Financial Select Sector SPDR Fund - 9th May 2023 | @ 79 Days | Snippet
Financial Select Sector SPDR Fund - 9th May 2023 | @ 79 Days | Snippet
'C' class signal detected in Financial Select Sector SPDR Fund (XLF) . Running at an average wavelength of 79 days over 8 completed sample iterations since May 2021. Currently moving down.
Signal Class & Attributes
Defining characteristics of the component detected over the sample period.
Detected Signal Class: C - learn more
Average Wavelength: 79.42 Days
Completed Iterations: 8
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.
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.
Phase: Moving Down
FM: +- 14 Days
AM: 0.415
Next Trough Range: May 25th - June 22nd, 2023
Next Peak Range: July 4th - August 1st, 2023
Sigma-L Recommendation: Late Sell
Time Target: ~ 8th June 2023
See Also…
DISCLAIMER: This website/newsletter and the charts/projections contained within it are intended for educational purposes only. Results and projections are hypothetical. We accept no liability for any losses incurred as a result of assertions made due to the information contained within Sigma-L. This report is not intended to instruct investment or purchase of any financial instrument, derivative or asset connected to the information conveyed in the report. Trade and invest at your own risk.
Signal Phase: This is ‘how far along’ the cycle is in it’s period at nowtime and is related to the predicted price action direction.
Signal Frequency Modulation: 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.
Signal Amplitude Modulation: 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.