Algo's Unleashed: A Beginner's Guide to Conquering Code: A Concise Algorithmic Trading Guide with Python

Title Page
Contents
Chapter 1: An Overview of Options Markets
1.1 History of Options Trading
1.2. Options Basics
1.3. Options Pricing Models
1.4. Option Market Structure
1.5. Risk and Portfolio Management with Options
Chapter 2: Basics of Python Programming
2.1 Python Basics
2.2. Object-Oriented Programming in Python
2.3. Essential Python Libraries
2.4 Advanced Python Features
2.5. Development Environment Setup
Chapter 3: Analyzing Time Series in Finance
3.1 The Fabric of Time: Structuring Time Series Data in Python
3.2. Time Series Descriptive Statistics
3.3. Time Series Visualization
3.4 Time Series Decomposition in Python
3.5. Time Series Forecasting Models
Chapter 4: Options Pricing Models in Python
4.1  Building a Black-Scholes Valuation Model
4.2 The Binomial Tree Model for Option Valuation
4.3. Monte Carlo Simulation for Options Pricing
4.4. Volatility Modeling and the Greek
Chapter 5: Statistical Analysis and Machine Learning for Options Trading
5.1 Introduction to Statistical Learning for Finance
5.2. Regression Analysis for Option Pricing
5.3 Classification Algorithms for Trade Signals
5.4. Unsupervised Learning Techniques
5.5 Deep Learning for Options Strategies
Additional Resources
Sample Trading Programs – Step by Step Guide
Sample Trading Program 1 - Generic
Step 1: Import Libraries and Set Up Environment
Step 2: Import and Preprocess Data
Step 3: Feature Engineering
Step 4: Create Labels
Step 5: Prepare Data for Model
Step 6: Build and Train Model
Step 7: Evaluate Model
Step 8: Implement Strategy and Backtest
Python – Complete Program
Sample Trading Program 2 - Generic
Sample Trading Program 3 – Interactive Brokers
Sample Trading Program 4 – Meta Trader