January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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How it works...
In Step 2, we defined the parameters that we used for this recipe:
- S_0: Initial stock price
- K: Strike price, that is, the one we can buy/sell for at maturity
- r: Annual risk-free rate
- sigma: Underlying stock volatility (annualized)
- T: Time until maturity in years
- N: Number of time increments for simulations
- n_sims: Number of simulated sample paths
- discount_factor: Discount factor, which is used to calculate the present value of the future payoff
In Step 3, we defined a function for calculating the option premium using the closed-form solution to the Black-Scholes model (for non-dividend-paying stocks). We used it in Step 4 to calculate the benchmark for the Monte Carlo simulations.
The analytical solution to the call and ...
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