• - Complete analytics platform for futures & spreads -
  • - Algorithmic trading signals based on seasonality -
  • - Everything in the cloud - no installation needed -
  • - iPad optimized -
  • - Free for personal use -
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Composite Commitments of Traders

Powerful visualizations of the Commitments of Traders data will give you an unprecedented edge in predicting the commodities markets. Our studies include both absolute (net positions) and relative (COT index) data. We combine the data from various types of COT reports (legacy futures only, legacy futures & options combined, disaggregated) into a continuous time series. Therefore you can analyze the COT decades back in one chart.

Seasonal trading signals

Our algorithm scans the market every day for seasonal trading opportunities in outright futures, interdelivery spreads and intermarket spreads. The signals are presented in simple charts, so you can get the idea behind the trade in a second. Moreover, the algorithm computes average expected return and maximal historical drawdown for every signal, so you can adjust you money management accordingly.

Long-term historical data

We are a licensed CME Group, Inc. market data distributor. Our app has a multidecade history of end-of-day data for most US commodities and futures. You can display the price data and make technical drawings right in the chart, or you can analyze how your favorite spread behaved decades ago.

Historical ratios

Track the intermarket fundamentals with long-term ratio charts. Visualize the hog feed ratios, popular gold/silver, dow/gold ratios and others.

Volume & OI comparison

Are you sure the spread you watch is liquid enough to trade? Check it out instantly using our custom volume & open interest comparative analysis.

Term structure visualization

Get the structure of the market by displaying its term structure (or forward curve).

Seasonality studies

Analyze futures or spreads in stacked charts. Highlight the seasonal behaviour in our interactive charts by hiding abnormal years or zooming the seasonal period.