Upgraded docs

Author: lsbardel

app/volatility_surface.py

@@ -0,0 +1,58 @@
+import marimo
+
+__generated_with = "0.20.4"
+app = marimo.App(width="medium")
+
+
+@app.cell
+def _():
+    import marimo as mo
+    from app.utils import nav_menu
+    nav_menu()
+    return (mo,)
+
+
+@app.cell(hide_code=True)
+def _(mo):
+    mo.md(r"""
+    # Volatility Surface
+
+    In this notebook we illustrate the use of the Volatility Surface tool in the library. We use [deribit](https://docs.deribit.com/) options on ETHUSD as example.
+
+    The library provide a volatility surface loader for Deribit. This code loads the surface as a [VolSurfaceLoader](api/options/vol_surface/#quantflow.options.surface.VolSurfaceLoader):
+
+    ```python
+    from quantflow.data.deribit import Deribit
+
+    async with Deribit() as cli:
+        loader = await cli.volatility_surface_loader("eth", exclude_open_interest=0)
+    ```
+    """)
+    return
+
+
+@app.cell
+async def _():
+    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)
+
+    # build the volatility surface
+    surface = loader.surface()
+    # calculate black implied volatilities
+    surface.bs()
+    # display inputs
+    surface_inputs = surface.inputs()
+    pd.DataFrame([i.model_dump() for i in surface_inputs.inputs])
+    return
+
+
+@app.cell
+def _():
+    return
+
+
+if __name__ == "__main__":
+    app.run()

docs/api/data/deribit.md

@@ -9,3 +9,4 @@ from quantflow.data.deribit import Deribit
 ```
 
 ::: quantflow.data.deribit.Deribit
+

docs/api/data/index.md

@@ -1,7 +1,7 @@
 # Data fetching
 
 
-The :mod:`quantflow.data` module provides classes and functions for fetching data from various sources.
+The `quantflow.data` module provides classes and functions for fetching data from various sources.
 To use the module the package must be installed with the optional `data` extra.
 ```
 pip install quantflow[data]

docs/api/options/vol_surface.md

@@ -9,6 +9,10 @@
 
 ::: quantflow.options.surface.VolSurfaceLoader
 
+::: quantflow.options.surface.VolCrossSectionLoader
+
+::: quantflow.options.surface.Strike
+
 ::: quantflow.options.surface.OptionPrice
 
 ::: quantflow.options.surface.OptionSelection

docs/api/sp/dsp.md

@@ -0,0 +1,3 @@
+# Doubly Stochastic Poisson process
+
+::: quantflow.sp.dsp.DSP

docs/api/utils/index.md

@@ -1 +1,3 @@
-# Utils
+# Utilities
+
+This section contains utility functions and classes that are used throughout the library. They are not meant to be used directly by the user, but they can be useful for advanced users who want to extend the library or understand its inner workings.

docs/api/utils/numbers.md

@@ -0,0 +1,4 @@
+# Numbers
+
+
+::: quantflow.utils.numbers.DecimalNumber

docs/api/utils/types.md

@@ -0,0 +1,6 @@
+# Types
+
+
+::: quantflow.utils.types.FloatArray
+
+::: quantflow.utils.types.FloatArrayLike

docs/bibliography.md

@@ -2,6 +2,36 @@
 
 ---
 
+### carr_madan
+
+Peter Carr, Dilip Madan
+
+[Option Valuation Using the Fast Fourier Transform](https://doi.org/10.1002/(SICI)1097-0261(199904)2:1<61::AID-FUT4>3.0.CO;2-4)
+
+Journal of Computational Finance, 2(4):61-73, 1999
+
+---
+
+### carr_wu
+
+Peter Carr, Liuren Wu
+
+[Time-Changed Lévy Processes and Option Pricing](https://doi.org/10.1016/S0304-405X(03)00171-5)
+
+Journal of Financial Economics, 71(1):113-141, 2004
+
+---
+
+### chourdakis
+
+Kyriakos Chourdakis
+
+[Option Pricing Using the Fractional FFT](https://doi.org/10.21314/JCF.2005.102)
+
+Journal of Computational Finance, 8(2):1-18, 2005
+
+---
+
 ### molnar
 
 Peter Molnar

notebooks/theory/characteristic.md docs/theory/characteristic.mdnotebooks/theory/characteristic.md renamed to docs/theory/characteristic.md

@@ -1,24 +1,12 @@
----
-jupytext:
-  text_representation:
-    extension: .md
-    format_name: myst
-    format_version: 0.13
-    jupytext_version: 1.16.6
-kernelspec:
-  display_name: Python 3 (ipykernel)
-  language: python
-  name: python3
----
-
 # Characteristic Function
 
-The library makes heavy use of [characteristic function](https://en.wikipedia.org/wiki/Characteristic_function_(probability_theory))
+The library makes heavy use of the [characteristic function](https://en.wikipedia.org/wiki/Characteristic_function_(probability_theory))
 concept and therefore, it is useful to familiarize with it.
 
 ## Definition
 
-The characteristic function of a random variable $x$ is the Fourier (inverse) transform of ${\mathbb P}_x$, where ${\mathbb P}_x$ is the distrubution measure of $x$
+The characteristic function of a random variable $x$ is the Fourier (inverse) transform of ${\mathbb P}_x$, where ${\mathbb P}_x$ is the distribution measure of $x$
+
 \begin{equation}
  \Phi_{x,u} = {\mathbb E}\left[e^{i u x}\right] = \int e^{i u s} {\mathbb P}_x\left(ds\right)
 \end{equation}
@@ -33,23 +21,23 @@ The characteristic function of a random variable $x$ is the Fourier (inverse) tr
 * moments of $x$ are given by
 
 \begin{equation}
-    {\mathbb E}\left[x^n\right] = i^{-n} \left.\frac{\Phi_{x, u}}{d u}\right|_{u=0}
+    {\mathbb E}\left[x^n\right] = i^{-n} \left.\frac{d\Phi_{x, u}}{d u}\right|_{u=0}
 \end{equation}
 
-## Covolution
+## Convolution
 
-The characteristic function is a great tool for working with linear combination of random variables.
+The characteristic function is a great tool for working with linear combinations of random variables.
 
 * if $x$ and $y$ are independent random variables then the characteristic function of the linear combination $a x + b y$ ($a$ and $b$ are constants) is
 
 \begin{equation}
-    \Phi_{ax+bx,u} = \Phi_{x,a u}\Phi_{y,b u}
+    \Phi_{ax+by,u} = \Phi_{x,a u}\Phi_{y,b u}
 \end{equation}
 
 * which means, if $x$ and $y$ are independent, the characteristic function of $x+y$ is the product
 
 \begin{equation}
-    \Phi_{x+x,u} = \Phi_{x,u}\Phi_{y,u}
+    \Phi_{x+y,u} = \Phi_{x,u}\Phi_{y,u}
 \end{equation}
 
 * The characteristic function of $ax+b$ is
@@ -79,11 +67,6 @@ The inversion formula for these distributions is given by
     {\mathbb P}_x\left(x=k\right) = \frac{1}{2\pi}\int_{-\pi}^\pi e^{-iuk}\Phi_{k, u} du
 \end{equation}
 
-```{code-cell}
-
-```
-
-(characteristic-exponent)=
 ## Characteristic Exponent
 
 The characteristic exponent $\phi_{x,u}$ is defined as