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Retrospective Simulation for Trading
Simulate alternate historical price paths using a non-parametric Brownian bridge to test trading strategies beyond the realised market history. See how retrospective simulation reveals risks of overfitting and enables more robust backtesting....
18 min read
Market Regime using Hidden Markov Model
Build a regime-adaptive trading strategy in Python with this hands-on guide. Detect market regimes using Hidden Markov Models and generate signals with Random Forests—all with complete code and walk-forward backtesting....
8 min read
Bayesian Statistics in Finance: A Trader's Guide to Smarter Decisions
Explore how Bayesian statistics helps traders update beliefs, build adaptive models, and manage risk. Learn Bayes’ Theorem, Naive Bayes, Bayesian inference, and their applications in algorithmic trading and quantitative finance....
19 min read
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
