How do you implement effective market data quality controls in a risk management environment?
How do you implement effective market data quality controls in a risk management environment?
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la_fonction_capetienne · External communityPost link
External question — Quantitative Finance Stack Exchange
Author: la_fonction_capetienne
Original post: https://quant.stackexchange.com/questions/85874
License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/
Adaptation: HTML converted to plain text; contact email addresses removed.
I work with market data used for risk calculations (interest rates, FX, equity prices, volatilities, etc.) and I'm looking for best practices to control data quality before it is consumed by downstream systems.
Typical controls I am considering include:
Completeness checks (missing instruments, missing fields)
Freshness checks (stale market data)
Threshold / tolerance checks against previous values
Cross-source validation
Outlier detection
Curve consistency checks
What controls are commonly implemented in banks, asset managers, or trading firms? How are thresholds usually calibrated to avoid both false positives and missed data issues?
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Quoted from Forex.com.bd-Editorial External question — Quantitative Finance Stack Exchange Author: la_fonction_capetienne Source score (net votes, not local likes): 1 Original post: https://quant.stackexchange.com/questions/85874 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. I work with market data used for risk calculations (interest rates, FX, equity prices, volatilities, etc.) and I'm looking for best practices to control data quality before it is consumed by downstream systems. Typical controls I am considering include: Completeness checks (missing instruments, missing fields) Freshness checks (stale market data) Threshold / tolerance checks against previous values Cross-source validation Outlier detection Curve consistency checks What controls are commonly implemented in banks, asset managers, or trading firms? How are thresholds usually calibrated to avoid both false positives and missed data issues?
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