Merge pull request #1 from vicaws/release

Release to pypi

.gitignore

@@ -26,6 +26,7 @@ share/python-wheels/
 .installed.cfg
 *.egg
 MANIFEST
+.idea/
 
 # PyInstaller
 #  Usually these files are written by a python script from a template

README.md

@@ -14,26 +14,27 @@ Some examples of arbitrage repair are shown as below:
 
 ![image](https://user-images.githubusercontent.com/32545513/83334755-9666ad80-a2a0-11ea-9910-34137539517b.png)
 
->An arbitrage-free normalised call price surface
-><img src="https://render.githubusercontent.com/render/math?math=(T,k) \mapsto c(T,k)">
->should satisfy some shape constraints. Assuming smooth surface function
-><img src="https://render.githubusercontent.com/render/math?math=c(T,k) \in C^{1,2} (\mathbb{R}_{ %3E 0} \times \mathbb{R}_{\geq 0})">,
->then these shape constraints are
->- Positivity: <img src="https://render.githubusercontent.com/render/math?math=0 \leq c \leq 1">
->- Monotonicity: <img src="https://render.githubusercontent.com/render/math?math=-1\leq\partial c / \partial k \leq 0">, <img src="https://render.githubusercontent.com/render/math?math=\partial c / \partial T \geq 0">
->- Convexity: <img src="https://render.githubusercontent.com/render/math?math=\partial^2 c / \partial^2 k \geq 0">
+An arbitrage-free normalised call price surface
+<img src="https://render.githubusercontent.com/render/math?math=(T,k) \mapsto c(T,k)">
+should satisfy some shape constraints. Assuming smooth surface function
+<img src="https://render.githubusercontent.com/render/math?math=c(T,k) \in C^{1,2} (\mathbb{R}_{ %3E 0} \times \mathbb{R}_{\geq 0})">,
+then these shape constraints are
+- Positivity: <img src="https://render.githubusercontent.com/render/math?math=0 \leq c \leq 1">
+- Monotonicity: <img src="https://render.githubusercontent.com/render/math?math=-1\leq\partial c / \partial k \leq 0">, <img src="https://render.githubusercontent.com/render/math?math=\partial c / \partial T \geq 0">
+- Convexity: <img src="https://render.githubusercontent.com/render/math?math=\partial^2 c / \partial^2 k \geq 0">
 
 ## Code
 
-### Installation of pre-requisites
+### Installation
 
-It is recommended to create a new environment and install pre-requisite
-packages. All packages in requirement.txt are compatible with Python 3.8.x.
+It is recommended to create a new virtual environment and install from pypi.
 
 >```
->pip install -r requirements.txt
+>pip install arbitragerepair
 >```
 
+**Requirements:** ```Python >= 3.8``` and ```CVXOPT >= 1.3.0```.
+
 ### Usage
 
 While an example can be found in [this jupyter notebook](notebook/example.ipynb),
@@ -46,6 +47,10 @@ the usage of this code consists of the following steps.
 >```
 
 **1.** Normalise strikes and call prices
+
+The inputs are four 1D ```numpy.array``` objects ```T, K, C, F```, which should be of the same length, representing 
+time-to-expiries, strike prices, option prices and forward prices. 
+
 >```
 >normaliser = constraints.Normalise()
 >normaliser.fit(T, K, C, F)

arbitragerepair/__init__.py

@@ -0,0 +1,2 @@
+from .constraints import *
+from .repair import *

arbitragerepair/repair.py

@@ -141,10 +141,10 @@ def l1ba(mat_A, vec_b, C, spread=None, solver='glpk'):
             delta0 = 1./len(delta_ask) if delta0 > 1./len(delta_ask) else delta0
             delta0 = 1e-8 if delta0 < 1e-8 else delta0
         except ValueError:
-            raise  ValueError('Please ensure that the spread input has legal '
-                              'format! It should contain two arrays/lists, one '
-                              'for bid-reference spread, one for ask-reference '
-                              'spread.')
+            raise ValueError('Please ensure that the spread input has legal '
+                             'format! It should contain two arrays/lists, one '
+                             'for bid-reference spread, one for ask-reference '
+                             'spread.')
 
         # Construct required quantities for the LP
         I = _np.eye(n_quote)

requirements.txt

@@ -1,4 +1,3 @@
-cvxopt==1.3.0
-matplotlib==3.2.2
-numpy==1.19.0
-pandas==1.0.5
+cvxopt>=1.3.0
+numpy>=1.19.0
+pandas>=1.0.5

setup.cfg

@@ -0,0 +1,2 @@
+[metadata]
+description_file = README.md

setup.py

@@ -0,0 +1,30 @@
+import os
+from setuptools import setup
+
+here = os.path.realpath(os.path.dirname(__file__))
+with open(os.path.join(here, 'README.md')) as f:
+    readme = f.read()
+
+setup(
+    name='arbitragerepair',
+    packages=['arbitragerepair'],
+    description='Model-free algorithms of detecting and repairing spread, butterfly and calendar arbitrages in European option prices.',
+    long_description=readme,
+    long_description_content_type="text/markdown",
+    install_requires=[
+        'cvxopt>=1.3.0',
+        'numpy>=1.19.0',
+        'pandas>=1.0.5'
+    ],
+    python_requies='>=3.8',
+    url='https://github.com/vicaws/arbitragerepair',
+    version='1.0.2',
+    license='MIT',
+    author='Victor Wang',
+    author_email='wangsheng.victor@gmail.com',
+    keywords=['option', 'arbitrage', 'quantitative finance', 'data cleansing', 'asset pricing'],
+    classifiers=[
+        'Programming Language :: Python :: 3',
+        'License :: OSI Approved :: MIT License'
+    ]
+)