optstrat

A small Python library for building options strategies.

It lets you define a strategy leg by leg, calculate the payoff at expiration, and compute max profit and max loss. All legs are assumed to share the same expiration.

Installation

pip install optstrat

For plotting examples:

pip install matplotlib

Usage example

Plot payoff using matplotlib:

import matplotlib.pyplot as plt

from optstrat import OptionStrategy

strategy = OptionStrategy("Covered Call", 100, contract_size=100)

# 100 shares + short 1 call contract
strategy.long_underlying(100, quantity=100)
strategy.short_call(110, 2.5, quantity=1)

max_profit, max_loss = strategy.max_profit_and_loss()
net_cost = strategy.net_cost()

print(f"Max Profit: {max_profit}")
print(f"Max Loss: {max_loss}")
print(f"Cost of entering position ${net_cost}")
for leg in strategy.legs:
    print(leg)

plt.plot(strategy.underlying_prices, strategy.payoffs)
plt.title(strategy.name)
plt.fill_between(
    strategy.underlying_prices,
    strategy.payoffs,
    where=(strategy.payoffs > 0),
    facecolor='g',
    alpha=0.4,
)
plt.fill_between(
    strategy.underlying_prices,
    strategy.payoffs,
    where=(strategy.payoffs < 0),
    facecolor='r',
    alpha=0.4,
)
plt.xlabel(r'$S_T$')
plt.ylabel('P&L')
plt.show()

Notes

• spot_range controls the simulated range around S0 as a decimal percentage.
• underlying_prices represents possible underlying prices at expiration.
• quantity is the number of contracts for option legs and the number of shares for underlying legs.
• contract_size applies only to option legs.
• strategy.net_cost() computes the net cost of entering the position.
• strategy.max_profit_and_loss() computes max profit and max loss at expiration.
• All legs are assumed to share the same expiration.