The Sigma-MT Suite (includes Sigma-MT EA and the Sigma-MT Scanner) is available now for new VIP Cycle Analysts (founding members). Please contact me (on X or Substack chat) once you have joined or upgraded from standard membership to receive the software.

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Prerequisites: the full single-chart course, parts one through five, or at minimum the quick start, spectrogram and detection guides. The scanner assumes you can read a rank, a wavelength and a phase because it is about to hand you dozens of them at once!

Everything this course has taught you so far is deliberate, single-chart work: attach the EA, read the spectrogram, judge the rank, project the turn. The obvious question follows you the whole way through. Which chart? A clean, high-ranking, well-phased cycle is a needle, and the market is a very large haystack; the trader who checks ten instruments by hand has still not checked the other two hundred. The Sigma-MT Scanner, (currently on version 1.7 and part of the Sigma-MT portfolio) exists to remove that problem entirely. It runs the same wavelet convolution, the same CFAR detection and the same quality scoring you know from the EA across every symbol in your Market Watch, on up to five timeframes at once, and returns a ranked, sortable table of every tradeable rhythm it finds. This part covers the operational half, getting it installed, configured and scanning. The next part covers reading what it returns and the part after that the click-through from scanner to chart for a full deep dive.

Install and the one-time template

The Scanner is itself an Expert Advisor. Copy it into MQL5\Experts alongside Sigma-MT, refresh the navigator, and attach it to any chart; the symbol and timeframe of that host chart are irrelevant, since the scanner ignores it’s host and takes over the window as a dedicated panel. Like the EA it places no trades and requests no permissions.

Before your first scan, do one piece of setup you will never have to repeat because it transforms the whole workflow later. Open any chart, attach Sigma-MT to it, configure the inputs however you like your analysis, then right-click the chart and save it as a template named SigmaMT, matching the Scanner’s SigmaMTTemplate input (in Chart Launch section), which defaults to exactly that name. Note, you can also use another name, if you wish just ensure they line up.

When you eventually click a result row, the scanner opens the suggested chart and applies this template automatically, so the cycle analysis appears pre-loaded with the EA rather than as a bare chart, matching the characteristics found via the scanner which uses the same engine. The parameter handoff that accompanies this is genuinely clever and gets full treatment in part eight; for now, just save the template and forget about it. If the template is missing the scanner will still open charts, with a warning in the log, and setting the input blank disables template application deliberately.

Choosing the universe

The Scanner’s universe is simply your Market Watch: every symbol currently shown there is scanned, and nothing else is. This is a deliberate design choice, because it means curating your scan list requires no configuration dialog at all, you add and remove symbols in the Market Watch exactly as you always have, and the next scan reflects it. Keep a lean, liquid watchlist and scans complete quickly; show hundreds of exotic crosses and the scan will dutifully churn through all of them. My own habit is a working set of the majors, the key crosses, the indices and the metals, which keeps a full multi-timeframe pass comfortably fast while covering everything I would realistically trade.

Timeframes and the analysis settings

The Analysis Settings group offers up to five timeframe slots. Timeframe1 defaults to M1 and any slot left at current is disabled, so you enable exactly as many resolutions as you want swept, up to all five. Each symbol is analysed independently on each enabled timeframe, which is what later allows the Scanner to notice when one instrument is carrying related cycles at several resolutions at once, the nested-cycle grouping that part seven unpacks. Be aware the workload multiplies accordingly: five timeframes across a large watchlist is five full analyses per symbol, and the progress readout will show you the cost in time and processing accordingly. Scanning through my main market watch of around 60 instruments at N=500, across 5 timeframes, takes around 45 seconds! In practice one should aim for Market Watch lists around 30-50 instruments in order to avoid clutter if analysing multiple timeframes. I leave it up to the user to find their preferred balance of this powerful feature.

The rest of the analysis inputs you already know, because they are the same engine. N is the sample size per analysis, AnalyseOn the price it decomposes, and the Time Frequency group carries the identical LowestFreq, HighestFreq, DetectionMethod, SNRThreshold, CFAR cell and bias settings and RecencyBias from the EA, with the same defaults and the same meanings. This is worth a moment’s appreciation: the scanner is not a lightweight screener applying some crude proxy and hoping the EA later agrees. Every row in its results table earned its place through the full wavelet convolution and CFAR detection you studied in the detection guide, at the settings you chose. What the scanner calls rank is precisely the 0 to 1000 rank the EA shows you and so forth.

The three ways to scan

The LoopInterval input sets the scanning rhythm, and there are three modes of operation within it. Manual, the default, scans once when you press R and then waits for you; this is the mode I recommend while learning and for the session trader who wants a fresh sweep at moments of their choosing. Continuous begins a new scan the moment the previous one completes, keeping the table as live as your hardware allows, which suits a dedicated scanning terminal left running. Between the two sit the fixed intervals, one, five, fifteen, thirty or sixty minutes, where the Scanner rests between sweeps and refreshes on schedule; these are the sensible default for most people, frequent enough that the table stays current, quiet enough that your terminal is not permanently occupied. Whichever mode is set, R always triggers a scan on demand provided one is not already running, and the panel’s status line shows progress through the symbol list as it works.

