomic policy decisions. In a second paper, HETEROVOL also analysed how heterogeneity impacted the volatility of financial assets in the context of continuous time stochastic volatility models. The new model focuses on pricing European-style financial options, with asset prices determined from micro-foundations that were derived from an equilibrium perspective. Importantly, this new non-affine model outperforms other existing models, both affine and non-affine ones. The project’s results were also disseminated through seminars, conferences, presentations and papers. Stakeholders from financial institutions and academics in the field of quantitative finance will no doubt find the new papers and approaches insightful.
Volatility of financial assets, economic models, HETEROVOL, heterogeneity, stochastic processes