Stop losing money on outdated backtests! Discover the revolutionary new way to deploy AI-driven algorithmic trading bots for real market data before risking a single dime of your own capital. In this video, Brian reveals a groundbreaking quantitative finance methodology: live forward-testing. Instead of relying on historical data that suffers from curve-fitting, watch as we deploy 12 different automated trading strategies in a live virtual environment. Using the power of Art

can state with absolute certainty that the trading strategy we are about to break down is the most profitable, risk-adjusted, and architecturally sound AI-generated strategy I have ever analyzed.

I highly encourage you to subscribe to the Quantlabs Substack, as it is the fastest-growing platform I engage with, and it’s where I drop all my latest code, strategies, and market analysis first.

For retail traders and professionals alike looking to generate consistent, reliable income, the answer no longer lies in predicting the long-term future. Instead, it lies in shrinking your time horizon.

The Python bots act as strategy engines — they consume market data, make trading decisions, and publish order commands, but they never directly touch exchange APIs.

The landscape of quantitative finance, high-frequency trading (HFT), and algorithmic strategy generation is undergoing a seismic shift. For years, breaking into the quant industry or building a proprietary trading desk required navigating a labyrinth of expensive third-party career coaches, static interview prep books, and months of grueling infrastructure coding. Today, that paradigm has been entirely shattered by the advent of ultra-cheap, highly advanced Artificial Intelli

The landscape of quantitative finance is undergoing a massive transformation, driven by the rapid advancements in Artificial Intel

Comprehensive Multi-Asset Backtest Analysis, Strategy Rankings, Position Sizing & Algorithmic Framework for Maximum Profit Potential — 2026–2030 Outlook

For decades, the "Random Walk" has been the bedrock of financial modeling, underpinning everything from the Black-Scholes equation to the Efficient Market Hypothesis (EMH). However, a persistent open problem in mathematics has clouded our understanding of stochastic processes: Why do some random walks revert to the mean (forgetting their history), while others diverge indefinitely (remembering their path)?

We’re conducting a daily poll to understand how institutional and professional traders prefer to receive their multi-asset derivatives strategy research.

What was once the exclusive domain of hedge funds and institutional trading desks can now be explored from your home computer using free, open-source tools and a demo brokerage account.

Building Bots – Speed and Customization to Start Revolutionizing Algorithmic Trading for Beginners

For traders and investors, this environment offers a rare window of opportunity—provided they know where to look.

I am here to talk about a revolution—a complete dismantling of the old guard.

hodology to rank strategies not just by raw return, but by the quality of that return relative to the risk endured.

The VIX Call Backspread represents a nuanced volatility trading strategy that profits from significant upward movements in the CBOE Volatility Index. The strategy's structure involves selling one at-the-money call option while simultaneously purchasing two out-of-the-money calls at a strike price approximately 25% higher than the current VIX level.

Rithmic Trading System 2.0: A Comprehensive Technical Guide to Building a Modern Trading Simulation Platform

Date: February 2, 2026 Subject: Analysis of Algorithmic Trading Strategies, AI Integration, and Market Volatility Following the Precious Metals Crash Source Material: Video Transcript, Byan (QuantLabsNet)

Desk: Quantitative Derivatives & Global Macro  Subject: The Volatility Paradox: Alpha Generation in a Dislocated Regime Security Level: L3 (Proprietary) Derivatives Strategy

The financial markets are currently perched on a precipice. With major indices showing fragility, tech giants like Microsoft dragging down sentiment, and geopolitical tensions simmering, the era of "easy money" for retail traders is over