Added pricer price

Author: lsbardel

.github/copilot-instructions.md

@@ -27,3 +27,4 @@ applyTo: '/**'
 * The documentation for quantflow is available at `https://quantflow.quantmid.com`
 * Documentation is built using [mkdocs](https://www.mkdocs.org/) and stored in the `docs/` directory. The documentation source files are written in markdown format.
 * Do not use em dashes (—) in documentation files or docstrings. Use colons, parentheses, or restructure the sentence instead.
+* Math in documentation and docstrings uses `$...$` for inline and `$$...$$` or `\begin{equation}...\end{equation}` for block equations. Do not use `.. math::` or `:math:` (RST syntax).

.gitignore

@@ -37,3 +37,4 @@ _build
 
 # builds
 app/docs
+docs/examples_output

.vscode/launch.json

@@ -14,7 +14,7 @@
             "args": [
                 "-x",
                 "-vvv",
-                "quantflow_tests/test_options.py",
+                "quantflow_tests/test_options_pricer.py",
             ]
         },
     ]

Makefile

@@ -27,6 +27,7 @@ marimo:				## Run marimo for editing notebooks
 .PHONY: docs
 docs:				## build documentation
 	@cp docs/index.md readme.md
+	@uv run ./dev/build-examples
 	@uv run mkdocs build
 
 .PHONY: docs-serve

app/volatility_surface.py

@@ -43,12 +43,19 @@ def _(mo):
 
 
 @app.cell
-async def _():
+def _(mo):
+    inverse = mo.ui.checkbox(value=True, label="Inverse options")
+    inverse
+    return (inverse,)
+
+
+@app.cell
+async def _(inverse):
     import pandas as pd
     from quantflow.data.deribit import Deribit
 
     async with Deribit() as cli:
-        loader = await cli.volatility_surface_loader("eth", exclude_open_interest=0)
+        loader = await cli.volatility_surface_loader("eth", exclude_open_interest=0, inverse=inverse.value)
 
     # build the volatility surface
     surface = loader.surface()

dev/build-examples

@@ -0,0 +1,28 @@
+#!/usr/bin/env python
+"""Run all example scripts in docs/examples/ and capture their stdout to .out files."""
+import subprocess
+import sys
+from pathlib import Path
+
+out_dir = Path("docs/examples_output")
+out_dir.mkdir(exist_ok=True)
+
+examples = sorted(Path("docs/examples").glob("*.py"))
+failed = []
+
+for script in examples:
+    out_file = out_dir / script.with_suffix(".out").name
+    print(f"running {script} -> {out_file}")
+    result = subprocess.run(
+        [sys.executable, str(script)],
+        capture_output=True,
+        text=True,
+    )
+    if result.returncode != 0:
+        print(f"FAILED: {script}\n{result.stderr}", file=sys.stderr)
+        failed.append(script)
+    else:
+        out_file.write_text(result.stdout)
+
+if failed:
+    sys.exit(1)

docs/api/options/black.md

@@ -5,7 +5,9 @@ $$
   k = \log{\frac{K}{F}}
 $$
 
-where \(K\) is the strike price and \(F\) is the forward price of the underlying asset.
+where $K$ is the strike price and $F$ is the forward price of the underlying asset.
+We also refers to this log-strike as `moneyness`, since it is zero for at-the-money (ATM) options,
+negative for in-the-money (ITM) call options, and positive for out-of-the-money (OTM) call options.
 
 
 ::: quantflow.options.bs.black_price
@@ -16,6 +18,8 @@ where \(K\) is the strike price and \(F\) is the forward price of the underlying
 
 ::: quantflow.options.bs.black_vega
 
+::: quantflow.options.bs.BlackSensitivities
+
 ::: quantflow.options.bs.implied_black_volatility
 
 ::: quantflow.options.bs.ImpliedVols

docs/api/options/pricer.md

@@ -7,3 +7,5 @@ different stochastic volatility models.
 ::: quantflow.options.pricer.OptionPricer
 
 ::: quantflow.options.pricer.MaturityPricer
+
+::: quantflow.options.pricer.ModelOptionPrice

docs/examples/heston_volatility_pricer.out

@@ -0,0 +1,8 @@
+{
+  "option_type": "call",
+  "moneyness": 0.0,
+  "ttm": 1.0,
+  "price": 0.19225250948685713,
+  "delta": 0.4081907106007492,
+  "gamma": 0.4063832911177639
+}

docs/examples/heston_volatility_pricer.py

@@ -0,0 +1,25 @@
+from quantflow.options.inputs import OptionType
+from quantflow.options.pricer import OptionPricer
+from quantflow.sp.heston import HestonJ
+from quantflow.utils.distributions import DoubleExponential
+
+pricer = OptionPricer(
+    model=HestonJ.create(
+        DoubleExponential,
+        vol=0.5,
+        kappa=2,
+        rho=-0.2,
+        sigma=0.8,
+        jump_fraction=0.5,
+        jump_asymmetry=0.2,
+    )
+)
+
+# Price an ATM call option at time to maturity 1.0
+price = pricer.price(
+    option_type=OptionType.call,
+    strike=100.0,
+    forward=100.0,
+    ttm=1.0,
+)
+print(price.model_dump_json(indent=2))