Dragon Alpha Promotion Decision
Scope
- Evaluation window:
2016-01-01 to 2025-12-31
- Reference branches:
workbook_preserving: reconstruction reference
alpha_first_selective_veto: current formal alpha control
alpha_first_glued_refined_hot_cap: leading higher-alpha candidate
Current Fact Pattern
alpha_first_selective_veto
- trades
102
- avg_return
2.86%
- profit_factor
4.04
- CAGR
28.70%
- real BUY / SELL overlap
101/101
alpha_first_glued_refined_hot_cap
- trades
91
- avg_return
3.42%
- profit_factor
5.11
- CAGR
31.32%
- real BUY / SELL overlap
90/90
refined minus current alpha
- avg_return
+0.56%
- profit_factor
+1.07
- CAGR
+2.62%
- overlap cost
-11 BUY / -11 SELL
What Has Already Been Proven
What Is Not Proven False
- The refined branch is not a knife-edge threshold artifact.
- The refined branch does not depend on deleting profitable samples.
- The refined branch does not lose its edge once reasonable costs are applied.
- The refined branch does not improve only in one tiny sample slice; the gain is concentrated in intended glued short-holding cleanup while medium/long buckets are preserved.
Real Remaining Blocker
- The only blocker is governance preference, not quant evidence.
- Automatic promotion was blocked because overlap loss exceeded the preset tolerance of
8 extra BUYs and 8 extra SELLs.
- In other words:
- quant answer: refined is better
- governance answer: refined is more different
Decision Tree
Option A: Keep alpha_first_selective_veto As Formal Alpha
Use this if the institution still values workbook continuity as a hard constraint.
Pros
- smaller divergence from workbook-style reconstructed history
- easier to explain as a conservative formal branch
- lower organizational change cost
Cons
- knowingly keeps
11 losing short-holding glued trades
- gives up better CAGR, PF, win rate, and drawdown quality
- keeps the weaker branch as the official alpha reference
Option B: Promote alpha_first_glued_refined_hot_cap To Formal Alpha
Use this if the objective is now explicitly "robust alpha first, workbook resemblance second".
Pros
- best headline return and compounding
- best cost-stress behavior
- best drawdown profile
- better walk-forward behavior
- removed set is fully explainable and low quality
Cons
- formal overlap drops from
101/101 to 90/90
- governance narrative must acknowledge deliberate workbook divergence
Option C: Keep Dual Track
Use this if governance is not yet ready to bless the stronger branch as official, but research should clearly move around the stronger branch.
- Operational meaning
alpha_first_selective_veto stays frozen as control
alpha_first_glued_refined_hot_cap becomes the default forward research branch
- all future new ideas are judged first against refined, then checked against control
Recommendation
- Governance-neutral recommendation: keep
DUAL_TRACK_GOVERNANCE
- Alpha-first recommendation: promote
alpha_first_glued_refined_hot_cap
Reason:
- If the question is "which branch is the better quant strategy", the answer is already
alpha_first_glued_refined_hot_cap.
- If the question is "which branch is safer to keep as an official bridge from workbook reconstruction", the answer remains
alpha_first_selective_veto.
Given the current research direction has already shifted toward stronger alpha, the practical operating stance should be:
- forward research default:
alpha_first_glued_refined_hot_cap
- benchmark control:
alpha_first_selective_veto
- reconstruction reference:
workbook_preserving
Promotion Trigger Rule
Promote refined immediately if any one of the following is accepted explicitly:
- workbook overlap is a cost metric, not a hard gate
- overlap tolerance is widened from
8/8 to at least 11/11
- the official objective becomes "maximize robust alpha on
399673 under explainable rules"
Do not block promotion on any of the following, because they have already been tested:
- transaction cost pressure
- local threshold fragility
- weak walk-forward behavior
- profitable-trade over-removal
- worse drawdown quality
Execution Rule Going Forward
- Do not resume workbook-style micro-alignment tuning as the main path.
- New experiments should target:
- whether refined can be improved further without damaging its current robustness
- whether any new rule beats refined on quality and stability, not on workbook resemblance alone
- If a future branch beats refined, compare it primarily against refined, not against workbook.