Fix/strategy optimization

[LeFi8]

No description provided.

[gemini-code-assist]

Code Review

This pull request introduces a hybrid gating mechanism that allows a trade-off between target metric degradation and annualized return improvement, configured via metric_return_tradeoff and metric_floor. The changes span configuration schemas, gate evaluation logic, orchestrator warnings, and unit tests. The review feedback highlights two important issues: first, the absolute metric_floor constraint is skipped when no baseline is present because it is nested inside the baseline-dependent check; second, there is a naming and description mismatch in the API reference documentation compared to the actual implementation.

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[gemini-code-assist]

The absolute metric_floor constraint is currently only checked inside _check_metric_improvement, which is skipped entirely if baseline is None. This means candidates will not be checked against the absolute target-metric floor when evaluated without a baseline. The absolute floor check should be performed independently of the baseline presence.

Suggested change

	if baseline is not None:
	result = _check_metric_improvement(report, baseline, target_metric, min_improvement)
	result = _check_metric_improvement(
	report, baseline, target_metric, min_improvement, tradeoff_coeff, metric_floor
	)
	if not result.accepted:
	return result
	if metric_floor is not None:
	candidate_val = _get_in_sample_metric_val(report, target_metric)
	if math.isnan(candidate_val) or candidate_val <= metric_floor:
	msg = (
	f"Candidate {target_metric.value} ({candidate_val:.4f}) is below the"
	f" required floor of {metric_floor:.4f}."
	)
	report.is_accepted = False
	report.rejection_reason = msg
	return GateResult(accepted=False, reason=msg, failed_gate="metric_floor")
	if baseline is not None:
	result = _check_metric_improvement(
	report, baseline, target_metric, min_improvement, tradeoff_coeff, metric_floor
	)
	if not result.accepted:
	return result

[gemini-code-assist]

The parameter names and descriptions in the API reference do not match the actual implementation in StrategyConfig (defined in src/autobacktest/strategy/config_schema.py). The fields are implemented as metric_return_tradeoff and metric_floor (not sharpe_return_tradeoff and min_metric_floor), and the tradeoff scaling is per 1pp (0.01) increase in annualized return rather than per 100% (1.0) increase.

Suggested change

	| `sharpe_return_tradeoff` | `float` | `0.0` | Acceptable target metric reduction per 100% (1.0) increase in annualized return; `0.0` disables trade-off |
	| `min_metric_floor` | `float\|None` | `None` | Absolute target metric floor below which candidates are always rejected regardless of trade-off; `None` disables |
	| `metric_return_tradeoff` | `float` | `0.0` | Metric reduction tolerated per 1pp (0.01) increase in annualized return; `0.0` disables |
	| `metric_floor` | `float\|None` | `None` | Absolute target-metric floor below which candidates are always rejected regardless of trade-off; `None` disables |