.. RatesLib documentation master file. .. raw:: html

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``Rateslib`` is a state-of-the-art **fixed income library** designed for Python. Its purpose is to provide advanced, flexible and efficient fixed income analysis with a high level, well documented API. .. raw:: html

Academic, Personal, or Educational Use	Commercial or Corporate Use
FREE to use and modify.	Banks, Funds, Accountants, Treasuries: Not Licenced. Can purchase a licence extension. $300 per year / per user. contact: rateslib@gmail.com

The techniques and object interaction within *rateslib* were inspired by the requirements of multi-disciplined fixed income teams working, both cooperatively and independently, within global investment banks. Highlights ========== *Curve construction is simple but has huge flexibility* -------------------------------------------------------- Multiple interpolation modes are offered by default and the generalised process for curve solving means very specific pricing artefacts can be accurately modelled with the correct formulations. The framework is accessible and requires minimal configuration. .. container:: twocol .. container:: leftside40 .. code-block:: python usd_curve = Curve( nodes={...}, convention="act360", calendar="nyc", interpolation="log_linear", id="sofr", ) solver = Solver( curves=[usd_curve], instruments=[...], weights=[...], s=[...], ) .. container:: rightside60 .. image:: _static/index_sofr.png :alt: Curve construction is flexible :width: 351 .. raw:: html

*API is designed for users with full documentation* ----------------------------------------------------------------- Although any fixed income library uses complex mathematical processes, the API has been carefully designed to provide a workflow that is very intuitive. In the case of using it for small scale learning items often few parameters and arguments are required. For larger series of curves and more complicated object oriented associations the API signature does not materially change. Best practice is demonstrated in documentation examples. .. code-block:: python xcs = XCS( effective=dt(2022, 2, 14), termination="15M", notional=100e6, float_spread=-10.25, spec="eurusd_xcs", curves=[...], ) # Create a EUR/USD Cross-Ccy Swap xcs.rate(solver=solver) xcs.npv(solver=solver, base="eur") *Wide range of fixed income Instruments available* ---------------------------------------------------- The most recent version of *rateslib* contains the main *Instruments* that dominate linear fixed income products. The large array of input parameters for these gives scope to fully capture the nuances of these products across sectors and geographic regions, capturing aspects like trading calendars, day count conventions, payment delays, etc. New specifications and calendars are continually being added as users enquire. A good example is a **US Treasury Bond**, replicated here with *rateslib* and the equivalent ticket in Bloomberg for reference point. .. ipython:: python ust = FixedRateBond( effective=dt(2023, 8, 15), termination=dt(2033, 8, 15), fixed_rate=3.875, spec="ust" ) # Create a US-Treasury bond ust.price(ytm=4.0, settlement=dt(2025, 2, 14)) ust.duration(ytm=4.0, settlement=dt(2025, 2, 14), metric="risk") .. image:: _static/ust_10y.gif :alt: US Treasury example using the FixedRateBond class :width: 611 *Minimal dependencies to other Python libraries* -------------------------------------------------- The dependencies are to **NumPy**, **Pandas**, and **Matplotlib**. *Rateslib* does not have any dependencies to any automatic differentiation libraries, such as PyAudi or JAX, preferring initially to use its own forward mode module. The test coverage is very high. Licence ======= This library is released under a **Creative Commons Attribution, Non-Commercial, No-Derivatives 4.0 International Licence**. See :ref:`here` for more details. Get Started =========== Move on to the next page to :ref:`Get Started` .. toctree:: :maxdepth: 0 :titlesonly: :hidden: i_get_started.rst i_licence.rst i_guide.rst i_about.rst i_api.rst i_whatsnew.rst