01 — DOMINANCE SHIFT
Identify the transition.
Locate the area where established bearish control begins to give way to measurable evidence of buyer dominance.
Bullish Dominance-Flip Identification & Trend Isolation
Find the shift.
Isolate the trend.
BDFIT is a rules-based framework designed to identify transitions from prolonged bearish dominance toward sustained bullish control. It is confirmation-led: the objective is not to predict the bottom, but to wait for evidence that a trend has changed.
Primary metric
CAGR
Time-normalized performance.
30% benchmark
76.45%
Framework-level historical success rate.
Duration profile
53.66%
Average CAGR in the controlled sample.
Median CAGR
45.69%
Controlled sample median.
Framework architecture
A process, not a prediction.
The public architecture is intentionally simple. Each stage answers a different question: has the structure changed, has the change been confirmed, and has a durable trend emerged?
02 — FIRST CONFIRMATION
Demand evidence.
The initial structural change is evaluated through objective confirmation rather than discretionary interpretation.
03 — SECOND CONFIRMATION
Filter the reversal.
A second layer of confirmation increases selectivity and helps distinguish a developing trend from temporary counter-trend movement.
04 — TREND ISOLATION
Follow the structure.
Once the required evidence develops, the framework focuses on the sustained bullish phase and applies a defined exit philosophy.
Proprietary methodology
The public framework does not disclose proprietary thresholds, pattern definitions, candle relationships, screening rules, confirmation mechanics, implementation details, or signal-generation logic. The purpose of this page is to explain the research architecture and empirical evidence—not to reproduce the methodology.
Back-test evidence
Measured across regimes.
The research evaluates the framework across multiple historical market cycles. CAGR is used where time normalization is meaningful; return-based exits are assessed separately using realized net growth.
Double Confirmation + Duration Exit
53.66%
Average CAGR across 168 completed trades, excluding 2020–2021 entries.
45.69%Median CAGR
285.92%Best CAGR
-37.64%Worst CAGR
68.45%≥30% CAGR
CAGR threshold distribution
How outcomes distribute.
Two exit philosophies
Same identification process.
Different objectives.
Duration Exit
Time-normalized performance.
Designed for evaluating annualized performance and consistency. Historical analysis uses CAGR so trades with different holding periods can be compared on a common basis.
168Trades
53.66%Average CAGR
45.69%Median CAGR
48.79%Std. deviation
Performance Exit
Realized upside.
Designed to evaluate absolute realized gains when positions are exited using predefined performance conditions. This is measured separately from CAGR because the objective and exit construction differ.
129Trades
102.51%Average net growth
97.41%Median net growth
492.89%Maximum net growth
Research discipline
Evidence before access.
The framework page is deliberately transparent about what has been tested while keeping the proprietary mechanism private. Detailed signal rules are reserved for members and are not required to understand the distinction between the research framework and the live signals.
Next step
Audit the results. Then evaluate the signals.
The portfolio is the evidence layer. The framework explains the research behind it.