Skip to main content

Interface package to make QuantLib pricing library functions available in Excel.

Project description

QuantLibXlOil

CI

Documentation

QuantLibXlOil is an interface package to make functions of the open-source QuantLib pricing library available in Excel.

The interface builds on the Python bindings for QuantLib via QuantLib-SWIG.

We use xlOil to make the QuantLib Python objects and functions available in Excel.

The QuantLibXlOil package largely contains wrapper functions in Python which delegate calls to QuantLib constructors and method/function call. The wrapper functions are made available to Excel via xlOil's function decorator. In addition, the package provides converter functions between Excel data types and QuantLib types.

Getting Started

QuantLibXlOil can be installed via pip.

Note: Remove any installation of the classical QuantLib Excel add-in if installed prior to installing QuantLibXlOil.

Setup Python Environment

We recommend setting up a clean Python environment with conda (or venv).

conda create -n xloil python
conda activate xloil

Install QuantLibXlOil and Dependencies

QuantLibXlOil is available via pip.

pip install -U quantlib_xloil

This step also installs the following dependencies:

  • xlOil for interfacing Python and Excel.
  • QuantLib library with Python interface.

Install xlOil Excel Add-in

xlOil comes with an installer script which can be run on the command line within the Python environment.

xloil install

Above step installs the xlOil Excel add-in and an xlOil.ini configuration file. Details on xlOil installation can also be found here.

Installation can be verified by opening Excel with a blank workbook. Type =xloVersion() in an empty cell and enter. This should display an output similar to the one below.

image

Load QuantLibXlOil Functions

To make the QuantLib wrapper functions available in Excel, the xlOil add-in needs to be configured.

xlOil comes with a custom menu ribbon xlOil Py. The menu block Modules contains a text input field Load Modules.

Add QuantLib_xlOil to the text field Load Modules. Use comma separation without spaces. The resulting entry in Load Modules should be

xloil.xloil_ribbon,QuantLib_xlOil

image

Restart Excel and open a blank workbook.

Test the QuantLib functions by entering =qlVersion() in an empty cell. This should produce a result like 1.41.

image

Now, you are all set for QuantLib in Excel.

Why Another QuantLib Interface?

Excel is widely adapted in the industry as calculation tool and GUI for a large variety of use cases.

QuantLib has the classical QuantLibXL interface for Excel. However, QuantLibXL was last updated for QuantLib v1.22 (April 2021). The QuantLibXL object and interface specification is quite complex and closely linked to QuantLib internals. This makes maintenance quite challenging.

The QuantLib Python interface is probably the best QuantLib interface in terms of coverage and maintenance. With the QuantLibXlOil package, we aim at leveraging the matured QuantLib Python interface.

As an additional objective, we want to disentangle QuantLib developments from Excel interface development. This is particularly relevant for QuantLib C++ internals. For example, switching from boost::something to std::something should not affect the Excel interface. This motivates building on top of an existing high-level language interface.

Linking between Python and Excel is a well understood task. There are several tools that implement that bridge. We opt for xlOil because it is open-source and works well for the use cases tested.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

quantlib_xloil-0.0.7.tar.gz (812.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

quantlib_xloil-0.0.7-py3-none-any.whl (93.0 kB view details)

Uploaded Python 3

File details

Details for the file quantlib_xloil-0.0.7.tar.gz.

File metadata

  • Download URL: quantlib_xloil-0.0.7.tar.gz
  • Upload date:
  • Size: 812.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for quantlib_xloil-0.0.7.tar.gz
Algorithm Hash digest
SHA256 e722d56210f1bbd56a006bd42b28ce2b8dd05dafe330a0149d688edd1f45598c
MD5 1ab97b48380c9f9a55b16957eab45876
BLAKE2b-256 8bf33bbdfab101be4f49d5fda7fdb48f09e5a1fe368e956ad932c51c80bda231

See more details on using hashes here.

File details

Details for the file quantlib_xloil-0.0.7-py3-none-any.whl.

File metadata

  • Download URL: quantlib_xloil-0.0.7-py3-none-any.whl
  • Upload date:
  • Size: 93.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for quantlib_xloil-0.0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 4fa890917464c1e0b2385c86d7705d3396a6872458f0f5015a2c3766c2abad53
MD5 58321333340001e7cc4a08252d648cb6
BLAKE2b-256 d700156f7ed96accecbcff1a66d66c5fbc1d3c4cdea2f1e4f15688a3e807b049

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page