Project 1 Option Pricing Tool
This tool prices one option in three independent ways, so that each method checks the other two.
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Sign inHow this project is built
The whole project consists of these five steps.
- A Monte Carlo engineA price is an average over many possible futures, so the first part draws those futures and reports the error of each estimate.
- A binomial treeA tree gives a second price without random numbers, and it also handles American options that can be used early.
- Black-Scholes with the GreeksThe exact formula becomes the reference for the other two methods, and the Greeks show how the price reacts to its inputs.
- One option, three pricesOnly now can all three methods price the same option, and their agreement is the strongest test of the tool.
- Implied volatility and a small smileOnce the prices are trusted, the last step runs the formula backwards and turns a quoted price into a volatility.
After the last step, all five parts run together in one program,
option_tool.py. What the finished tool does
What the finished tool does
You set an option with its strike, its time and its volatility, and the tool prices it in three independent ways that must agree. It also shows how well a delta hedge protects the seller and turns a market price back into its implied volatility.
What you get
- 01The five steps with their code Each step explains its idea, walks through its code piece by piece and names its limits.
- 02The working tool,
option_tool.pyThe full program in one file, with its settings and experiments to try. - 03Defend it in an interview Typical follow-up questions, each with the reasoning you need to answer it.
- 04Use it with real data Which data the tool needs, how to load it and what to change in the code.