05 February 2023

SUERF's Roldan: A scientific illusion in risk management?

Risk management models failed in both cases of an endogenous shock (the GFC) and an exogenous shock (the pandemic, coming from outside the perimeter of the economy and the financial system).

In approximately a decade, financial systems have been subject to two extreme shocks of a very different nature: the Global Financial Crisis and the Covid shock. Whilst the first failure was widely recognised and led to widespread regulatory reviews, the second failure has gone unnoticed, the reason for this being that financial operators fared much better than what models would foresee (models overestimated risks). Modern risk management tools are essential for effective risk control in financial firms, but they are not a silver bullet. We need to recognise this and embrace a holistic approach combining expert judgement, a faster review of assessments and policy responses (as we learn by experience) and, why not, a greater use of intuition.

Introduction

When I was a young economist in the Research Department of the Bank of Spain, working mostly as an applied macroeconomist, a research paper written by Larry Summers made an impression on me. It was called “The Scientific Illusion in Empirical Macroconomics”.1 Not sure anymore where this article sits in the literature (whether it has lost relevance) or whether his author still stands by it. But the conclusions were very clear: the abstract states that “It is argued that formal econometric work, where elaborate technique is used to apply theory to data or isolate the direction of causal relationships when they are not obvious a priori, virtually always fails. The only empirical research that has contributed to thinking about substantive issues and the development of economics is pragmatic empirical work, based on methodological principles directly opposed to those that have become fashionable in recent years”. I tried since then to be more modest in my research approaches, and most probably failed!

But the quest for the right tone in applied economic research remains elusive. The technological progress, the widespread use of computers, the increase in capabilities of analysing more data, etc., is not helping the pursuit for a sensible strategy in the search for pragmatism. And despite the frequent shocks that have shown the limits of modelling, the overengineering trend continues. For sure, modelling, use of more data, hardware being more capable of dealing with sheer volumes of information, etc., all that is a net positive. But, yet again, the key issue is the risks of overreliance.

The field of finance seemed immune to the scepticism that was widespread in the macro field. The use of daily, even hourly or real time statistical data, seemed to guarantee the analysis was sounder than in the macro field. But then came the Global Financial Crisis, breaking historical correlations within hours. And, of course, models didn´t survive the shock untarnished.

The GFC shock, of an endogenous nature, was followed in less than a decade by the Covid shock, an exogenous shock orthogonal to the functioning of the economy or to the financial sector. In the following lines we will reflect on what the Covid shock has done to risk management models in the field of finance, and whether we are ignoring the challenges posed by the emergence of orthogonal exogenous shocks (such as Covid 19, but also the Russian invasion of Ukraine).

The Covid 19 shock

Now that the pandemic is petering out with an O(micron) bang, it is time to look back, but also to look forward. Looking back, we are mesmerised how we have been able to survive not just the pandemic, the lockdowns, but the enormous impact it had on variables like employment and GDP growth. In fact, I do recall the panic I felt when the first US unemployment rate statistics came out: that vertical line was something we have never witnessed. Literally....

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