Discover a fast, adaptive trend following strategy built specifically for NQ futures using the power of Kalman Filters. In this video, we explore how this innovative approach goes beyond traditional moving averages by filtering out market noise and dynamically tracking price trends. You’ll learn how the Quantitative Trend Indicator (QTI) is constructed using both fast and slow Kalman Filters to generate clear entry and exit signals.

We walk through the exact trading rules, review detailed backtest results from 2017 to 2024, and examine how the strategy performed both before and after optimization. With high-frequency execution—up to 16 trades per day—the potential is eye-catching: strong annualized returns, reduced drawdowns, and a Sharpe ratio that outperforms the benchmark.

But it’s not all upside. The video also dives into the real-world frictions that can erode theoretical performance, like execution speed, slippage, and transaction costs. We discuss those risks honestly and look at possible next steps for improving or adapting the system to other markets and timeframes.

If you’re interested in algorithmic trading, quant strategies, or just want to understand how Kalman Filters can be applied to financial markets, this is one you won’t want to miss. Subscribe for more insights into advanced trading systems, performance analytics, and practical challenges in turning code into edge.

Find the full research paper here: https://community.quantopian.com/c/community-forums/fast-trend-following

For more quant-focused content, join us at ⁠⁠⁠⁠https://community.quantopian.com⁠⁠⁠⁠. There, you can explore a wealth of resources, connect with fellow quants, engage in insightful discussions, and enhance your skills through our extensive range of online courses.

Quant Radio is an AI-generated podcast, intended to help people develop their knowledge and skills in Quant finance. This podcast is not intended to provide investment advice.

#TrendFollowing #QuantTrading #KalmanFilter #NQFutures #Backtesting #AlgoTrading