README.md

American Option Example Library

Overview

This is an example Python script using Quantlib in order to calculate American Option prices. This is provided purely as an example and is not intended to be used as-is for financial pricing.

Setup

There is a provided Dockerfile and a setup script to configure a virtual environment and generate protobuf code.

You can run setup.sh locally for development purposes and it can also be used in the Dockerfile.

Running locally

Setup the virtual environment

Run setup.sh:

./setup.sh

Generate test data

Generate 1000 example tasks:

.venv/bin/python3 main.py gentasks --count 1000 tasks.jsonl

With the file directly

Directly run pricer with the test data:

.venv/bin/python3 main.py load tasks.jsonl

With gRPC

Run the pricing engine locally on the default port 2002:

.venv/bin/python3 main.py serve

In a separate command prompt, grpcurl with the test data to try it out: to generate JSON test data for the pricing library. This will only send in the first request.

head -n 1 tasks.jsonl | grpcurl -d @ -plaintext localhost:2002 main.PricingService/CalcPrices

Running in a container

Build the container

docker build -t pricer .

Generate test data

Generate 1000 example tasks:

docker run pricer gentasks --count 1000 - > tasks.jsonl

With the file directly

Directly run pricer with the test data:

docker run -v $PWD:/data pricer load /data/tasks.jsonl

With gRPC

Run the pricing engine locally on the default port 2002:

docker run -p 2002:2002 pricer serve

In a separate command prompt, grpcurl with the test data to try it out: to generate JSON test data for the pricing library. This will only send in the first request.

head -n 1 tasks.jsonl | grpcurl -d @ -plaintext localhost:2002 main.PricingService/CalcPrices