monte-carlo-contracts 0.7.0

Composable financial contracts with Monte Carlo valuation

Monte Carlo Contracts

Composable financial contracts with Monte Carlo valuation. This module employs ideas from How to Write a Financial Contract by S. L. Peyton Jones and J-M. Eber. However, the implementation is not based on functional programming but rather using an object oriented approach. Also, this implementation is tailored towards Monte Carlo based cashflow generation whereas the paper favours more general methods.

Features

• Composition of financial contracts using elementary contracts Zero, One, Give, Scale, And, When, Cond, Anytime and Until
• Boolean and real valued observables (stochastic processes) to be referenced by contracts
• Cashflow generation for composed contracts given simulation models on fixed dategrids

Examples

• Equity Options
• FX Options
• Working with Observables
• Cashflow types

Install

You can install monte-carlo-contracts using pip with

pip3 install monte-carlo-contracts

or you can simply download mcc.py and then run it using python3 with

python3 mcc.py

History

See HISTORY.md.

Credits

Main developer is luphord [e-mail]. cookiecutter-pyscript is used as project template.

History

0.7.0 (2022-03-13)

• BREAKING CHANGE: ObservableFloat.simulate and ObservableBool.simulate now accept a DateIndex first_observation_idx as first argument, Contract classes will pass acquisition_idx; this allows observations to depend on the time of entering a contract, e.g. "maximum spot since acquisition"
• BREAKING CHANGE: FixedAfter fixes composed observable after (including) first_observation_idx, not from the beginning
• Add operator overloading for Contract classes, i.e. you can now do One("USD") - One("EUR") | 1.2 * One("GBP") instead of Or(And(One("USD"), Give(One("EUR"))), Scale(1.2, One("GBP")))
• Maximum and Minimum observables to observe the larger and smaller value of two observables at the same time on the same path
• RunningMax and RunningMin observables to observe running extreme values from first_observation_idx onwards
• Support Python 3.10
• Make use of type annotations added to numpy

0.6.0 (2022-03-04)

• BREAKING CHANGE: Make SimpleCashflows a pandas.DataFrame
• Run notebooks in automated tests using nbval
• Migrate from travis-ci to GitHub Actions
• Explicitly support Python 3.8 and 3.9
• Move history to HISTORY.md

0.5.0 (2020-11-08)

• BREAKING CHANGE: Add simulated_rates to Model (included in constructor); pass an empty dict for simulated_rates to adapt your code
• BREAKING CHANGE: BrownianMotion and GeometricBrownianMotion generalized to dynamic mean/drift; pass mu_t = lambda t: mu * t to adapt your code
• LinearRate observable supported by TermStructureModel
• First steps towards term structure models
• FixedAfter observable to keep an observable fixed after a condition is true
• Observables support arithmetic operations (binary +, -, *, /, ** and unary -) with other observables as well as constants (also right operators work)
• Working with Observables example notebook

0.4.0 (2020-11-04)

• Discounting (Model.discount)
• Evaluation (Model.evaluate)
• String representations for contracts and observables

0.3.0 (2020-10-23)

• Simulation of basic contract Until
• Currency conversion of IndexedCashflows
• Or contract supports multiple currencies
• ObservableFloat supports <, <=, > and >= operators with float or other ObservableFloat instances
• ObservableBool supports ~, & and | operators for combined conditions
• Equity Options and FX Options examples

0.2.0 (2020-10-11)

• Simulation of basic contracts Zero, One, Give, Scale, And, When and Cond
• Partial simulation of Or contract
• Float observables Stock and FX
• Boolean observables At
• SimulatedCashflows and model-bound IndexedCashflows to represent cashflows
• Basic Model allowing the generation of cashflows for the contracts above

0.1.0 (2020-09-22)

• Created using cookiecutter-pyscript