computer science

QuantLib

QuantLib is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand QuantLib rather than just read about it. In short: QuantLib is an open-source software library which provides tools for software developers and practitioners interested in financial instrument valuation and related subjects. QuantLib is written in C++.

Key takeaways

QuantLib belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect QuantLib to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of QuantLib from memory before moving on to harder problems.

Reference excerpt

QuantLib is an open-source software library which provides tools for software developers and practitioners interested in financial instrument valuation and related subjects. QuantLib is written in C++.

History The QuantLib project was started by a few quantitative analysts who worked at RiskMap (currently StatPro Italia). The first e-mail announcing QuantLib to the world was sent on December 11, 2000, and signed by Ferdinando Ametrano, Luigi Ballabio and Marco Marchioro. RiskMap was founded by Dario Cintioli, Ferdinando Ametrano, Luigi Ballabio, Adolfo Benin, and Marco Marchioro. The people at RiskMap faced the problem, not for the first time in their lives, to build a financial library from scratch. It was Ferdinando's idea to build an open source library that could be used by quants all over the world when starting to build a new quantitative library. Currently, the QuantLib project is headed by Luigi Ballabio and Ferdinando Ametrano.

Release History

Usage QuantLib is available as C++ source code which is compiled into a library. It is known to work on Windows, Mac OS X, Linux and other Unix-like operation systems. It can be linked with other languages via SWIG. The Python binding can be installed via pip; the "RQuantLib" package makes parts of QuantLib accessible from R. Much of QuantLib's functionality can be used in Excel via the add-in QuantlibXL.

Licensing QuantLib is released under a modified BSD license known as the XFree86-type license. It is GPL compatible.

Features The software provides various facilities for computing values of financial instruments and related calculations. It is a major example of Mathematical finance. Its main use is in quantitative analysis. The financial instruments and derivatives it can evaluate include

Options Asian options Basket options Cliquet options Compound options Digital options Lookback options Vanilla options Bonds Amortizing bonds Convertible bonds Fixed rate bonds Floating rate bonds Zero-coupon bonds Yield curve Date calculations Calendars Date calculations Day counting methods Swaps Asset swaps BMA swaps Year-on-year inflation swaps Vanilla swaps Quantos Currencies It has models for

Yield curves Interest rates Volatility It can compute derivative prices using methods including:

Analytic formulae Tree methods Finite difference methods Monte Carlo methods

See also Mathematical finance List of finance topics#Financial markets

References

External links QuantLib homepage Is QuantLib over engineered? QuantLib in C++ Reference

Worked examples

Example 1 — a first encounter with QuantLib

Start with the simplest possible case. Write down what QuantLib claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to QuantLib before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about QuantLib ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of QuantLib

In research: QuantLib appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses QuantLib in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: QuantLib is common in secondary-school and first-year university syllabi. It links to neighbouring topics Free computer libraries, Free software programmed in C++, Mathematical finance, so understanding it makes those chapters shorter.
In everyday life: Look for QuantLib outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study QuantLib in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what QuantLib means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain QuantLib out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is QuantLib in simple terms?

Why does QuantLib matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study QuantLib?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on QuantLib.