1. Collect current market information
The process begins with live or near-real-time data such as candles, price, volume, trades, order-book depth, funding, open interest and liquidations.
Every output is limited by the timeliness and quality of these inputs. Missing, delayed or erroneous source data can affect the setup and simulated lifecycle.
2. Convert raw data into features
Raw values are transformed into features that describe trend, momentum, volatility, market structure and derivatives activity.
Normalization allows values measured in different units to be compared without one input dominating only because its raw number is larger.
3. Evaluate bullish, bearish and neutral evidence
The model assigns directional meaning to the evaluated features. Some inputs may support a bullish case, others a bearish case, and others may remain neutral.
Conflicting evidence can lower confidence, narrow the probability difference or produce a CHOP assessment.
4. Produce direction and probability context
After combining the evidence, the system can produce a direction label and Long and Short probabilities.
Thresholds help prevent small score differences from being presented as a qualified directional setup.
5. Generate simulated reference levels
The platform may derive a simulated entry region, target milestones, protective stop and invalidation level from market structure and the active methodology.
These values describe the mock lifecycle. They are not exchange orders and cannot guarantee a real execution price.
6. Qualify the setup
A directional assessment does not automatically become a mock position. The platform applies confirmation, quality and eligibility rules before a setup qualifies.
A setup may remain in a waiting state when the evidence is insufficient, conflicted or outside the active methodology.
7. Open a synchronized mock position
When the setup qualifies, ScalperBaba can record a simulated entry using the market price observed by the platform.
No exchange account is connected, no API key is used for trading, no funds are held and no real order is submitted.
8. Track targets and protective stops
The mock lifecycle can advance through target milestones, breakeven protection, profit floors, trailing steps and protective-stop conditions.
The displayed lifecycle shows how the methodology responds to changing live prices inside the simulation.
9. Close and record the simulated outcome
A mock position may close because of a target, protective stop, trailing rule, expiration, system condition or administrative close.
The recorded result is simulated and may differ materially from real execution because of spread, fees, funding, slippage, latency, liquidity and liquidation rules.
Common reasons a mock setup fails
- The market regime changes faster than the model adapts.
- A news event overwhelms prior technical and derivatives evidence.
- Input data is delayed, incomplete or temporarily unavailable.
- The direction is reasonable but the timing or invalidation logic fails.
- Real execution would differ from the simplified simulation.
See the concepts inside one market-intelligence workspace.
ScalperBaba organizes qualified LONG and SHORT setups, directional probabilities, technical structure, derivatives flow, liquidations, open interest, funding and depth, then tracks synchronized simulated positions using live data.