There are common pathways in the transmission of viruses and volatility. Volatility, like infectious disease, is transmitted through common sources of infection. Sources of volatility transmission include investor psychology, market contagion, and liquidity pressures. The science of epidemiology, the Kermack-McKendrick SIR Model (1927) and “Reproduction Ratio” are useful mechanisms to examine market contagion and volatility spikes – both UP and down.
Most quantitative risk models fail to detect regime changes. Because quant alpha and risk models rely heavily on historical data, off-the-shelf risk models are unable to rapidly respond to exogenous epochs like novel coronavirus (COVID-19). This presentation will discuss these issues. It will further demonstrate how asset managers are using Machine Learning to uncover correlated sources of risk and classify and monetize differentiated sources of potential alpha in ways that quantitative risk models cannot handle.