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The stockrobot.ai [SR] AI engine is designed to build bots that evolve over time, learn from each other, and "reproduce" by commingle their programming DNA create compound algorithms.
Trading signals from the bots are posted in real-time to Discord, along with historical bot performance and multi-bot indicators.
Built purely from evolutionary mutation and randomness, SR bots explore novel indicators in unique combinations that no human would think to test. The SR engine is a universal algorithm machine at its core.
By looking outside the box, SR turns quantitative analysis inside out. Rather than top-down development of trading strategies, SR strategies "emerge" from the bottom-up.
Every new bot's program is infused with the collective performance of other bots. As the ecosystem grows, so too does the selective pressure towards optimized algorithms.
SR weekly newsletter and discord channel distill the thousands of weekly bot trades into unique market insights. Discord membership grants direct /-command access to bot intel.
SR's long term value is in amassing a the world's largest active stable of trading algorithms, fully tested over time to distill out only actually working strategies. Early adopters will be considered founding members.
The roadmap of SR feature rollouts, bot additions and future directions is contingent on getting subscribers. This is designed to be a community driven service, as the community grows so too will the value. Sign up today to get early access to all the bot signals on our discord as well as the monthly news letter.
Dr. Stephan Woflram's thoughts on computation drove the thinking behind stockrobot.ai.
Rather than top-down directed search, the SR engine is searching the space of all possible computable trading indicators.
George Soros discussing the EMH (efficient market hypothesis). His theory of reflexivity states that market prices have an impact on fundamentals. This deviates from the prevailing view that "alpha" - or excess returns from active management - is impossible. Stockrobot.ai searches for alpha strategies in an entirely novel way.
Mandelbrot predated Wolfram in exploring complexity emerging from simple algorithms. His book 'The (Mis)Behavior of Markets' had a large influence on the thinking behind stockrobot.ai.
Nassim Taleb is required reading for thinking about the markets computationally.
SR bots make no epistemic claims, leaning into concepts of luck and randomness as drivers of profit.
The concept of computational irreducibility claims that for most natural systems, the best way to predict how they will behave is to simply "run the program". Every SR bot represents a novel program, collectively the SR bot ecosystem creates a computational microscope for exploring the space of all possible trading algorithms.
Jeff Hawkins has had a profound impact on how we think about intelligence. His books "On Intelligence" and "A Thousand Brains" are excellent.
In SR there is not "one model" of the market - rather thousands of models each analyzing the markets independently.
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