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Category: Advanced Stock Analyzer

  • Portfolio Construction Rule – DSI-Based Allocation

    Portfolio Construction Rule (DSI-Based Allocation)

    After ranking stocks using the Dynamic Stock Selection Index (DSI), capital is distributed proportionally based on relative strength.

    Formal Allocation Rule

    Ws(t) = DSIs(t) / Σ DSIs(t)

    Interactive Portfolio Weight Calculator

    Stock DSIs(t) Weight Ws(t)
    Interpretation:
    Weights sum to 100% of capital. Higher DSI scores receive proportionally larger allocations.

  • Regime-Specific Dynamic Stock Selection Indices

    Regime-Specific Index Versions (Adaptive Market Framework)

    Dynamic Stock Selection uses regime-specific index formulations, where factor relevance changes with market conditions.

    Bull Market Index

    DSIbull = Momentum + Earnings Growth + Relative Strength

    Bear Market Index

    DSIbear = Low Debt + Cash Flow + Volatility Control

    Inflationary Phase Index

    DSIinfl = Pricing Power + Commodities Exposure + ROCE

    Interactive Regime-Specific Index Calculator

    Factor Standardized Score
    Momentum
    Earnings Growth
    Relative Strength
    Low Debt
    Cash Flow
    Volatility Control
    Pricing Power
    Commodities Exposure
    ROCE
    Interpretation:
    Always compare stocks using the same regime-specific index. As regimes change, factor relevance updates automatically.

  • Market-Regime-Adaptive Weights (Key Innovation)

    Market-Regime-Adaptive Weights

    This model dynamically updates factor weights based on changing market relevance, allowing continuous and automatic regime adaptation.

    Adaptive Weight Update Rule

    wᵢ(t) = wᵢ(t−1) · e−λ ΔRᵢ(t)

    Interactive Market-Regime Weight Update Simulator

    Factor (i) wᵢ(t−1) ΔRᵢ(t) wᵢ(t)
    Interpretation:
    Updated weights reflect alignment with the current market regime. Factor importance evolves smoothly without abrupt rebalancing.

  • Dynamic Stock Selection Index (DSI)

    Dynamic Stock Selection Index (DSI)

    The Dynamic Stock Selection Index (DSI) adapts factor relevance and weights across market regimes, ensuring regime-aware stock ranking.

    Main Formula

    DSIs(t) = Σi ∈ F15(t) wᵢ(t) · zs,i(t)

    Interactive DSI Calculator (Single Stock)

    Factor (i) zs,i(t) wᵢ(t)
    Interpretation:
    Higher DSI indicates stronger alignment with the current market regime. Use DSI values to rank stocks evaluated at the same time.

  • Factor-Selection Operator (500 → 15)

    Factor-Selection Operator (500 → 15)

    This operator dynamically selects the top-15 most relevant factors from a large universe, preventing overfitting and ensuring regime adaptability.

    Formal Definition

    F15(t) = Top-15 factors ranked by Rᵢ(t)

    Interactive Factor-Selection Simulator

    Factor ID Rᵢ(t) – Relevance Score
    Interpretation:
    The output represents F15(t), the active factor set used for stock selection at the current time.

  • Stock Market Factor Relevance Function

    Factor Relevance Function (Stock Market – Dynamic Model)

    This module computes the dynamic relevance score of a stock-market factor based on macro conditions, sector leadership, and recent predictive power.

    Mathematical Definition

    Rᵢ(t) = α · Mᵢ(t) + β · Sᵢ(t) + γ · Pᵢ(t)

    Interactive Factor Relevance Calculator

    Tuning Parameters

    Interpretation:
    Higher Rᵢ(t) values indicate factors that should be prioritized for stock selection in the current market phase.

  • Machine-Assisted Adaptive Selection Index

    Machine-Assisted Adaptive Selection Index

    This module demonstrates a learning-based weight update mechanism, where selection weights evolve automatically based on observed gain, mirroring gradient-based optimization in AI systems.

    Weight Update Rule

    bᵢ(t+1) = bᵢ(t) + η · ∂G(t) / ∂bᵢ

    Interactive Adaptive Weight Update Simulator

    Trait (i) bᵢ(t) ∂G(t)/∂bᵢ bᵢ(t+1)
    Interpretation:
    Positive sensitivity increases trait importance, negative sensitivity reduces it. The learning rate controls adaptation speed and stability.

  • Constraint-Based Dynamic Selection Index

    Constraint-Based Dynamic Selection Index

    This module maximizes selection gain while enforcing hard constraints on selected traits. Restricted traits are held constant and excluded from optimization.

    Optimization Objective

    Maximize   I(t) = Σ bᵢ(t) · xᵢ

    Subject to Constraint

    Δxⱼ(t) = 0   for restricted traits

    Interactive Constraint-Based Index Calculator

    Trait (i) xᵢ bᵢ(t) Restricted?
    Interpretation:
    Restricted traits (Δx = 0) are excluded from optimization. The index reflects only improvable components, ensuring realistic and constraint-safe decisions.

  • Time-Weighted Selection Index (Decay Model)

    Time-Weighted Selection Index (Decay Model)

    This model applies exponential decay so that older factors gradually lose influence as conditions change.

    Mathematical Model

    I(t) = Σ [ bᵢ · e−λ(t − tᵢ) ] · xᵢ

    Interactive Time-Weighted Index Calculator

    Factor xᵢ bᵢ tᵢ
    Interpretation:
    Recent factors contribute more strongly than older ones. The index automatically adapts to temporal relevance decay.

  • Stage-Specific Selection Index – Breeding Pipeline Model

    Stage-Specific Selection Index (Breeding Pipeline Model)

    Selection priorities change across breeding stages. This module evaluates genotypes using stage-specific objective functions.

    Early Generation Index (F₂–F₄)

    Iearly = Σ bᵢ(E) · xᵢ

    Advanced Generation Index (F₅–F₈)

    Iadvanced = Σ bᵢ(A) · xᵢ

    Release Stage Index

    Ifinal = Σ bᵢ(R) · xᵢ

    Interactive Stage-Specific Index Calculator

    Trait xᵢ bᵢ(stage)
    Interpretation:
    Genotypes must perform well across all pipeline stages. This prevents premature selection of lines that fail later.