Advanced Algorithmic Intelligence for Asset Allocation
Presentation for Advanced Traders and Institutional Investors
Developed and Distributed by
CRYPTOS LINKING
© 2024 Cryptos Linking. All Rights Reserved.
This proprietary system, its algorithms, methodologies and all associated documentation are protected by French and international intellectual property laws, including the French Intellectual Property Code (Articles L111-1 and following).
Legal Protection: Any reproduction, representation, modification, publication or adaptation of all or part of this system is prohibited without prior written authorization from Cryptos Linking.
Confidentiality: Confidential document intended for advanced traders and institutional investors. Any unauthorized disclosure is strictly prohibited.
A proprietary market regime classification system combining three complementary quantitative methodologies to accurately identify bullish, bearish, consolidation and transition phases.
Analysis Engines
Identified Regimes
Confidence Score
Advanced statistical modeling simulating hidden state inference through market manifestation observation. Integrates emission probabilities, transition matrices and Bayesian persistence logic.
Aggregation of seven recognized technical indicators (moving average alignment, directional strength, congestion, trend following, momentum) into a robust consensus score.
Detection of volatility clusters via fast/slow ratio to identify expansions, contractions and directional correlations signaling regime changes.
Statistical model inferring the hidden state of the market through three observable dimensions:
Normalized Returns
Structural Volatility
Volume Patterns
A bullish market tends to remain bullish. Probabilistic inertia reflecting market reality.
Bayesian Mechanism
Dynamically adjusted probabilities: present state strongly influences future state via weighted transition matrices.
Time Window
Sliding memory over N periods: recent regimes have exponentially decreasing weight.
Probabilistic Output
P(Haussier) • P(Baissier) • P(Consolidation)
Continuous 0-1 distribution for each state
Intelligent aggregation of seven technical dimensions into a robust consensus score, each providing a unique perspective on current market behavior.
Moving Average Alignment
Relative short/medium/long term configuration
Directional Strength
Intensity of directional vs sideways movement
Congestion Level
Measurement of market sideways character
Trend Following Signals
Confirmation of established direction
Price Slope
Angle and velocity of movement
Momentum
Acceleration and strength
Beyond simple binary classification, the system identifies five distinct states including critical transition phases:
BULLISH
Confirmed
Strong upward consensus. All engines converge toward an established bullish trend.
TRANSITION ↑
Bullish
Uncertain but positively oriented movement. Hesitation phase before confirmation.
CONSOLIDATION
Range/Sideways
Market without clear direction. Oscillation within a limited price zone.
TRANSITION ↓
Bearish
Uncertain but negatively oriented movement. Warning signal before confirmation.
BEARISH
Confirmed
Strong downward consensus. All engines converge toward a bearish trend.
Each identified regime comes with a confidence score (0-100%) measuring consensus among the three engines, allowing exposure modulation.
High Confidence
Strong consensus • Max position 100% • Tight stop • Leverage possible
Good Confidence
Solid agreement • Position 60-80% • Standard stop • Active monitoring
Moderate Confidence
Mixed signals • Position 30-50% • Wide stop • Increased caution
Low Confidence
Strong divergence • Position 0-20% • Cash • Waiting for clarity
Practical Example
Bullish signal detected:
Conf. 92% → Allocation 100%
Conf. 75% → Allocation 70%
Conf. 58% → Allocation 40%
Conf. 42% → Allocation 10%
Impact: -35% average drawdown
The fusion of three distinct methodological perspectives effectively filters false signals.
Strategic adaptation based on context: trend, range or transition.
Dynamic sizing: maximum exposure on high confidence, conservatism on ambiguous signals.
Early detection of transitions providing temporal advantage for repositioning.
Separate visualization of each component enabling consensus understanding.
Works on all asset types and timeframes with automatic adaptation.
Dynamic exposure adjustment based on regime and its score.
Example
High confidence bullish → Equity overweight
Bearish transition → Exposure reduction
Consolidation → Less volatile assets
Activation of strategies adapted to identified context.
Example
Established trend → Momentum strategies
Consolidation → Mean-reversion
Transition → Position reduction
Risk parameter adjustment based on stability.
Example
High confidence → Standard budget
Transition phase → Budget reduction
Low confidence → Defensive position
A multi-dimensional approach transforming technical analysis into structural market understanding.
Convergence of three distinct quantitative methodologies producing robust consensus.
Early detection of transitions providing time window to adjust allocations.
Systematic framework for position sizing based on objective metrics.
Quantitative navigation tool for institutional portfolios