Please refer to the Jupyter notebook for the overview of main features.

The entire project as well as the notebook above is available on GitHub.

## Features

- Modular structure allows to define and plug-in new market instruments.
- Based on multivariate optimization, no bootstrapping.
- Supports arbitrary tenor-basis and cross-currency-basis relationships between curves, as long as the problem is properly constrained.
- Risk engine supports first-order (Jacobian) approximation to full curve rebuild when bumping market instruments.
- Supports the following curve optimization methods:
- Linear interpolation of the logarithm of discount factors (aka piecewise-constant in forward-rate space)
- Linear interpolation of the continuously-compounded zero-rates
- Cubic interpolation of the logarithm of discount factors

## Curve naming conventions

For the purpose of this project, the curves are named in the following way:

**USDLIBOR3M**refers to USD BBA LIBOR reference rate with 3 month tenor**GBPSONIA**refers to overnight GBP SONIA compound reference rate**USDOIS**refers to overnight USD Federals Fund compound reference rate

In a mono-currency context, the reference rates above can be used also for discounting (e.g.

**USDOIS**curve used for discounting of collateralised USD trades and

**USDLIBOR3M**curve for discounting of unsecured USD trades).

In a cross-currency context, the naming convention for discounting curves is as follows:

<CurrencyOfCashFlow>-<RatePaidOnCollateral>Few examples:

**USD-USDOIS**Discounting curve for USD cash-flows of a trade which is collateralised in USD, paying collateral rate linked to USDOIS. Names USD-USDOIS and USDOIS refers to the same curve.**GBP-GBPSONIA**Discounting curve for GBP cash-flows of a trade which is collateralised in GBP, paying collateral rate linked to GBPSONIA. Names GBP- GBPSONIA and GBPSONIA refers to the same curve.**GBP-USDOIS**Cross-currency discounting curve for GBP cash-flows of a trade which is collateralised in USD, paying collateral rate linked to USDOIS.

## TODO

- Solve stages for global optimizer (performance gain)
- Proper market conventions (day count and calendar roll conventions)
- Smoothing penalty functions
- Risk transformation between different instrument ladders
- Split-curve interpolators (different interpolation method for short-end and long-end of the curve)
- Jacobian matrix calculation via AD (performance gain)

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