This repo is for research about differences with regression to the mean and gambler's fallacy.
We worked on this code for shows there is no non-risk and perfect strategy. Do not believe this simulation's result can reproduce in real gambling. We caution that these results are solely for academic purposes, and we do not endorse or encourage gambling as a means of making money.
In this work, we investigate the difference between the regression to the mean, and the gambler's fallacy, by simulating a simple betting game using various betting strategies. The code in the repo simulates the game with different strategies, including random guessing, gambler's fallacy, martingale betting, and regression-based strategies, and evaluates their performances. The results show that there is no perfect strategy. This further shows that using regression to the mean for gambling is not safe and that will be the same as the gambler's fallacy.
Cognitive bias is a common fallacy of human thinking that can lead to misjudgment and decision-making. Gambler's fallacy and regression to the mean are intuitively similar but they have many differences.