How to make money investing with data, simulations, and statistics

Curriculum

Lecture 1: Ultra-Short-Term Trading and Quantitative Trading Using Data

Lecture 2: The Definition of Quant and Current Trends, Ultra-Short-Term Trading, and Market Microstructure

Quant in Change
-predominance
-Trend
-Computerization
-Modeling
-High-speed
-Datafication
-Artificial intelligence
- Ultra-short-term trading/algorithmic trading
Market Microstructure vs. Financial Analysis
-Hogachang
-Market participants
-PIN

Lecture 3: Practical Algorithm Strategies

-VPIN actual data
-Practical Strategy: Merrill Lynch 250
-The Flower of Short-Term Trading: Market Making Strategy
-Added inventory management
-Added VPIN and Book pressure
-Cascade market making
-Advanced Market Making
-Trend strategy
-Trend scalping strategy
Technical Analysis vs. Microstructural Analysis
- Market microstructure summary

Introduction to investment strategy development and simulation using data from the 4 major markets

-Strategy development using data analysis
-VIX Sell Strategy
Pattern Recognition Using Machine Learning
- Data collection for strategy verification
-Principal component analysis
-Optimization and backtesting process
-Strategy Verification / Robustness

Lecture Features

• Practical strategies you can learn and immediately apply! Even among various strategies, there are priorities.

PPSS's PICK

"The most common misconception about quants is that they predict the future and prices. Ultimately, quants find an advantage and then realize that advantage through the law of large numbers."

"The most important strategy is market making. You can consider 80-90% of ultra-short-term trading to be market making. This strategy involves simultaneously placing buy and sell orders to exploit spreads. Therefore, it's not significantly affected by bullish or bearish markets, and it offers the advantage of generating significant profits even without significant capital."

"There's nothing new about creating a strategy. It doesn't require much background knowledge. You need to develop a sense of data analysis, experiment with various data sets, and develop the skills to understand which data to work with."

Instructor Interview

• A Former Trader Discusses Ultra-Short-Term Quant Trading: An Interview with CEO Kwon Yong-jin