pyfeng 0.1.2

Python Financial Engineering

PyFENG: Python Financial ENGineering

PyFENG is the python implemention of the standard option pricing models in financial engineering.

• Black-Scholes-Merton (and displaced diffusion)
• Bachelier (Normal)
• Constant-elasticity-of-variance (CEV)
• Stochastic-alpha-beta-rho (SABR)
• Hyperbolic normal stochastic volatility model (NSVh)

About the package

• It assumes variables are numpy arrays. So the computations are naturally vectorized.
• It is purely in Python (i.e., no C, C++, cython).
• It is implemented with python class.
• It is intended for, but not limited to, academic use. By providing reference models, it saves researchers' time.

Instllation

pip install pyfeng

Upgrade

pip install --upgrade pyfeng

Code Snippets

In [1]:

import numpy as np
import pyfeng as pf
m = pf.Bsm(sigma=0.2, intr=0.05, divr=0.1)
m.price(np.arange(80, 121, 10), 100, 1.2)

Out [1]:

array([15.71361973,  9.69250803,  5.52948546,  2.94558338,  1.48139131])

In [2]:

sigma = np.array([0.2, 0.3, 0.5])[:, None]
m = pf.Bsm(sigma, intr=0.05, divr=0.1) # sigma in axis=0
m.price(np.array([90, 100, 110]), 100, 1.2, cp=np.array([-1,1,1]))

Out [2]:

array([[ 5.75927238,  5.52948546,  2.94558338],
       [ 9.4592961 ,  9.3881245 ,  6.45745004],
       [16.812035  , 17.10541288, 14.10354768]])

Author

• Prof. Jaehyuk Choi (Peking University HSBC Business School)

Others

• See also FER: Financial Engineering in R developed by the same author. Not all models in PyFENG is implemented in FER. FER is a subset of PyFENG.