The software calculates a discrete Monte Carlo spectrum of most probable prices (within a defined sample size) in a game theory of retail trade and purchase of a product in a given overcountable price range [a,b] with certain price start value s (agreed between trader and buyer) and attractive (static) price interaction force (experienced by the buyer), assuming a Poisson trade event distribution.
The resulting discrete Monte Carlo price spectrum with maximal price sum can be applied to numerically approximate an optimal trading strategy (Nash equilibrium) for efficient trading within the range of the given sample size for a multiplayer game.
git clone https://github.com/alexej-schelle/MonteCarloPriceSpectrum.git and start the software monte_carlo_price_spectrum.py
Download files at https://github.com/alexej-schelle/MonteCarloPriceSpectrum/ and start the software monte_carlo_price_spectrum.py
git clone https://github.com/alexej-schelle/MonteCarloPriceSpectrum/ and read docs/README.txt
Note : Please note that, besides that the Python routine works well, a rigorous mathematical proof for the approach to approximate a multiplayer Nash equilibrium is so far still missing.
FH-Doz. Dr. Alexej Schelle