Compare by market conditions
In the strategy center, review triggers, position behavior, exits and unsuitable environments. Trend and range strategies address different conditions. A name, isolated return or short historical period is not enough to choose one.
Separate simulation from research
Current evidence covers adapted grid and bounded DCA versions in local simulation. Catalog inclusion does not establish executability, and joint acceptance of two BOT flows is still pending. Simulation records cannot prove real fills or a live trading connection.
Treat constraints as part of the strategy
Review allocation, costs, risk limits and pause conditions together. Several strategies can share correlated exposure, so adding a strategy requires another portfolio-level check.
An AI BOT approval covers a specific plan. Changes to the account, material parameters or execution scope require another check and approval. Autonomous AI trading is designed to choose opportunities within an explicitly authorized scope; its independent authorization and continuous operation remain under development. Signing in, connecting, reading data and executing trades are distinct permissions.
Align the conditions before comparing results
Compare strategies using the same market, observation period, data version and cost assumptions. If one was tested only in a trend and another through a long range, their returns may reflect different environments rather than different quality. Trading frequency also changes the effect of fees, slippage and reserved capital.
When results diverge from expectations, distinguish a failed hypothesis from missing data, an incorrectly triggered rule or execution that departed from the plan. Identify the cause before revising. Change a defined condition and retain the version so the next review remains comparable.