Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required)

Overview

Binomial Option Pricing Calculator

Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required)

Background

A derivative is a financial instrument that derives its value from the price of an underlying asset. An option gives the owner the ability to buy or sell the underlying asset at pre-determined price. An option that allows the holder to buy the asset at the pre-determined price (also known as the exercise or strike price) is called a call option. An option that lets the owner sell the underlying asset at the strike price is called a put option. There are three key types of options, a European option allows the holder to exercise ('redeem') the option only at maturity of the option. An American option can be exercised any time before maturity. A Bermudan option is exercisable at pre-deteremined dates decided at the creation of the option.

The binomial pricing method is one of the three most common methods used to value options - the others being the Black-Scholes model and a Monte Carlo simulation. The method predicts the price of the underlying asset at intervals (branches) between now and maturity of the option contract. This creates a tree showing the price movements of the asset, which can be used to find the fair value of the option. Unlike Black-Scholes, the binomial method allows the intrinsic value of the option to be calculated prior to maturity, better representing the value of American and Bermudan options which have the option of early exercise.

Pricing options using this method is done by:

  1. Determining the magnitude that stock prices will rise or fall between each branch.
  2. Calculating the probability that the stock price will move upwards or downward.
  3. Forming the binomial stock price tree with the specified number of branches.
  4. Calculate the payoff of the option at maturity.
  5. Working backwards, value the option by discounting the value of the option at the following nodes using. If the option is American or Bermudan and exercisible at that branch, then the value of the option if it was exercised is calculated, if it is greater than the discoutned value, it becomes the calculated value of the branch.
  6. The value derived at the top of the tree is the fair value of the option today.

Features of the Script

  • Does not require any libraries - it will work in base python3 and immune to changes in libraries
  • Option type is specified as a parameter allowing easy implementations
  • Returns and displays the calculated stock tree

The following assumptions are made by the model:

  • No dividends are paid across the option's life
  • Risk-Free rate is constant across the option's life
  • The price will move up or down each period

Variables and Paramaters

The variables required are:

Name Symbol Description
Stock Price s The current price of the underlying asset (time 0)
Exercise Price x The strike price of the option contract
Time to Maturity t The time until maturity of the option contract (in years)
Risk-Free Rate r The current risk-free rate
Branches/Steps b The number of branches used to value the option
Volatility v The volatility of the price movements in the underlying asset

Optional variables are:

Name Symbol Description
Option Nationality nat 'A' for American (default), 'B' for Bermudan, 'E' for European
Option Type typ 'C' for Call (default), 'P' for Put
Print Results prnt True to enable printing (default), False to disable
Exercisible Periods exP The branches that a Bermudan option can be exercised

Related Projects

Beta calculator with stock data downloader: https://github.com/sammuhrai/beta-calculator

Disclaimer

Script is for educational purposes and is not to be taken as financial advice.

Owner
sammuhrai
sammuhrai
Business Intelligence (BI) in Python, OLAP

Open Mining Business Intelligence (BI) Application Server written in Python Requirements Python 2.7 (Backend) Lua 5.2 or LuaJIT 5.1 (OML backend) Mong

Open Mining 1.2k Dec 27, 2022
First and foremost, we want dbt documentation to retain a DRY principle. Every time we repeat ourselves, we waste our time. Second, we want to understand column level lineage and automate impact analysis.

dbt-osmosis First and foremost, we want dbt documentation to retain a DRY principle. Every time we repeat ourselves, we waste our time. Second, we wan

Alexander Butler 150 Jan 06, 2023
Desafio 1 ~ Bantotal

Challenge 01 | Bantotal Please read the instructions for the challenge by selecting your preferred language below: Español Português License Copyright

Maratona Behind the Code 44 Sep 28, 2022
Data Competition: automated systems that can detect whether people are not wearing masks or are wearing masks incorrectly

Table of contents Introduction Dataset Model & Metrics How to Run Quickstart Install Training Evaluation Detection DATA COMPETITION The COVID-19 pande

Thanh Dat Vu 1 Feb 27, 2022
TheMachineScraper 🐱‍👤 is an Information Grabber built for Machine Analysis

TheMachineScraper 🐱‍👤 is a tool made purely for analysing machine data for any reason.

doop 5 Dec 01, 2022
Single-Cell Analysis in Python. Scales to >1M cells.

Scanpy – Single-Cell Analysis in Python Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It inc

Theis Lab 1.4k Jan 05, 2023
This is a tool for speculation of ancestral allel, calculation of sfs and drawing its bar plot.

superSFS This is a tool for speculation of ancestral allel, calculation of sfs and drawing its bar plot. It is easy-to-use and runing fast. What you s

3 Dec 16, 2022
Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

Amundsen 3.7k Jan 03, 2023
Finds, downloads, parses, and standardizes public bikeshare data into a standard pandas dataframe format

Finds, downloads, parses, and standardizes public bikeshare data into a standard pandas dataframe format.

Brady Law 2 Dec 01, 2021
Uses MIT/MEDSL, New York Times, and US Census datasources to analyze per-county COVID-19 deaths.

Covid County Executive summary Setup Install miniconda, then in the command line, run conda create -n covid-county conda activate covid-county conda i

Ahmed Fasih 1 Dec 22, 2021
Python for Data Analysis, 2nd Edition

Python for Data Analysis, 2nd Edition Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media Buy

Wes McKinney 18.6k Jan 08, 2023
Pip install minimal-pandas-api-for-polars

Minimal Pandas API for Polars Install From PyPI: pip install minimal-pandas-api-for-polars Example Usage (see tests/test_minimal_pandas_api_for_polars

Austin Ray 6 Oct 16, 2022
Shot notebooks resuming the main functions of GeoPandas

Shot notebooks resuming the main functions of GeoPandas, 2 notebooks written as Exercises to apply these functions.

1 Jan 12, 2022
Methylation/modified base calling separated from basecalling.

Remora Methylation/modified base calling separated from basecalling. Remora primarily provides an API to call modified bases for basecaller programs s

Oxford Nanopore Technologies 72 Jan 05, 2023
Senator Trades Monitor

Senator Trades Monitor This monitor will grab the most recent trades by senators and send them as a webhook to discord. Installation To use the monito

Yousaf Cheema 5 Jun 11, 2022
PySpark bindings for H3, a hierarchical hexagonal geospatial indexing system

h3-pyspark: Uber's H3 Hexagonal Hierarchical Geospatial Indexing System in PySpark PySpark bindings for the H3 core library. For available functions,

Kevin Schaich 12 Dec 24, 2022
Display the behaviour of a realtime program with a scope or logic analyser.

1. A monitor for realtime MicroPython code This library provides a means of examining the behaviour of a running system. It was initially designed to

Peter Hinch 17 Dec 05, 2022
Picka: A Python module for data generation and randomization.

Picka: A Python module for data generation and randomization. Author: Anthony Long Version: 1.0.1 - Fixed the broken image stuff. Whoops What is Picka

Anthony 108 Nov 30, 2021
Python dataset creator to construct datasets composed of OpenFace extracted features and Shimmer3 GSR+ Sensor datas

Python dataset creator to construct datasets composed of OpenFace extracted features and Shimmer3 GSR+ Sensor datas

Gabriele 3 Jul 05, 2022
Using approximate bayesian posteriors in deep nets for active learning

Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components

ElementAI 687 Dec 25, 2022