Master non-linear regression: Logistic, Quantile, Decision Trees, Random Forests, SVR for finance. Tackle complex patterns, enhance predictive modeling with these machine learning tools....
Master advanced linear regression models in finance: Polynomial, Ridge, Lasso, Elastic Net, LARS. Tackle multicollinearity, feature selection challenges for robust financial modeling. Learn key techniques now!...
Discover Elías' inspiring journey from traditional finance in Chile to mastering quantitative trading through EPAT—overcoming challenges in coding, language, and career transition with perseverance and purpose....
Position sizing is the methodology used to determine the size of a particular trade, strategy or portfolio of assets. Learn different position sizing techniques such as Kelly Criterion, Optimal F, CPPI, TIPP....
In this blog on “Understanding the chain rule,” we will learn the math behind the application of chain rule with the help of an example....
To help develop a deeper understanding of statistical analysis by focusing on the methodologies adopted by frequentist statistics and Bayesian statistics....
Use the ARIMA Model for Stock Price Forecasting in Python with a step-by-step guide on data preparation, parameter tuning, backtesting, and strategy evaluation....
Statistical thinking, a beginner's guide! Making decisions with limited information is a part of life. Get introduced to the way of making decisions using a structured approach through statistics....
Explore the best trend indicators for trading, including MACD, RSI, ADX, and Bollinger Bands. Learn how to use these indicators to build trend-following strategies with Python examples....
Explore bias-variance tradeoff in machine learning for trading. Learn how underfitting, overfitting, and error decomposition impact model performance and strategy development in finance....