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Historical Market Data Sources
A comprehensive list of free and paid financial data providers, detailing available asset classes, data types, and access methods....
7 min read
Types of Regression in Finance for Analysis and Their Uses
Types of regression in finance - What are they? How to learn about them? This is your one-stop guide to the various types of regression. Learn with examples, charts & comparisons....
13 min read
Exploring Linear Regression Analysis in Finance and Trading
Getting under the hood of linear regression where we demystify the jargon regularly encountered on the topic. Let’s dive in!...
13 min read
Walk-Forward Optimization in Python for ML Models
Learn how to apply Walk-Forward Optimization (WFO) in Python using XGBoost for stock price prediction. Understand how WFO helps manage concept drift and maintain model accuracy in dynamic financial markets....
9 min read
Walk-Forward Optimization (WFO): A Framework for More Reliable Backtesting
Learn how Walk-Forward Optimization (WFO) works, its limitations, and how to implement it for backtesting trading strategies. Enhance your strategy testing with a structured framework for more reliable results....
5 min read
QuantInsti in 2025: A Summary of our Contributions, Collaborations, Events & Updates
Explore QuantInsti’s impactful collaborations, announcements, webinars, industry events, and academic initiatives for 2025. Learn about our collaborations, regulatory updates, expert insights....
5 min read
RSI Indicator: Calculation, Python Implementation and Trading Strategy
Learn how the RSI indicator works, from its formula and calculation to trading strategies and backtesting. Explore Python implementation with real-world examples and visualizations....
13 min read
Basic Guide to Trade Options Intraday: Strategies and Risk Management
Learn intraday options trading strategies, including scalping, volatility breakouts, and gamma scalping. Explore risk management tips and trade execution methods for intraday option trading....
14 min read
Autoregression: Time Series, Models, Trading, Python and more
The autoregressive (AR) model is a key tool for time series forecasting in trading. This guide covers its formula, calculation, and step-by-step model building, including a Python implementation....
16 min read
DBSCAN Vs K-Means
K-Means has its limitations DBSCAN solves them. This guide explains how DBSCAN works, its advantages over K-Means, and how to implement it in Python....
9 min read
