GEX Market Structure
Investigate how the strategy’s trades behaved under different gamma conditions and around relevant GEX levels. The finding concerns the strategy’s response to those conditions.
EdgeQuery applies proprietary research instruments to trade history and available market context to investigate where performance came from and why it changed.
Investigate how the strategy’s trades behaved under different gamma conditions and around relevant GEX levels. The finding concerns the strategy’s response to those conditions.
Examine value areas, points of control, high- and low-volume regions, and price location to investigate where setups succeeded or struggled.
Where detailed data supports it, investigate participation, execution conditions, and spoof-sensitive liquidity around successful and failed trades.
Compare behavior in trend, chop, and transitions. Test longs and shorts separately rather than assuming they need the same confirmation.
Investigate profit concentration, drawdowns, sessions, trade direction, and actual exposure when an economic release occurred.
Connect a finding to its supporting trades and conditions. Challenge competing explanations and investigate meaningful questions revealed by the evidence.
Before filtering out a losing condition, investigate whether it also produces some of the strategy’s best trades.
The answer may be smaller size, different exits, or no change. The next experiment should preserve valuable trades as well as reduce losses.
A closed-trade log can support trade-level diagnostics. Intratrade paths, volume-profile context, GEX context, and order-flow research require the relevant market data and coverage.
We establish available fields, instrument coverage, date ranges, and data permissions during the pilot. Missing evidence and unresolved explanations should remain visible in the findings.
Let’s investigate a real strategy problem, review the evidence together, and decide how the research should fit your platform.