A quantitative and qualitative investment decision making framework
for minimising risk and uncertainty: Institutional Investors coming to
grips with a highly complex interrelated investment world
Dr Carol Royal and Bruce Garvey
UNSW Business School, University of New South Wales, Sydney, Australia
Dyson School of Design Engineering, Imperial College, London

Abstract: Ernest Rutherford, the Nobel Prize winning physicist claimed: “Qualitative is nothing but poor quantitative.” This 100 year-old dictum unfortunately still castes a long shadow in relation to the qualitative/quantitative divide present in the analytical process and subsequent decision-making. Recent dramatic increases in computing power including big data analytics, have supported the view that quantitative is best. Much financial analysis has concentrated on risk, whereby probabilistic methods can allow decision makers to make decisions based on a belief that quantitative, and therefore measurable indicators, validate such decisions. The appearance of precision through quantification, mathematics, and printouts often conveys a validity that  is not justified. But how do institutional investors treat uncertainty, a situation where there is little or no measurable data and where the decision environment is not only rapidly changing but rapidly and randomly evolving in terms of its structure? Investment managers have complained recently not so much about the volatility of the markets, but about uncertainty. Rules of thumb do not work anymore, correlations no longer hold, or worse, sometimes they hold and sometimes not. Mathematicians such as Rene Thom the founder of “catastrophe theory” think differently, being convinced that the qualitative is a great deal more than just a mediocre form of the quantitative. When confronted by uncertainty, this paper proposes a framework which enables oth quantitative and qualitative factors to be integrated into, if not more accurate, then more meaningful and consistent forecasts. When qualitative data issued side by side with quantitative analysis, institutional investors have access to more valid and more powerful information on current and potential future financial performance. This framework, applying iterative monitoring of earlier forecasts and judgments, has the virtue of being both more flexible and dynamic, helping institutional investors to mitigate uncertainty and risk.

Keywords: Human Capital Analysis, Qualitative Analysis, Quantitative Analysis, Investment Risk.