Overfitting
Too many rules or tuned parameters can fit historical noise instead of a durable market effect.
A profitable historical test is a hypothesis under assumptions. The real research job is to discover which assumptions are doing the work and whether the idea survives more realistic conditions.
Too many rules or tuned parameters can fit historical noise instead of a durable market effect.
The test accidentally uses information that would not have been available at the simulated decision time.
The dataset excludes delisted instruments, bad ticks or periods that make the strategy look worse.
Ignoring spread, commission, slippage, latency, partial fills and liquidity can create results that cannot be reproduced live.
A bot can repeat a mistake faster than a human. Network outages, stale data, duplicated orders, time-zone errors, API token problems, broker disconnections and unexpected platform updates all need failure handling.
Generative AI can explain APIs, draft code and accelerate prototypes. Treat generated code as untrusted until it has been reviewed, tested and restricted to the permissions actually required. Software correctness and strategy profitability are separate questions.
Historical simulation cannot guarantee future results. Automated trading can amplify both strategy and software errors.
Use ESTVELO as a research workspace: verify the source, check the jurisdiction, understand the assumptions and separate market information from a personal trading decision.