ΣL Uranium Composite - 3rd July 2023 | @ 148 Days
Last trade: + 17.59% | 'B' class signal detected in in Sigma-L Uranium Composite (NXE/DNN/UEC/CCJ/UUUU). Average wavelength of 148 days over 9 iterations since December 2019. Currently peaking.
Trade Update
Summary of the most recent trade enacted with this signal and according to the time prediction detailed in the previous post for this instrument. For a composite analysis, each constituent’s respective gain over the period is displayed, in descending order. The average of the constituent gain is also shown.
Type: Buy - ΣL Uranium Composite 28th April 2023
Entry: 28th April 2023
Exit: 30th June, 2023
Constituent Gain:
UEC (30.27%)
NXE (20.77%)
CCJ (13.97%)
DNN (13.64%)
UUUU (9.28%)
Composite Average Gain:
17.59%
Current Signal Status
Defining characteristics of the component detected over the sample period.
Detected Signal Class: B - learn more
Average Wavelength: 148.38 Days
Completed Iterations: 9
Time Frequency Analysis
Time frequency charts (learn more) below will typically show the cycle of interest against price, the bandpass output alone and the bandwidth of the component in the time frequency heatmap, framed in white. If a second chart is displayed it will usually show highpassed price with the extracted signal overlaid for visual clarity.
Current Signal Detail & Targets
Here we give more detail on the signal relative to speculative price, given the detected attributes of the component. In most cases the time target to hold a trade for is more important, given we focus on cycles in financial markets. Forthcoming trough and peak ranges are based upon the frequency modulation in the sample (learn more).
Phase: Peaking / Peaked
FM: +- 20 Days
AM: N/A (Composite)
Next Trough Range: August 29th - October 8th, 2023
Next Peak Range: November 13th - December 23rd, 2023
Sigma-L Recommendation: Sell
Time Target: ~ 18th September, 2023
Current Signal Phase
This is ‘how far along’ the cycle is in it’s period at now time and is related to the predicted price action direction.
Current Signal Frequency Modulation (FM)
This is how much, on average, the signal detected varies in frequency (or wavelength) over the whole sample. A lower variance is better and implies better profitability for the component. Frequency usually modulates relatively slowly and over several iterations.
Current Signal Amplitude Modulation (AM)
This is how much the component gains or loses power (price influence) across the sample, on average. Amplitude modulation can happen quite quickly and certainly is more evident than frequency modulation in financial markets. The more stable the modulation the better.
Interesting. Thank you for these detailed analyses. I’m actually quite fascinated by the correlations with my Model. Again, I’ll continue to follow. Quietly. Thanks!