ergoeconWe are hiring!

Applications are open for two new research positions in Ergodicity Economics. For further details and to apply, please click here.


LML Fellows Ole Peters (PI) @ole_b_peters, Alex Adamou @alex_adamou, Yonatan Berman @bermanjoe, Colm Connaughton @CPCannaughton, Oliver Hulme @hulme_oliver, and their collaborators contribute to LML’s economics programme.


The project is a full re-write of economic theory, taking account of the ergodicity question: are averages over time identical to expectation values (averages across the stochastic ensemble)? This is effective because the foundations of economic theory were laid at a time when our formal understanding of randomness was in its infancy and conceptually naïve. Yet the key formal models of human behavior used in economics are models of decision-making under randomness. These themes are explored through the EE portal.

Accessible 15-minute introduction (from 2011):

Science-history background

  • Economics was the first discipline to develop the mathematics of randomness (17th century).
  • The early conceptualisation of randomness has a flaw: it assumes that randomness playing out over time has the same effect as randomness playing out over an ensemble of parallel systems (parallel universes). In modern terms, it assumes ergodicity.
  • Economics noticed symptoms that arise from this flaw and designed tools, most notably utility theory (18th century), that mitigate some of them.
  • In the 19th century a new conceptualisation of randomness emerged in the context of physics, namely in thermodynamics and statistical mechanics. This conceptualisation recognises from the start the central role of time and makes the ergodicity problem explicit. It thereby resolves the fundamental flaw, rather than treating its symptoms.

Time line of the project
2011: Peters provides a solution of the leverage optimisation problem in finance [1]. He also publishes a solution of the 300-year-old St. Petersburg paradox [2], a key problem in the foundations of both economics and probability theory.

2013: Peters and Adamou [4] extend the work on leverage optimisation [1] to test a prediction it makes about the nature of fluctuations in stock prices. This produces a solution of the Equity Premium Puzzle and suggests an algorithm for setting central bank interest rates.

2015: Following a suggestion from economics Nobel Laureate Ken Arrow, Peters and Adamou [7] publish a solution of the insurance puzzle: why do people buy insurance although the transaction reduces their expected wealth? By extension this explains, and helps price, financial derivatives. In the same year they publish a solution of the cooperation conundrum: why would one entity voluntarily give up resources for the benefit of another, but without immediate benefit for itself [6]?

2016: Peters and physics Nobel Laureate Murray Gell-Mann [8] publish a detailed solution of the gamble-selection problem, which is the foundation of economic decision theory.

Adamou and Peters [9] point out that the techniques and concepts developed in this context lead to deep insights into the dynamics of economic inequality. Berman, Peters, and Adamou [10] published a detailed study of American wealth distributions.

2017: Rick Bookstaber argues in his book “The end of Theory” that the ergodicity problem severely limits the usefulness of mainstream economic theory.

2018: A generalization of the results presented by Peters and Gell-Mann [8] is published [11]. This clarifies how the emerging framework is related to classical expected utility theory (EUT). It removes the arbitrariness associated with EUT due to the free choice in the latter of a utility function. At the same time, it is less restrictive than, for instance Whitworth’s (1870) or Kelly’s (1956) treatments because it provides interpretations of utility functions other than the logarithm (for example Cramer’s 1728 square-root).

Following discussions with Jean-Philippe Bouchaud, an important interdisciplinary link between a statistical-mechanics model of spin glasses (the random-energy model) and simple models of investment portfolios (sums of log-normal variates) is published [12]. This link has been known for many years by some researchers and finance professionals. It has allowed powerful techniques developed by physicists in the 1980s to be applied in the context of finance and economics.

Nassim Taleb argues in his book “Skin in the game” that the ergodicity problem requires us to re-think how we use probabilities in economic theory and beyond.

2019: Oliver Hulme’s neuroscience group at the Danish Research Center for Magnetic Resonance conducts behavioral experiments that show strong predictive power of the framework

Marc Elsberg publishes the bestseller “Gier” (in German) – a thriller based on LML’s economics project. See also the accompanying interactive animation.

Peters publishes an update and overview of ergodicity economics [13].

Ergodicity economics has a Wikipedia page.


[13] O. Peters
The ergodicity problem in economics.
Nature Phys. 15, 1216–1221 (2019).

[12] O. Peters and A. Adamou
The sum of log-normal variates in geometric Brownian motion.
arXiv:1802.02939 (2018).

[11] O. Peters and A. Adamou
The time interpretation of expected utility theory.
arXiv:1801.03680 (2018).

[10] Y. Berman, O. Peters, and A. Adamou
Far from equilibrium: Wealth reallocation in the United States.
arXiv:1605.05631 (2016).

[9] A. Adamou and O. Peters
Dynamics of inequality.
Significance 13, 3, 32–37 (2016).

[8] O. Peters and M. Gell-Mann
Evaluating gambles using dynamics.
Chaos 26, 023103 (2016).

[7] O. Peters and A. Adamou
Rational insurance with linear utility and perfect information.
arXiv:1507.04655 (2015).

[6] O. Peters and A. Adamou
The evolutionary advantage of cooperation.
arXiv:1506.03414 (2015).

[5] O. Peters and W. Klein
Ergodicity breaking in geometric Brownian motion.
Phys. Rev. Lett. 110, 100603 (2013).


[4] O. Peters and A. Adamou
Stochastic Market Efficiency.
Santa Fe Institute Working Paper #2013-06-022 (2013).

[3] O. Peters
Menger 1934 revisited.
arXiv:1110.1578 (2011).

[2] O. Peters
The time resolution of the St Petersburg paradox.
Phil. Trans. R. Soc. A 369, 369, 1956, 4913–4931 (2011).

[1] O. Peters
Optimal leverage from non-ergodicity.
Quant. Fin. 11, 11, 1593–1602 (2011).

0 replies

Leave a Reply

Want to join the discussion?
Feel free to contribute!

Leave a Reply

Your email address will not be published. Required fields are marked *