Micro Gold (MGC) Order Flow Study Framework
A neutral framework for studying Micro Gold futures with Bookmap. The goal is to document liquidity and execution consistently—not to turn one historical pattern into a promise about the next move.
Know the MGC contract before reading the chart
CME Micro Gold futures use the symbol MGC. The contract unit is 10 troy ounces, which is one-tenth the size of the standard 100-ounce Gold futures contract. The minimum price fluctuation is $0.10 per ounce, so one tick equals $1 per MGC contract.
Those specifications matter for review and risk measurement. A move that looks visually small on a heatmap can still represent multiple ticks. Always confirm the active contract month, tick value, and the instrument shown by your data provider before comparing examples.
Start with session and data context
Order-flow observations depend on the data being viewed. Record the MGC contract month, session, data source, replay/live mode, and any major scheduled event that could change liquidity conditions. Futures liquidity can shift around rollover, economic releases, and changes in participation.
This context does not predict direction. It simply prevents you from comparing unlike samples and calling them the same setup.
Map liquidity before price reaches it
Use the Bookmap heatmap to mark persistent bids and offers relative to prior highs, lows, session extremes, and recent structure. Note whether the displayed size has been stable, adding, pulling, migrating, or already tested.
The purpose is to create a before-the-event record. If a level is only labeled important after price reacts, the review is vulnerable to hindsight bias.
Add executed order-flow evidence at the test
When MGC reaches the area, compare the displayed liquidity with volume bubbles, footprint-style bid/ask pressure, delta/CVD, and the actual price response. Aggressive buying into a sell wall can lead to acceptance if the wall is consumed, or to absorption if heavy execution produces limited progress and the passive side remains.
The same logic applies to aggressive selling into bids. Do not classify the event from color, delta, or volume alone; compare aggression with liquidity and result.
Use Volume Profile to define prior acceptance
A session or composite Volume Profile can identify POC, value-area edges, HVNs, and LVNs. These levels provide historical executed-volume context, while the heatmap shows current and historical resting liquidity. The two layers can overlap or conflict.
For a study, document the profile window in advance. Changing the profile range after seeing the outcome can manufacture a level that was not part of the original decision context.
Three neutral MGC study scenarios
- Liquidity hold: price approaches a persistent band, aggressive volume increases, but price makes limited progress. Record whether the area rejects or eventually accepts through.
- Liquidity pull: a visible band disappears or migrates before the test. Record how price behaves after the passive interest changes without assuming why the order was removed.
- Liquidity consumption: repeated executions reduce the resting band and price begins to build beyond it. Record whether the new area gains acceptance or quickly fails back through.
These are observation categories, not entry instructions. Their value comes from repeating the same definitions over many sessions.
Build a journal that can be audited
- Contract month and session.
- Bookmap/data-feed context.
- Nearest persistent liquidity and structural levels.
- Volume Profile references.
- Footprint/delta/CVD behavior at the test.
- Initial interpretation and explicit invalidation.
- Before/after screenshots and post-session notes.
KS8 can organize these layers, but it cannot remove futures risk or guarantee that a historical relationship will repeat. Use examples to improve observation quality, not to promise outcomes.