AI-powered stock analysis & quantitative research
Machine learning models, backtesting frameworks, and data-driven trading strategies — from research to deployment.
Communication Services Sector Analysis 2026: Two Tracks
Communication services sector analysis 2026 — decode the ad-platform vs telecom divergence and screen XLC components to find where the money is rotating next.
Options Flow Analysis: Institutional Sentiment Ahead of NVDA
Options flow analysis exposes a retail-versus-institutional split ahead of Nvidia earnings. We quantify the divergence with market data and a pandas workflow.
Cisco Stock Analysis: AI Networking Supercycle vs Margins
A comprehensive Cisco stock analysis examining AI networking demand against gross margin pressure — see where CSCO fits in your quant portfolio research today.
CRM Stock Analysis: Agentforce AWU vs. cRPO Inflection
CRM stock analysis — a pre-earnings deep dive into Salesforce's Agentforce billing model versus cRPO growth, so you can frame the risk before the report.
Qlib Review 2026: Microsoft's AI Quant Platform
Microsoft Qlib is the best open source AI quant platform for beginners with Python skills — learn how to get started, install it, and run your first backtest.
How to detect backtest overfitting in Python
Learn how to detect backtest overfitting in Python using the deflated Sharpe ratio and the probability of backtest overfitting, from the academic papers.
Consumer Discretionary Sector Analysis 2026: XLY vs S&P 500
Consumer discretionary sector analysis 2026: records on the tape, softness in spending. See the data, the diverging winners, and how to screen for them.