Machine Learning for Algorithmic Trading in Python

Day 1:

1.Setting up the Python environment

2.Familiar with the IDE environment

3. Introduction to Python

4.Getting started with Panda and other Libraries

Day 2:

1.Trend-Following Strategy 1 (single indicator)

2.Trend-Following Strategy 2 (multiple indicators)

3.Mean Reversion Strategy 1 (single indicator)

4.Mean Reversion Strategy 2 (multiple indicators)

Classroom or Live Stream Sessions from NSE India, Mumbai

Day 3:

1. Introduction of Machine Learning and Algorithmic Trading 1.
2. Python for Algorithmic Trading
3. Important Terminologies
4. Calculating returns
5. Technical Requirements for Algorithmic Trading
6. Exploratory Data Analysis on Stock Pricing Data
7. Formulating a Trading Strategy

Day 4:

1.Backtesting a Trading Strategy

2.Visualize the Performance of the Strategy

3.Setting up the broker’s API

4.Algorithmic Trading Strategies

5.Option Greek Calculations

• To empower participants with a deep understanding of machine learning applications in algorithmic trading using python.
• Participants will have acquired the skills  to perform exploratory data analysis on stock pricing data, formulate effective trading strategies, and implementing algorithmic tracing models.
• The bootcamp aims to bridge the gap between theoretical knowledge and practical application, enabling participants to navigate the complexities of algorithmic trading with confidence.

This bootcamp is suitable for individuals with foundational understanding of programming languages concepts and a keen interest in finance and trading.

Whether you are a finance professional looking to enhance your skills or a programmer eager to delve into the world of algorithmic trading, this program is designed to accommodate a diverse range of backgrounds. Participants should have a basic familiarity with python, as the bootcamp will focus on its application in algorithmic trading.