QuantLib specialists for your dedicated team.

Where QuantLib fits in a long-term product team.

The unglamorous parts are what make QuantLib valuable. Day count conventions, business day adjustments, holiday calendars per market and settlement rules are tedious, error-prone and unforgiving: a wrong convention produces a valuation that is subtly and persistently incorrect. Having them implemented and tested is worth more than the pricing engines.

Curve construction is where most valuation error starts. Instrument selection, interpolation method and bootstrapping choices change discount factors and therefore every valuation that depends on them. Two teams with the same market data and different curve configurations get different numbers, both defensible.

What your dedicated team does with QuantLib.

Financial libraries need testing against known benchmarks. Validating pricing against published values or an independent implementation is the only way to establish that a configuration is correct.

That validation discipline is part of the delivery standard for quantitative work, agreed as part of how the monthly fee is built.

Common QuantLib use cases.

• Conventions handled correctly Day counts, calendars and settlement rules implemented and tested precisely.
• Curves built deliberately Instrument selection and interpolation chosen explicitly, because they drive every valuation.
• Pricing validated against benchmarks Results checked against published values.

Adding QuantLib skills to your team.

Quantitative development capacity is assigned in a dedicated data engineering team, with benchmark validation part of the definition of done.

You can add QuantLib capacity as one dedicated specialist or as part of a wider remote team, managed by a service delivery manager from our offices in Thailand. Companies hire dedicated developers this way under one agreement and one monthly fee.