Fair Value Drift: When Your Quote Gets Old Fast

Stale fair values misprice risk and invite adverse selection. In fast markets, even milliseconds of drift can flip a trade from edge to liability.

Tracking lag between reference prices and order flow keeps models current and protects against quoting ghosts.

Why it matters

Fair value is the anchor for quoting and hedging. If it lags reality, fills accumulate at mispriced levels, leading to hidden losses.

Common mistakes

• Updating fair value only on trade events.
• Ignoring feed delays between venues.
• Failing to halt trading when drift is detected.

Implementation steps

Measure divergence

Compare fair value to live best bids/offers and mark lag.

Use fastest data

Feed models with direct feeds or co-located sources when possible.

Set drift policies

Pause or adjust quoting when divergence exceeds tolerance.

LiquidityAI tie-in

• Latency monitors track fair value update times.
• Policies auto-halt strategies on excessive drift.
• Analytics show P&L impact from lag.

Case sketch (composite)

A market-maker’s quotes lagged futures by 20ms, leading to adverse fills. LiquidityAI alerts prompted feed upgrades, cutting drift to 5ms and recovering 4bps of edge.

Takeaways

• Fair value drift turns good quotes bad.
• Measure and alert on divergence continuously.
• Pause trading when drift breaches tolerance.

LiquidityAI provides tools and education for systematic trading. This article is for informational purposes only and does not constitute investment advice. Trading involves risk, including possible loss of principal.