The Secret of Algorithmic Trading: How AI Predicts Stock Prices

🔥 stock In investment About Korea passion!

I had a really big passion for stock investment! So I personally attended a famous chart trading technique lecture that cost over 400,000 won per 3 hours, and through swing investment through chart analysis, I have consistently earned an average of 1 million won per month for 3 years .

💼 Based on the seed created in this way, we are currently challenging long-term investments and gradually building a stable portfolio.

⚡ Short term invest In automation About Korea worry

But we didn't stop there. After thinking about a more efficient and systematic way to invest, the idea came to us: "Can't we automate short-term investments?"

🤖 I thought that if I built a program that directly creates an AI-based stock price prediction model and catches trading signals in the actual market, not only me but also you would be able to capture trading timing more efficiently.

🎯 lecture produce meter

I created this course because I wanted to share the know-how I've accumulated through this process with many people. And in the next part , I'm planning to cover the process of implementing a US stock automatic trading program in practice, so please pay attention!

“I hope you too can experience a new investment paradigm using data and technology !”

📰 AI Algorithmic Trading – Taking Over 60-80% of Wall Street

• In fact, many securities firms and investment institutions in the United States are actively introducing stock analysis and automated trading using AI. For example, in 2017, Goldman Sachs replaced 600 stock traders with two computer engineers and introduced the artificial intelligence investment analysis program 'Kensho', which enabled analysis that would have taken 15 people 4 weeks to be processed in 5 minutes.

• Also, Renaissance Technologies, an American fund company, conducts trading 100% through computer systems and has an average annual return of 30%. The company generates profits through statistics and scientific algorithmic trading.

• As such, AI-based stock trading is so widespread that it accounts for more than 60-80% of U.S. stock trading, and many companies are using this technology to increase efficiency and profitability.

🔥 This course's unique features and differences

✅ Predict stock prices with deep learning + economic indicators!

• Rather than simple AI modeling , we combine it with economic data to make more precise predictions .

• Precisely predict target future stock prices by inputting economic data and the stock price data you want to predict as dual inputs .

• Build the entire pipeline : [Data collection → Preprocessing → Model design → Prediction → Evaluation].

✅ Direct implementation of AI model verified with 94% accuracy

• We don't just stop at theory, we directly learn and improve AI models that have actually been verified .

• You can train AI prediction models for individual stocks as well as the S&P 500 and QQQ .

✅ Fully practice-oriented lectures – linked to real-world investments

• Rather than simply learning AI modeling, you will practice with real-world data so that you can apply it directly to your investments .

• In the second half of the lecture, you will learn how to analyze AI prediction results and establish investment strategies .

✅ Step-by-step explanation so even beginners can follow along

• No need to have AI development experience!

• We will go through everything step by step, from how to collect data to how to apply deep learning models.

📌 Practice environment

• Python (pandas, NumPy, TensorFlow, etc.)

• Google Colab, Visual Studio Code, or Cursor IDE

• FRED API and Yahoo Finance Data Collection

• Matplotlib, Seaborn, Plotly (data visualization)

📌 Learning Materials

• We provide you with a Notion link!

• Please refer to the class notes for the intro lecture!

  
  

  
  

  
  

  You can check the class notes right away, like in the second capture , by placing the mouse over the playback screen (black) on the current screen and scrolling down a little .

  
  

  
  

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  Lessons without lecture materials will not display any materials.
  📑 Please note that only lessons with the icon have materials! 😊

  

  If you have difficulty accessing the company's internal network environment, please feel free to contact us at banbu.jh@gmail.com at any time! 😊

📌 Additional information that would be helpful to know

• Deep Learning and Machine Learning Fundamentals

  • Experience with TensorFlow is helpful.

  • Knowing basic neural networks (NN) and time series analysis concepts will help you understand faster.

• Experience in data analysis and preprocessing

  • If you have experience using data manipulation and analysis libraries such as Pandas and NumPy, you will find it easier to follow the exercises.

• Basic understanding of financial data and economic indicators

  • Experience working with financial data from data sources such as FRED API, Yahoo Finance is a plus.

📌 Don’t worry if the above concepts seem unfamiliar!
The lectures are structured to kindly explain relevant content and allow you to learn naturally through practice. 🚀