In this video, I present a simple long-only algorithmic trading strategy based on volatility contraction and breakout logic, trading the NASDAQ 100 CFD on the H1 timeframe. This is a systematic trading approach designed for traders interested in algo trading, quantitative trading, and automated trading systems.
Full Pseudocode for Automated Trading Strategy: https://www.youtube.com/post/UgkxjvJl4s0Mx9TGEZWZU7yzUFdmTEb9jbqv
Content of the video:
0: 40 Strategy Logic & Edge
1: 38 Risk Management & Exits
2: 21 Weekend & Robustness
2: 50 Backtest & Verification
3: 41 Performance Stats
You will see how this trading strategy enters the market when the Schaff Trend Cycle crosses above 54, while price is still compressed below its 34-period SMA. Instead of chasing classic breakouts, this algorithmic trading system waits for volatility contraction and then trades the bullish impulse that follows.
Risk management is fully mechanical. The strategy uses a dynamic stop-loss based on yesterday’s low and a dynamic profit target tied to the weekly open. All trades are also closed if the Schaff Trend Cycle rises above 82.5, acting as an indicator-based emergency exit. This type of multi-condition exit is common in systematic trading systems and trading bots.
The strategy keeps trades open over the weekend and remains profitable even if positions are closed on Fridays or daily before session close. During robustness testing, it stayed profitable under significant parameter changes and timeframe variations, which is a key requirement for any profitable trading strategy and serious algorithmic trading strategy.
Backtests are limited by broker data, but the system has been forward-tested for over six months on a MetaTrader 5 demo account. It also passed Monte Carlo simulations with 1,000 randomized runs, a standard method in quant trading and systematic trading to test whether a strategy is fragile or robust.
Since 2018, the strategy executed 510 trades with a 37% win rate. Average win is about $8, average loss just over $2, giving a payout ratio close to 4:1. Profit Factor is 2.36, SQN around 1.7, and maximum drawdown only 0.53%. Low CAGR is caused by very low market exposure and conservative position sizing, not by lack of edge.
This video is useful for traders, trading for beginners, and anyone interested in how to trade using algorithmic trading strategies, trading systems, and trading bots. You can find the full pseudocode and strategy logic in the description for free.
If you are interested in algo trading, quant trading strategies, systematic trading systems, or learning how to build a trading bot, this video shows a real example with real data and real tests.
✍️ AUTHENTICITY:
All strategies, scripts, and trading insights are my original work, based on years of algorithmic trading experience. The original script has been translated into English and voiced by AI.
Details: http://youtube.com/post/Ugkx4jS8kmfc18q8rfeHvOpGC0ZJ2iLeN2jM?si=jequeZREiYVJc4bk
🕰️ TIME ZONE NOTE:
Strategies are developed in Europe. All references use Central European Time (CET/CEST).
Details: http://youtube.com/post/UgkxbLvwoVkUXIJs4zr7s4T9twI1n2CaAS5d?si=rN8hxhoZ-VBKeD8v
⚠️ RISK DISCLAIMER (Short Form):
– Educational content only. Not financial, investment, or trading advice. I am not a licensed financial advisor.
– High Risk: Trading CFDs, futures, and leveraged derivatives involves a high risk of rapid losses.
– Technical Risk: Algorithmic strategies may fail due to technical issues or extreme market volatility.
– Simulated Results: Backtest or demo results differ from live trading (slippage, liquidity, psychology).
– No Guarantees: Past performance does not guarantee future results.
– Loss Warning: A significant percentage of retail traders lose money (70–89%).
– Your Responsibility: You are solely responsible for your trading decisions. Do not trade based solely on internet content.
Full risk disclosure: http://youtube.com/post/UgkxgX0EX5j2pHEC9WBtdLoGK01Y-h7Io5nl?si=JKDyeBmvjPz_F_GU