Ole Peters

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Ole Peters
The problem with formalists and behavioral econmists  
Both behavioral economics and formalists are wrong about what they consider irrational behavior in economics
When ergodicity is introduced, what is thought to be irrational behavior considering economic theory, is actually pretty rational
The "biases" that sprouted out of cognitive biases, never take account for ergodicity and time series and often fall apart when those factors are considered
Much of the policy delivered to policy makers come from the old formalists or new behavioral economics, both having dangerously wrong understanding of ergodicity, which ends up with suboptimal advice given to policy makers
The Poor Foundation of Behavioral Economics and Formalists
Behavioral economics grew out of Prospect Theory
Prospect Theory grew out of Expected Utility Theory
Expected Utility Theory is deeply mathematically flawed, especially on the concept of time. The foundation of both fields are both poor

The Ergodicity Problem of Economics
The ergodic hypothesis is a key analytical device of equilibrium statistical mechanics.
It underlies the assumption that the time average and the expectation value of an observable are the same.
Where it is valid, dynamical descriptions can often be replaced with much simpler probabilistic ones — time is essentially eliminated from the models.
the prevailing formulations of economic theory — expected utility theory and its descendants — make an indiscriminate assumption of ergodicity. This is largely because foundational concepts to do with risk and randomness originated in seventeenth-century economics, predating by some 200 years the concept of ergodicity, which arose in nineteenth-century physics. In this Perspective, I argue that by carefully addressing the question of ergodicity, many puzzles besetting the current economic formalism are resolved in a natural and empirically testable way.
We will call an observable ergodic if its time average equals its expectation value,
the core ergodicity question: is the time average of an observable equal to its expectation value?
A gamble 
Would you accept the gamble and risk losing at the toss of a coin 40% of your house, car and life savings?
The failure of the expected wealth model to describe actual human behaviour is known as the St. Petersburg paradox,
Utility Theory
Utility theory considers a static probability space, without an explicit treatment of time.
Economics by asking explicitly whether something is ergodic, which is often not the case. As we have seen, ergodicity economics is a perspective that arises from constructing ergodic observables for non-ergodic (growth) processes.
We all live through time and suffer the physical consequences (and psychological consequences, for that matter) of the actions of our younger selves. With ergodicity economics, the psychological insight that some people are systematically more cautious than others attains a physical interpretation. Perhaps people aren’t so different, but their circumstances are.
Experiment
In the additive environment people were given a starting wealth of about $150 and then each made 312 choices between additive gambles, with fixed dollar amounts at stake, for example between tossing a coin for winning $40 or losing $30; and tossing a coin for winning $30 or losing $20. 
In contrast, in the multiplicative environment, the same people were also given about $150, and then made 312 choices between multiplicative gambles, with fixed proportions of wealth at stake, for example between tossing a coin for a 100% gain in wealth or a 70% loss; and tossing a coin for a 30% gain or a 20% loss.
Growth rate optimization predicts a relationship between how fast something grows and how volatile it is. This relationship holds not only for the stock market indexes we have checked but even for bitcoin.
each behavioural pattern that follows from growth rate maximization has its own narrative and vocabulary. Take discounting as an example: thousands of studies investigate subjective perceptions of the value of a dollar in the future. When expressed mathematically, the heart of this narrative becomes a story about growth rates. One has to relabel and rearrange some terms in the relevant equation, but eventually the ergodic growth rate is recovered as the fundamental concept

Leverage efficiency

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Why is Risk/Reward is Important to Think About When Making Business Decisions

When making business decisions, it's absolutely critical to view the concept of risk/reward through an ergodic lens. Ask yourself: are the potential rewards of this decision ergodic over time? Will the ensemble average of outcomes match the time average?

Too often, businesses make the mistake of focusing solely on expected values and short-term rewards, ignoring the long-term ergodic consequences. They chase after high-risk, high-reward opportunities without considering how those risks compound over time. Is the volatility of outcomes sustainable? Will the business still be around to reap any rewards?

An ergodic perspective reveals that many seemingly attractive business gambles are actually irrational and destructive when you factor in the effects of time. The rewards may look enticing at first glance, but they fail the ergodicity test. Optimizing for growth rates, not just absolute outcomes, is key.

So when weighing risks and rewards, always come back to ergodicity. Will this decision optimize our growth rate over time? Is it robust to volatility? Are we sacrificing long-term ergodic viability for a short-term expected value?

Remember, in the real world where businesses rise and fall, it's ergodic merits that matter most. Judge risks and rewards accordingly. Don't be misled by non-ergodic thinking that ignores the inescapable reality of time. Is your conception of risk/reward grounded in ergodicity?

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