Tag: Python
-
Real-Time Trading Systems and Deployment Best Practices
Your backtest won't survive production. Latency budgets, order rejection handling, kill switches, and monitoring that catches bugs before losses.
-
Risk Management and Portfolio Optimization Techniques in Python
VaR underestimates tail risk, Markowitz explodes on estimation error. Fix it with shrinkage estimators and Kelly criterion position sizing.
-
Backtesting Frameworks: Building Your First Trading Strategy
Most backtests lie about profitability through lookahead bias. Build a point-in-time engine that doesn't cheat on order fills or data access.
-
Quant Feature Engineering with Pandas and TA Indicators
Why shift(1) is the most important line in your feature engineering pipeline โ and how to avoid the temporal leakage that kills strategies.
-
Getting Started with Quantitative Investment in Python
Build a quant trading infrastructure in Python: data pipelines, log return calculations, and backtesting that includes transaction costs.
-
Python์ผ๋ก ์์ํ๋ ํ๋ก๊ทธ๋๋ฐ: ์ด๋ณด์๋ฅผ ์ํ ์๋ฒฝ ๊ฐ์ด๋
Python basics to production skills: syntax, data structures, and real automation workflows for data analysis, web scraping, and scripting.
-
Advanced Trading Bot Features: Risk Management and Backtesting
Avoid the Kelly Criterion trap in crypto bots. Walk-forward backtesting + slippage models reveal what actually works for position sizing.
-
Upbit Trading Bot Part 2: Market Analysis and Order Execution
Build a moving average bot on Upbit that handles API failures and slippageโlessons from real trades that lost money before they made it.