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Simple and Multiple Linear Regression in Algorithmic Trading: A Practical Guide for Quants
Explore how linear regression powers trading strategies in quantitative finance. Understand OLS, model assumptions, Python code for stock prediction, and real-world use cases for building and evaluating trading models....
23 min read
Beyond the Hype: What "Independent Events" REALLY Mean for Your Trades
Explore how statistically independent events help cut through market noise and shape reliable trading strategies. Understand independence, correlation, and cointegration with practical examples and algorithmic use cases....
18 min read
Beginner's Guide to Machine Learning Classification in Python
Build classification trading strategy in Python for predicting the S&P500 price from scratch. Learn how to handle binary and multiclass problems using key ML algorithms like SVM, with a full coding workflow—from data prep and training to evaluation and visualization....
6 min read
Building a Trading Strategy using Bias-Variance Decomposition
Explore the bias-variance tradeoff in machine learning for trading strategies. Learn how to build and backtest a trading model using PCA, VIF, and bias-variance decomposition to optimize performance and mitigate overfitting....
17 min read
Reinforcement Learning in Trading
Learn how reinforcement learning is applied in stock trading with Q-learning, experience replay, and advanced techniques. Explore its edge over traditional ML in building trading strategies....
9 min read
Modelling Asymmetric Volatility with the GJR-GARCH Framework
Explore the GARCH and GJR-GARCH models for volatility forecasting. Learn their differences, formulas, and how to forecast NIFTY 50 volatility using Python in this hands-on guide....
9 min read
Moving Average Crossover Strategies
Moving average crossover strategies explained. Explore types of moving averages, learn how to build effective trading strategies, and get insights on advantages, examples, and FAQs for traders....
16 min read
From Logistic to Random Forests: Mastering Non-linear Regression Models
Master non-linear regression: Logistic, Quantile, Decision Trees, Random Forests, SVR for finance. Tackle complex patterns, enhance predictive modeling with these machine learning tools....
14 min read
Beyond the Straight Line: Advanced Linear Regression Models for Financial Data
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!...
15 min read
Elías’ Journey: From Finance to the World of Quant – Powered by EPAT
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....
6 min read
