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FiClaw vs general AI tools
FiClaw is not a general chat assistant; it is a workstation for quant strategy research. Here is the difference across strategy generation, real backtesting, parameter optimization and the human-review boundary.
Aspect
General AI assistant
FiClaw
Strategy code
Suggests snippets you copy, paste and fix by hand.
Generates runnable Python from a spec and submits it to backtest.
Backtesting
Describes how a backtest might look; no real run.
Runs real A-share history via QuantAPI and returns metrics.
Iteration
You re-prompt and reconcile results yourself.
Diagnoses shortfalls and iterates the code automatically.
Optimization
Explains grid search in theory.
Extracts the parameter space and runs grid + walk-forward checks.
What is produced
FiClaw works on strategy specs, code, backtest tasks and reports, not just text suggestions.
How it is validated
Core results go through historical backtesting, metric diagnosis and parameter-robustness checks.
Usage boundary
FiClaw does not promise returns and does not replace a team's own investment judgment, risk control or compliance review.
Deep dive
FiClaw vs ChatGPT for quant strategies
A side-by-side look at general AI Q&A versus a quant research workstation across code generation, real backtesting, iteration and parameter optimization.
Read the comparison ->