How COT Data Can Reveal Market Edges: Bitcoin’s $120K Top, Oil Bottoms & Trading Strategies

Can you identify major market turning points before they become obvious on a price chart?

Most traders rely on technical indicators such as RSI, MACD, or moving averages. But these tools share one limitation: they are primarily derived from price.

Commitments of Traders (COT) data offers something different — insight into how major market participants are actually positioned.

In our latest StrategyQuant interview, we sit down with Pavel Hála, founder of SpreadCharts, to explore how COT data can help traders identify market extremes, understand institutional positioning, and discover opportunities that traditional price indicators might miss.

How COT Data Helped Identify Bitcoin’s $120K Top

One of the most interesting stories from the interview is how Pavel used COT data, alongside other market indicators, to anticipate Bitcoin’s major top around $120,000 in summer 2025.

His analysis revealed excessive positioning and important warning signals suggesting the bull market could be approaching a turning point.

But Bitcoin is only one example.

Pavel also explains how his proprietary COT indicators helped him identify major opportunities in the energy markets, including the oil bottom in 2020 and another important signal in December 2025.

What makes these examples particularly interesting is that the signals came from market positioning data — information that cannot simply be derived from price charts.

What You’ll Discover in This Interview

• COT Data Explained: Understand what COT reports reveal about institutional traders, commercial hedgers, and speculators.
• Bitcoin’s $120K Top: Discover how excessive market positioning helped Pavel anticipate a major Bitcoin reversal.
• Oil Market Opportunities: Learn how COT-based indicators identified significant opportunities in the energy sector.
• Which Markets Work Best: Explore why COT analysis behaves differently across commodities, forex, cryptocurrencies, and stock indices.
• Market Regimes and Extremes: See how changes in institutional positioning can help identify bullish and bearish market conditions.
• Algorithmic Trading Applications: Understand why COT data works best when combined with price action, seasonality, and other independent market signals.

COT Data Is Now Available in StrategyQuant X

〜と一緒に StrategyQuant X Build 145, traders can access historical COT data supplied by SpreadCharts directly within the platform.

This opens new possibilities for systematic research, including testing COT-based filters, analyzing market regimes, and combining positioning data with algorithmic trading strategies.

As Pavel explains during the interview, COT data should not be treated as a standalone trading signal. Its real value comes from combining it with other sources of information and validating ideas through systematic research.

All COT data in StrategyQuant X is provided by SpreadCharts, giving traders access to high-quality historical positioning data for systematic research and strategy development.

Watch the full interview with Pavel Hála from SpreadCharts on YouTube and discover how COT data could become part of your trading research process.