Quantitative Analysis using ChatGPT & Python

Focused View

Jothi Prakash Anandan

3:36:13

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1 - Introduction to Stock Market Data Analysis

1 - Introduction.mp4

02:26

2 - What is the stock market why data analysis is important for trading.mp4

03:55

3 - What is ChatGPT and how can it be used for stock market data analysis.mp4

06:13

4 - Overview of the course curriculum.mp4

01:24

2 - Data Collection Storage and Preparation using ChatGPT

5 - Overview of different sources of stock market data.mp4

05:06

6 - Retrieving data from different sources eg APIs CSV files websites.mp4

01:17

7 - Fetching data from Yahoo Finance.mp4

13:38

7 - yahoo-finance-code.zip

8 - Fetching data from Alpha Vantage.mp4

10:12

8 - alpha-vantage-code.zip

9 - Fetching data from Quandl.mp4

05:29

9 - quandle-data-fetch.zip

10 - Scraping data from NSE Educational purpose only.mp4

18:38

10 - nse-india-scraping.zip

11 - Scraping data from Nasdaq Educational purpose only.mp4

20:59

11 - nasdaq-scaping.zip

12 - Storing data in a MySQL database optional using ChatGPT.mp4

08:56

12 - database-storing-example.zip

3 - Technical Indicators ChatGPT

13 - Understanding the basics of technical indicators and how they are used.mp4

08:09

14 - Moving Average using ChatGPT.mp4

12:06

15 - RSI using ChatGPT.mp4

17:58

16 - Bollinger Bands using ChatGPT.mp4

08:17

4 - Strategy Creation Backtesting Performance Measurement using ChatGPT

17 - How a trading strategy is created.mp4

06:07

18 - Creating a Trading Strategy Plan.mp4

12:46

19 - Creating the Trading Strategy.mp4

29:38

19 - pullback-strategy-swing-trading-v2.zip

20 - Performance Measurement.mp4

19:20

5 - Next Steps Conclusion

21 - Next Steps Conclusion.mp4

03:39

Description

Mastering Technical Analysis and Algorithmic Trading in Python using ChatGPT

What You'll Learn?

Use ChatGPT to create technical analysis using Python
Understand various technical indicators and their applications in trading.
Backtest trading strategies and evaluate performance using Python programming language.
Gain practical experience by building and testing trading algorithms in real market conditions.

Who is this for?

Python programmers

Traders, Investors

Students of any level

Stock Market Enthusiasts

What You Need to Know?

Basic Python knowledge

Basic Market Knowledge

Basic Math Concepts

If you know what is ChatGPT, that's enough

More details

Description
The course "Quantitative Analysis using ChatGPT & Python" is designed for individuals interested in learning how to analyze their trading strategies and backtest their trading ideas using Python & ChatGPT. This course provides a practical introduction to algorithmic trading, including the basics of quantitative analysis and technical analysis.
Through a step-by-step approach, this course teaches students how to develop and implement trading strategies using Python. The course starts by introducing the basics of Python programming, data analysis, and visualization, and then moves on to more advanced topics such as statistical modeling, time series analysis, and machine learning.
The course also covers popular trading indicators, such as moving averages, Bollinger Bands, and Relative Strength Index (RSI), and shows students how to implement these indicators in Python to generate trading signals.
In addition, students will learn how to use Python libraries such as pandas, NumPy, and Talib for data analysis and how to backtest their trading strategies.
By the end of the course, students will have a solid understanding of algorithmic trading, backtesting, and the Python programming language, enabling them to develop and implement their own automated trading strategies.
This course is ideal for individuals who have a basic understanding of financial markets and trading concepts and are looking to learn how to automate their trading strategies. Some prior programming experience, preferably in Python, would be helpful but is not required.
Who this course is for:
Python programmers
Traders, Investors
Students of any level
Stock Market Enthusiasts

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• I've been working as a data scientist for over five years now,• I'm also a seasoned algorithmic trader with over five years of experience.• I've developed more than five profitable trading strategies, using everything from statistical analysis to machine learning.• I'm the one who believes data analysis and understanding can make you a successful trader/businessman.

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