Econophysics Trading System

The idea is fairly simple: the system is built around the dynamics of a non-equilibrium medium. There are no hard thresholds or conventional if-else rules, no forecasting algorithms and no AI. It responds to market shocks through mathematical conservation laws, with its internal state adapting to changing volatility. It's still an experimental system, not yet a prototype, but the simulation of physical states is already showing some interesting results. I'm approaching the problem through concepts borrowed from quantum mechanics, thermodynamics and statistical physics. These fields deal with complex systems where tracking every individual element and predicting its exact future state isn't always practical. Rather than trying to predict market direction, the engine continuously processes incoming exchange data through an evolving physical model. Each component affects the others, and the overall behavior emerges from their interaction. There's no learning from historical trades, searching for profitable patterns or memorizing winning combinations. What interests me most at this stage isn't individual trades, but how the system behaves as a whole during a session. The main thing I'm watching is how it handles energy and accumulated pressure. One encouraging change is that drawdowns have become considerably smaller than in earlier experiments, even under highly unstable market conditions. That's an important milestone. It suggests that the underlying mechanics may actually be working. The goal isn't to guess which way the market moves. It's to build a system that can absorb external pressure, redistribute energy, neutralize negative charges and eventually bring session equity above its previous all-time high. Video showing the draft in action (transactions and data can be found via the link in the video description): https://youtu.be/9FfTlnbw_xE