derpy 0.1.1

Financial derivatives and portfolio analysis tools for python

derpy

Financial derivatives and portfolio analysis tools for python

• Free software: MIT license

• Documentation: https://derpy.readthedocs.io.

How to get up and running

to include the module in your project, you can simply use pip install derpy then in your python project

import derpy
print(derpy.__version__) # returns '0.0.1'

Example uses

Bonds

from derpy import bond as bd

px = 95.0428
face_val = 100.0
mat = 1.5
cpn_frq = 2
cpn_rate = 5.25
ytm = 5.5

print('    Price: {}'.format(bd.bond_price(face_val, mat, ytm, cpn_rate, cpn_frq)))
print('    Yield: {}'.format(bd.bond_ytm(px, face_val, mat, cpn_rate, cpn_frq)))
print('   ModDur: {}'.format(bd.bond_duration(px, face_val, mat, cpn_rate, cpn_frq)[0]))
print('   MacDur: {}'.format(bd.bond_duration(px, face_val, mat, cpn_rate, cpn_frq)[1]))
print('Convexity: {}'.format(bd.bond_convexity(px, face_val, mat, cpn_rate, cpn_frq)))

Options

from derpy.options import black_scholes_merton as bsm

# usage method 1: use function wrapper
input = ['call', 20, 21, 0.20, 0.1, 0.0002, 0]
call_price = bsm.option_pricing(bsm.euro_option, input)
call_gamma = bsm.option_pricing(bsm.gamma, input)

# usage method 2: call individual functions
put_price = bsm.euro_option('put', 20, 21, 0.2, 0.1, 0.0002) # div_yield is optional
put_gamma = bsm.gamma('put', 20, 21, 0.2, 0.1, 0.0002, 0.0001)

print(call_price)  # return 0.16384395..
print(call_gamma)  # return 0.23993880..
print(put_price)  # return 1.16342..
print(put_gamma)  # return 0.2399107..

Portfolio analysis

from derpy import portfolio as pt

securities = ['AAA', 'BBB']
positions = [[11, 10], [12, 10], [13, 10], [13, 11], [13, 12]]
prices = [[10, 10], [11, 10], [12, 10], [12, 10], [12, 10]]
dates = ['2018-07-01', '2018-08-01', '2018-09-01', '2018-10-01', '2018-11-01']

df_positions = pd.DataFrame(data=positions, columns=securities, index=dates)
df_prices = pd.DataFrame(data=prices, columns=securities, index=dates)

p = pt.Portfolio(names=securities, positions=df_positions, prices=df_prices)

print(p.sec_values())
print(p.sec_weights())
print(p.portfolio_value())
print(p.portfolio_returns())

History

0.1.0 (2018-09-19)

• Released option pricing

• Released portfolio analysis

• Added testing for Options and Portfolios