Metadata-Version: 2.4
Name: optipricepro-jax-gui
Version: 1.0.2
Summary: OptiPricePro JAX Studio - standalone graphical pricing workbench
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: streamlit>=1.30
Requires-Dist: requests>=2.31
Requires-Dist: pandas>=1.5
Requires-Dist: numpy>=1.24

# OptiPricePro JAX Studio

A standalone graphical pricing workbench for the OptiPricePro JAX service.

Studio is a complete product on its own: it needs no other OptiPricePro
package and no separate API licence. It performs no pricing on your machine —
it collects the product, model and simulation settings you choose, sends them
to the JAX pricing service over HTTPS, and displays the results.

## Installation

One wheel, one key:

    conda create -n optipricepro-jax-studio python=3.11 -y
    conda activate optipricepro-jax-studio

    python -m pip install optipricepro_jax_gui-1.0.0-py3-none-any.whl

## Running

    set OPTIPRICEPRO_JAX_API_KEY=sk_live_YOUR_JAX_STUDIO_KEY
    optipricepro-jax-gui

Check your licence and connection at any time:

    optipricepro-jax-gui-check

To choose a different local port, pass Streamlit options straight through:

    optipricepro-jax-gui --server.port 8600

## What you can price

- European, American and Bermudan exercise, plus the four native lookback
  exercise classes
- Vanilla, digital, arithmetic-Asian, geometric-Asian, floating-strike and
  rolling-average underlyings
- Barrier and lookback wrappers in all five composition orders, with 17
  barrier classes including continuously monitored variants
- Stochastic rates (Ho-Lee, Vasicek, CIR, Extended CIR), stochastic
  volatility (Heston, Bates), stochastic dividends, sentiment and sentiment
  volatility, with uploaded correlation matrices and term-structure curves
- Stock jumps, quasi-random and variance-reduction simulation families
- Importance sampling and analytical control variates
- The full gradient and Hessian, with named Greeks

Each result shows the value, its error, replication prices where applicable,
control-variate diagnostics, headline Greeks, the complete gradient and
Hessian, retained-variable metadata, and the resolved configuration.

## Configuration reference

| Variable | Purpose |
| --- | --- |
| `OPTIPRICEPRO_JAX_API_KEY` | Your JAX Studio licence key (or enter it in the sidebar) |
| `OPTIPRICEPRO_JAX_API_URL` | Override the service endpoint (rarely needed) |
| `OPTIPRICEPRO_JAX_PRICE_PATH` | Override the pricing path if your deployment differs |

These names are specific to this product, so it can be installed alongside the
Pandas client and Pandas Studio without keys or endpoints interfering.

## A note on the hard payoff

The **Hard payoff** option, on by default, uses the exact payoff formulation
that reproduces the validated benchmarks. Unticking it enables a smoothed
payoff controlled by a smoothing beta, which changes the value slightly. Leave
it on unless you specifically want the smoothed formulation.

## Licence and support

Your Studio key is issued for this product and is metered independently of any
other OptiPricePro licence you may hold. Keep it confidential.

Contact British Asteroid Belt Trading Company with your company name, Python
version and the complete error message if you need assistance.
