Using complexity economics and chaos theory, J. Doyne Farmer leverages big data to forecast everything from the stock market to roulette.
What if we could predict the economy the way we predict the weather? What if governments could run simulations to forecast the effects of new policies鈥攂efore they happen? And what if the key to all of this lies in the same chaotic systems that explain spinning roulette wheels and rolling dice?
is a University of Oxford professor, complexity scientist, and former physicist who once beat Las Vegas casinos using his scientific-based methods.
In his recent book (Yale University Press, 2024), Farmer is using those same principles to build a new branch of economics called complexity economics鈥攐ne that uses big data to help forecast market crashes, design better policies, and find ways to confront climate change.
On this episode of the Big Brains podcast, Farmer explains his work, whether we can really predict the unpredictable, and how using chaos theory could shake up well-established economic approaches:
. Subscribe to Big Brains on and .
Source:
