Risk and scientific socialism
February 11, 2023
The way we manage financial risk has a lot in common with the old concept of scientific socialism. The modern-day riskometer is pseudoscientific, and the increased reliance on it leads to disastrous systemic risk.
One of the things that fascinates me about the banking system is that so many of the individuals who work in it profess to believe in free markets — indeed, many view themselves as libertarians — while going about their business in a very socialistic manner, with no irony. I could talk about bailouts, but not today.
We don't hear much about scientific socialism these days, but it used to be a fairly widespread concept: a scientific blueprint for avoiding all of capitalism's worst characteristics.
Friedrich Engels created the term "scientific socialism" in his book Socialism: Utopian and Scientific in 1880, describing Karl Marx's political, economic, and social approach as "scientific socialism." In other words, the study of political, social, and economic phenomena using scientific methodologies to predict likely future results and developments.
Scientific socialism entails the development of testable hypotheses based on empirical observations; when reality does not follow the theory's predictions, ad hoc assumptions are added to the initial theory to ensure it fits the actual facts.
Karl Popper argued that scientific socialism is "pseudoscientific" in his 1945 book The Open Society and Its Enemies.
Popper contends that science is founded on testable hypotheses based on empirical observations, and that hypotheses are then altered or refuted based on actual outcomes. Because scientific socialism's assertions cannot be tested; they cannot be falsified; it is pseudoscientific.
So, what does this have to do with financial risk management?
We quantify risk using what I term a riskometer. It is a device that allows the operator to plunge it into the City of London's guts and extract a risk measurement.
For the technically minded, it combines a risk concept (such as Value-at-Risk), a probability (such as 99% daily), and a measuring approach (such as GARCH).
My contention is that, like scientific socialism, the riskometer is pseudoscientific.
However, it does not appear to be so. No, it is ostensibly an objective and scientific method of risk assessment, and by employing it, we move away from subjectivity, incompetence, and even corruption.
I can now hear the objections, like backtesting, but the answer is no, it does not solve the problem.
The basic issue is that no risk measurement can be fully validated because risk is a latent process. All we can do is validate model output against an assumption about what is important.
And we may make an infinite number of statements about what is important, most of which are contradictory.
We cannot falsify a risk forecast, according to Karl Popper, and hence it is not scientific.
So, risk models — riskometers — are no more scientific than scientific socialism.
What does this mean for riskometer practitioners?
Models and riskBloggs and appendices on artificial intelligence, financial crises, systemic risk, financial risk, models, regulations, financial policy, cryptocurrencies and related topics
© All rights reserved, Jon Danielsson,