You are a professional fixed-income investor and credit derivatives market maker with deep experience in CDX trading, index basis dynamics, and systematic portfolio design.
Your task is to design a pilot systematic CDX overlay strategy that trades only liquid CDX contracts (e.g., CDX IG, CDX HY, and CDX XO) as a tactical enhancement to a slower-moving credit allocation framework.

1. Objective and Role

Define the strategic purpose of this pilot within a broader credit portfolio:

Its investment objective (e.g., short-term alpha, liquidity hedge, convexity enhancement).

Its relationship to the core asset allocation process (faster-reacting, uncorrelated, capital-efficient).

Expected investment horizon (days to weeks) and turnover profile.

2. Scope of Instruments

Specify:

Which CDX indices and tenors should be used for the pilot.

Whether to include ETF proxies (HYG, LQD) for signal generation only or as tradeable instruments.

Any liquidity, margin, or clearing considerations relevant to practical trading.

3. Core Signals (3-signal pilot)

The pilot strategy must rely only on these three signals:

ETF vs CDX Basis

Define how ETF flow and pricing dislocations versus CDX spreads can signal temporary mispricing.

Explain the intuition behind when to go long or short CDX protection.

Discuss how to normalize and interpret the basis dynamically (e.g., flow-adjusted, volatility-scaled).

VIX vs CDX Gap (Cross-Asset Risk Sentiment)

Describe how divergences between equity implied vol (VIX) and credit spreads capture cross-asset stress asymmetry.

Clarify directional logic (e.g., when VIX spikes more than CDX, when to buy vs sell protection).

Suggest how to handle transient vol spikes vs sustained regime changes.

Short-Term Spread Momentum

Define the concept of momentum in CDX spreads over short horizons (3–10 days).

Explain when continuation or mean-reversion dominates, and how volatility-adjusted momentum improves robustness.

Specify how to determine when to fade vs follow spread moves.

4. Signal Integration & Positioning Logic

Explain:

How to convert each signal into a standardized score (e.g., z-score or percentile).

How to combine the three signals into a single tactical positioning score (weights, decay, aggregation logic).

The trade expression: when to go directional (long/short protection) versus neutral or reduced exposure.

How to determine the expected signal half-life and update frequency.

5. Risk, Sizing, and Governance

Define:

Position sizing principles: DV01- or volatility-based scaling; typical gross and net risk limits.

Stop-loss and signal fade mechanics (when to unwind or scale down).

Expected turnover, slippage, and liquidity assumptions given standard CDX bid/ask spreads.

Governance and oversight guidelines to ensure clear differentiation from slower asset allocation signals.

6. Evaluation Framework

Outline how the pilot’s success should be assessed conceptually:

Performance metrics (hit rate, information ratio, turnover-adjusted return).

Diversification benefits relative to core portfolio exposures.

Behavior under stress or event conditions (macro, vol spikes, ETF outflows).

Lessons expected to inform scaling into a multi-signal production strategy.

Output Requirements

Produce a concise, practitioner-style investment strategy document that:

Explains the economic logic, trading rationale, and integration of each signal.

Includes positioning guidelines, risk parameters, and governance structure.

Avoids any mention of coding, data sourcing, or model implementation details.

Reads like a strategy brief for investment committee review, not a quant note.