A world that is hungry for data and quick results often grants greater value to a popular conviction of future forecasts than to the intrinsic knowledge acquired by realized adverse events. The author of this article urges us to pay history the attention it deserves.
Events such as the COVID-19 pandemic and the accompanying economic mayhem raise a lot of questions about human behavior. Already, this news service has examined behavioral finance – that framework of ideas seeking to understand why and how people manage money in the way that they do, if only to try and curb mistakes and improve composure.
This article continues in this behavioral vein and also looks at the case for “historical stress-testing” approaches to investments. The analysis comes from Yannis Sardis, PhD, who is director of Finvent Software Solutions. (More details on Finvent below.) We hope this article stimulates conversations, and invite readers to email us at email@example.com and firstname.lastname@example.org The usual editorial disclaimers apply to outside contributors’ views.
“Prediction is very difficult, especially if it is about the future” - Niels Bohr, Danish physicist, Nobel Laureate 1922.
Although N Bohr's quote was meant to address a seminar question about his prediction of the influence of quantum physics on the world in the future, it sets a base for the difficulty that theoretical and empirical sciences have in consistently relying on models of variable complexity in order to make meaningful predictions about future events. Our modern, information-thirsty and quick-results-oriented, world often assigns greater value to a popular conviction of future forecasts than to the intrinsic knowledge acquired by realized adverse events. And therein lies one of the most common reasons for collective herding behavior and cognitive fallacies.
Financial decision-making is part of a complex ecosystem that blends behavioral psychology and investment management acumen. Should decisions be consistently judged by the process by which they were derived or simply by their outcome? Although the answer relies on the definition of decision quality, it largely depends on the compatibility between the decision maker and the judge (who performs a second-order assessment).
In finance, a decision maker continuously faces various (known and unknown) risks that could drastically and speedily affect the value of a portfolio’s holdings. The day-to-day process of evaluating the portfolio’s risk exposure to normal or Black Swan market conditions cannot (and should not) be adequately covered by a single risk approach and its variations (let alone by no risk approach, as often observed in the field). Instead, a systematic decision-making process of applying a full set of risk methodologies should be applied to capture the adherence or the divergence of a portfolio's probability distribution of returns from normality.
As recent markets vividly displayed, a robust risk management framework demands the implementation of scenario simulations where the distribution is extremely skewed towards tail events, situations that happen rarely. Such shocks could be caused by various macro-economic or idiosyncratic events, which can consequently spread widely to previously thought of as uncorrelated choices of assets (systematic or undiversified risk). Examples of historical crises that resulted in large losses of invested capital within a certain period of time (varying from days to months) include the Black Monday of 1987, the Gulf War of 1990, the Asian Crisis of 1997, the Russia Devaluation of 1998, the Global Financial Crisis of 2008 and the (so far developing) Global COVID-19 Health Crisis.
Despite the fact that a large portion of such losses are often due to excessive leverage, high asset valuations and over-concentration of positions, one should seriously consider the use of the factors underling such extreme divergences from normality, to stress-test their often seemingly well-diversified multi-asset investment portfolios.
We should certainly not rely on the assumption that history repeats itself, since the background conditions, driving factors and collective investor sentiment often differ vastly between distant periods of economic and market activity. However, to assess and verify that adequate capital is preserved to cover unexpected losses, investors should attempt to estimate the impact that the re-occurrence of such damaging historical events could have on the portfolio performance.