Stock Market Data Analysis Using Chatgpt & Python
Date: 11 May 2023 | Posted by: mitsumi
Stock Market Data Analysis Using Chatgpt & Python
Published 5/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.01 GB | Duration: 3h 36m
Mastering Technical Analysis and Algorithmic Trading in Python using ChatGPT
Published 5/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.01 GB | Duration: 3h 36m
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.
Requirements
Basic understanding of financial markets and investment concepts
Familiarity with programming languages like Python
Understanding of basic mathematical concepts
Familiarity with data analysis and visualization tools such as Pandas, Numpy
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.
Overview
Section 1: Introduction to Stock Market Data Analysis
Lecture 1 Introduction
Lecture 2 What is the stock market & why data analysis is important for trading
Lecture 3 What is ChatGPT and how can it be used for stock market data analysis
Lecture 4 Overview of the course curriculum
Section 2: Data Collection, Storage and Preparation using ChatGPT
Lecture 5 Overview of different sources of stock market data
Lecture 6 Retrieving data from different sources (e.g. APIs, CSV files, websites)
Lecture 7 Fetching data from Yahoo Finance
Lecture 8 Fetching data from Alpha Vantage
Lecture 9 Fetching data from Quandl
Lecture 10 Scraping data from NSE (Educational purpose only)
Lecture 11 Scraping data from Nasdaq (Educational purpose only)
Lecture 12 Storing data in a MySQL database (optional) using ChatGPT
Section 3: Technical Indicators & ChatGPT
Lecture 13 Understanding the basics of technical indicators and how they are used
Lecture 14 Moving Average using ChatGPT
Lecture 15 RSI using ChatGPT
Lecture 16 Bollinger Bands using ChatGPT
Section 4: Strategy Creation & Backtesting & Performance Measurement using ChatGPT
Lecture 17 How a trading strategy is created
Lecture 18 Creating a Trading Strategy Plan
Lecture 19 Creating the Trading Strategy
Lecture 20 Performance Measurement
Section 5: Next Steps & Conclusion
Lecture 21 Next Steps & Conclusion
Anyone interested in learning about trading algorithms,Traders, Investors, Finance professionals, and students looking to gain hands-on experience in algorithmic trading,Python programmers
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