ΣL Signal Rating System

This article looks at how we differentiate periodic signal classes on Sigma-L. This is a helpful resource to refer to when interpreting the time frequency plots presented in our market reports.

‘A’ Class

Highly amplitude stationary for the majority of the sample
Highly frequency stationary for the majority of the sample
Maximum gain per frequency across the frequency range and within the bandwidth of the signal, within the sample timeframe
Clear spectral spacing around the signal

Copper (HG), a typical wow! signal demonstrating a beacon like quality across the time and frequency range sampled. Highly amplitude and frequency stationary with no other periodic signal of note coming anywhere near it’s clarity.

‘B’ Class

Highly amplitude stationary for at least half of the sample
Highly frequency stationary for at least half of the sample
Maximum or second highest gain per frequency across the frequency range and within the bandwidth of the signal, within the sample timeframe
Clear spectral spacing around the signal

An example of a ‘B’ class signal in XAU/XAG. Some mild frequency and amplitude modulation, the most typical signal we will likely see in the analysis - an excellent component to note for subscribers.

‘C’ Class

Highly amplitude stationary for at least half of the sample
Highly frequency stationary for at least half of the sample
Maximum or second highest gain per frequency across the frequency range and within the bandwidth of the signal, within the sample timeframe

The 80 day component in GBPUSD with a good degree of stationarity but less defined spectral spacing, a typical ‘C’ class signal

Component Yield Over Sample

This metric uses our gain per frequency measure to show the total notional yield over the sample timeframe if a trader/investor had bought / sold short at the troughs and peaks given by the time frequency analysis. The component highlighted in the report is measured for the duration of the timeframe, with a running cumulative total of yield at each timepoint. This can be thought of as a ‘brute force’ time frequency analysis with amplitude replaced by yield, in some sense.

Here in COPX yield over time is measured by our gain per frequency feature. The resulting heatmap displays lighter colours for running gains and darker colours for running losses. It is no surprise that often the greatest yields come in the region of highly periodic signals. In the above case the excellent component around 79 days has yielded around 187% since January 2021.

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