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Gold/Silver Strategy Suite -- Overview

29 strategies across 8 categories, purpose-built for precious metals alpha generation. All strategies implement the Strategy base class and declare regime tags, factor exposures, capacity models, and decay monitors per the institutional mandate (SS5).

Architecture

graph TB
    subgraph "Data Layer"
        FRED[FRED API]
        CFTC[CFTC COT]
        COMEX[COMEX Warehouse]
        SGE[SGE Withdrawals]
        OPT[Options Chain]
        LBMA[LBMA Fix/Vaults]
        ETF[ETF Flow Tracker]
        CB[Central Bank Reserves]
    end

    subgraph "PIT Layer"
        PIT[pit_join -- no lookahead]
    end

    subgraph "Strategy Categories"
        A[A. Macro Regime<br/>A.1-A.5]
        B[B. Curve & Carry<br/>B.6-B.9]
        C[C. Stat Arb<br/>C.10-C.13]
        D[D. Positioning<br/>D.14-D.18]
        E[E. Options<br/>E.19-E.22]
        F[F. Microstructure<br/>F.23-F.26]
        G[G. ML/Meta<br/>G.27-G.28]
        H[H. Tail Hedge<br/>H.29]
    end

    subgraph "Portfolio Construction"
        ALLOC[Risk-Parity Allocator]
        RISK[Risk Engine]
        EXEC[Execution Router]
    end

    FRED & CFTC & COMEX & SGE & OPT & LBMA & ETF & CB --> PIT
    PIT --> A & B & C & D & E & F & G & H
    A & B & C & D & E & F & G & H --> ALLOC
    ALLOC --> RISK --> EXEC

Strategy Registry

A. Macro Regime (5 strategies)

Directional precious metals exposure driven by macroeconomic state variables.

ID Strategy Module Rebalance Sharpe Range Status Detail
A.1 Real Rate Gold real_rate_gold.py Daily 0.6--1.0 Live Spec
A.2 DXY Gold dxy_gold.py Daily 0.5--0.9 Live Spec
A.3 Breakeven Inflation Gold breakeven_inflation_gold.py Weekly 0.4--0.8 Live Spec
A.4 VIX Haven vix_haven.py Daily 0.7--1.2 Live Spec
A.5 Central Bank Accumulation central_bank_gold.py Monthly 0.3--0.6 Live Spec

Category thesis: Gold is a macro asset whose primary driver is the opportunity cost of holding a zero-coupon store of value. Real rates, the dollar, inflation expectations, risk appetite, and central bank reserve decisions jointly determine the regime.

B. Curve & Carry (4 strategies)

Extract carry and basis signals from the gold and silver futures term structure.

ID Strategy Module Rebalance Sharpe Range Status Detail
B.6 GC Term Structure gc_term_structure.py Daily 0.5--0.9 Live Spec
B.7 SI Term Structure si_term_structure.py Weekly 0.4--0.8 Live Spec
B.8 Cross Carry cross_carry.py Weekly 0.5--0.8 Live Spec
B.9 Backwardation Stress -- Daily 0.6--1.0 Planned Spec

Category thesis: The futures term structure embeds cost-of-carry (storage + financing) and convenience yield (physical demand urgency). Deviations from fair carry signal mispricing; roll yield is a persistent risk premium.

C. Statistical Arbitrage (4 strategies)

Market-neutral relative value within the precious metals complex.

ID Strategy Module Rebalance Sharpe Range Status Detail
C.10 Gold/Silver Ratio gold_silver_ratio.py Daily 0.7--1.1 Live Spec
C.11 Gold/Platinum -- Daily 0.4--0.7 Planned Spec
C.12 Miners vs Metal -- Weekly 0.5--0.9 Planned Spec
C.13 Levered ETF Decay -- Daily 0.6--1.0 Planned Spec

Category thesis: Precious metals share common macro drivers but have distinct supply/demand structures. Ratios between metals, miners, and levered products mean-revert with estimable half-lives.

D. Positioning & Flows (5 strategies)

Trade against crowd positioning and track physical demand proxies.

ID Strategy Module Rebalance Sharpe Range Status Detail
D.14 COT Extreme cot_precious.py Weekly 0.5--0.9 Live Spec
D.15 Hedging Pressure hedging_pressure.py Weekly 0.4--0.7 Live Spec
D.16 ETF Flow Momentum -- Daily 0.4--0.8 Planned Spec
D.17 COMEX Warehouse comex_warehouse.py Daily 0.5--0.9 Live Spec
D.18 SGE Withdrawals sge_withdrawals.py Weekly 0.4--0.8 Live Spec

Category thesis: Futures positioning data reveals when the crowd is offside. Physical flow data (COMEX stocks, SGE withdrawals, ETF creations) provides ground-truth demand signals that lead price.

E. Options (4 strategies)

Harvest the volatility risk premium and exploit skew/term-structure dislocations.

ID Strategy Module Rebalance Sharpe Range Status Detail
E.19 Vol Risk Premium vol_risk_premium_pm.py Monthly 0.6--1.0 Live Spec
E.20 Skew -- Weekly 0.4--0.8 Planned Spec
E.21 Gamma Scalp -- Daily 0.5--0.9 Planned Spec
E.22 Vol Term Structure -- Weekly 0.5--0.8 Planned Spec

Category thesis: Gold/silver implied volatility systematically exceeds realized volatility. The premium compensates for jump risk and can be harvested via short-vol strategies with tail-hedge overlays.

F. Microstructure (4 strategies)

Exploit predictable intraday/intraweek patterns and event-driven price dislocations.

ID Strategy Module Rebalance Sharpe Range Status Detail
F.23 Event Drift -- Event 0.5--0.9 Planned Spec
F.24 Fix Dislocation -- Daily 0.4--0.7 Planned Spec
F.25 Overnight -- Daily 0.3--0.6 Planned Spec
F.26 Seasonality -- Monthly 0.3--0.5 Planned Spec

Category thesis: Precious metals markets have structural microstructure patterns: the London AM/PM fix creates predictable dislocations, FOMC/NFP events generate post-announcement drift, and gold has documented seasonal patterns (Indian wedding season, Chinese New Year).

G. ML & Meta (2 strategies) + H. Tail Hedge (1 strategy)

Machine learning overlays that size/gate discretionary signals, plus a structural tail hedge.

ID Strategy Module Rebalance Sharpe Range Status Detail
G.27 Meta-Labeller -- Daily +0.1--0.3 SR lift Planned Spec
G.28 Regime Classifier regime_detector.py Daily Filter Live Spec
H.29 Tail Hedge -- Monthly Negative carry Planned Spec

Category thesis: ML meta-models improve the aggregate portfolio by learning which base strategies to trust in each regime. The tail hedge is always-on insurance that bleeds carry but protects against 4+ sigma drawdowns.

Aggregate Portfolio Properties

Metric Target
Gross Sharpe (before costs) 1.5--2.0
Net Sharpe (after costs) 1.0--1.5
Max drawdown < 12%
Monthly turnover < 200%
Correlation to SPX < 0.15
Strategy count (live) 13
Strategy count (planned) 16

Cross-References