Probabilistic valuation methods migrated from actuarial science into financial markets via Gaussian risk models

Evidence

The second valuation method used in finance is probability-based statistics. Statistics were used in the 19th century by insurers to estimate the probabilities of accident or death based on observed past frequencies, but remained confined to the world of actuaries. It was only later that they arrived in the world of finance, through the work of researchers trying to predict stock exchange movements (Walter 1996, 1999). Fluctuations in prices on the markets, and the occasionally high volatility even within a single day, were incompatible with the idea that prices necessarily have some objective foundation, and can be predicted. One ”solution” to this problem has been to consider it possible to describe stock market prices using mathematical expectations and volatility (standard deviation). This hypothesis then became generalised and is now used to construct models assuming that value generally follows a probabilistic law that is principally describable by the mean and standard deviation (as in a Gaussian distribution). This conceptualisation was then introduced into all management and valuation models, and every financial valuation now assumes that the two criteria of risk and return will be taken into consideration. — Ève Chiapello, Financialisation of Valuation, 33

Categorization

• XREF: This migration of actuarial statistics into all valuation models connects to the reader’s interest in how financialized valuation colonizes non-financial activity — the same Gaussian probabilistic frame now underwrites every investment appraisal. — connects to: Under a Gaussian distribution extreme tail events become effectively impossible — Mark Blyth, Austerity: The History of a Dangerous…, 106; The bell-curve shape of Gaussian distributions is what banks’ risk models assume; Option pricing theory developed as Kuhn-style normal science elaborating the random-walk model — Donald MacKenzie, An Engine, Not a Camera: How Financial…, 532 (+3 more)

Related

• The bell-curve shape of Gaussian distributions is what banks’ risk models assume (similarity 0.90)
• Financialization treats risk as probabilisable, displacing close knowledge of the object valued (similarity 0.83)
• Value-at-risk quantifies portfolio exposure through estimated loss probabilities. (similarity 0.81)
• Accounting’s fair-value shift substitutes financial models for actual market prices (similarity 0.81)
• Finance derives prices for new objects from unrelated market prices (similarity 0.78)
• Financialised valuation draws on financial economics and mathematical finance. (similarity 0.78)

Broader Connections

• Value-at-risk quantifies portfolio exposure through estimated loss probabilities. #exemplifies (0.80) — Donald MacKenzie, An Engine, Not a Camera, 995
• Option pricing theory developed as Kuhn-style normal science elaborating the random-walk model #expands (0.78) — Donald MacKenzie, An Engine, Not a Camera, 532
• Credit-risk regulation imports market-finance models developed for traded securities. #expands (0.75) — Ève Chiapello, Financialisation of Valuation, 60