Pick the research directions you'd back, rank your top few, and leave comments. When done,
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The situation, in one paragraph. Our time-bar feature set is saturated (a 77-indicator baseline had ~1 non-redundant
feature) — more features is not the lever; turnover/cost is. ODB (event-clock) intra-bar order-flow features are the project's
first temporally-stable signal (same sign 2022→2026) — genuinely new information — but they do not survive realistic
trading costs. A strong gross signal (per-bar Sharpe ~0.9) collapses to negative at ~7 bps round-trip. So the question is not
"add more data" — it is how to combine the two bar-clocks into something that survives cost, and which minimal experiment tells us most, fastest.
What the research says (adversarially verified). Across equities, options and crypto, strong-gross/high-turnover signals
reproducibly die at realistic cost — cost is the binding constraint, not signal quality. Orthogonality between the two clocks is
real in information but theoretically under-determined (classical mutual information can't cleanly separate "synergy" from
"redundancy" without an extra axiom) — so it must be measured carefully, not assumed. The convergent recommendation is a small honest
pilot before any fusion: establish single-clock baselines → measure the true added information → then test fusion under real cost.
Options below are graded by Effort and strength of Evidence.
The 8 candidate directions
Overall
Generated from two deep-research passes (quant methodology + interaction design) + prior internal ODB work.
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