Filtering the flood

A broad watchlist on several timeframes can return more rows than any human should triage raw, so the scanner filters at the source. IgnoreBelow sets the minimum acceptable rank for a cycle to appear at all, in tiers of 600, 700, 800 or 900, and I would encourage you to use it aggressively: the whole discipline of this course has been that detections below 700 deserve suspicion, and a scan-level floor simply enforces that discipline before the noise ever reaches your eyes. MinWavelengthMinutes discards cycles shorter than a chosen wavelength, expressed in minutes, which matters because a market-wide sweep of low timeframes will always find an abundance of very fast, technically valid but practically untradeable rhythms. A floor of an hour or two clears them out at a stroke. Set to zero it shows everything. Personally, if trading intraday, I set the minimum at 45 minutes - in my experience there is often great cycle features around an hour intraday but anything shorter is dicing with randomness just too much!

GroupInPhase, gathers rows of the same symbol across timeframes when their cycles are in phase, and it sits right on the border between operating the scanner and interpreting it. I will introduce it here and do it justice in part seven, where phase confluence and the harmonic validation behind that grouping are the entire subject.

Your first sweep

Put it together and the first session looks like this: Attach the scanner, confirm your Market Watch holds the instruments you actually care about, enable two or three timeframes to start, set IgnoreBelow to 700 and let it cook. Watch the progress line walk the symbol list, and when the table settles, simply read it with the eyes this course has given you: wavelengths in real units, ranks you know how to weigh, phases you know how to interpret. Click a column header to sort, shift-click to add a second sort, and scroll with the arrow keys. Press R to rerun the scan at a time of your choosing or set it to loop autonomously with the loop input described above.

Resist clicking through to charts for now; the next part is about extracting the full meaning of this table, the phase confluence between it’s rows and the harmonic relationships that mark a genuinely special result. The process after that completes the journey from a row in the table to a fully audited trade candidate.

Where to go next

Part seven, Reading the Results: Phase Confluence and Harmonic Validation, takes the table you can now produce and teaches you to read it the way the engine intends. What each column asserts, why in-phase cycles across timeframes are grouped together and the harmonic test that separates coincidence from genuine nested structure.

Licence: Sigma-MT is provided exclusively to founding members of Sigma-L and is licensed for your personal use only. Redistribution or copying, cloning or in any way reproducing the EA or Scanner files is prohibited without express prior permission.

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.

The Sigma-MT Suite is available now for new VIP Cycle Analysts (founding members). Please contact me (on X or Substack chat) once you have joined or upgraded from standard membership to receive the software.

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Prerequisites: the quick start, the spectrogram guide, detection guide, projection guide and the yield guide. You should be comfortable reading spectral power, trusting a score and understanding the bandpass as the dominant cycle extracted cleanly from price. No new keys are introduced in this part; the composite is configured entirely through the inputs.

Introducing composite analysis

Every part of this course so far has interrogated one instrument at a time. This part widens the aperture, and in doing so it reaches back to one of the oldest ideas in the cycle literature. Hurst called it the Principle of Commonality: the observation that broadly related instruments do not each dance to a private tune but share their dominant cyclic behaviour, with the differences between them being largely a matter of amplitude and noise rather than of rhythm. A basket of dollar pairs breathes with the dollar. A group of index futures inhales and exhales risk together. Hurst asserted this from painstaking manual study in the 1960s; the composite mode in Sigma-MT lets you test it numerically on any basket you care to assemble, in seconds, and then, crucially, profit from the answer.

The logic of the feature is simple to state. Each member of a related basket carries the shared cycle buried under its own idiosyncratic noise: the news spike particular to one pair, the earnings gap particular to one stock. Combine the members correctly and the common rhythm, being roughly in phase across the basket, reinforces, while the private noise, being uncorrelated, tends toward cancellation. The signal-to-noise ratio of the commonality cycle rises above anything a single member could offer. Then, having detected that shared cycle with a confidence no lone chart could give you, the software answers the practical question that follows: on which instrument in the basket is trading optimal for yield over time?

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The Sigma-MT Suite is available now for new VIP Cycle Analysts (founding members). Please contact me (on X or Substack chat) once you have joined or upgraded from standard membership to receive the software.

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Prerequisites: the quick start, the spectrogram guide, detection guide and the projection guide. You should be comfortable reading the spectral properties of a signal and a bandpass. You should understand that the bandpass is the dominant cycle extracted cleanly from the price action at the targeted bandwidth.

Every guide so far has pointed forward: detect the cycle, score it, project it, box the next turn. This one turns around and looks back historically, giving an estimation of past performance. Yield mode, on the Y key, asks a simple question of the cycle currently on your chart: if you had traded this rhythm across the visible window, buying every trough and selling every peak, what would it have returned? The answer is one of the most useful sanity checks in the software, and also one of the easiest to misread, so this guide is as much about what the number does not mean as what it does.

What yield mode actually does

Press Y and the engine walks the weighted bandpass from the oldest bar to now-time, finding every inflection point along the way. It then lines these up into a sequence of trades, which the software calls legs, always starting from a trough so that the first move is a buy. Trough to the next peak is a long; peak to the next trough is a short. The cycle is simply traded in both directions, turn by turn, across the whole window.

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The Sigma-MT Suite is available now for new VIP Cycle Analysts (founding members). Please contact me (on X or Substack chat) once you have joined or upgraded from standard membership to receive the software.

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Prerequisites: the quick start, the spectrogram guide and the detection guide. You should be comfortable reading a spectrogram, trusting a score, and understanding that the bandpass is the dominant cycle extracted clean from the noise.

Detection told you a cycle is real and the score told you how stationary it is based upon extensive criteria. This guide concerns itself with what the engine does next: it takes that identified cycle and projects it forward, marks where the next turning point should fall, draws a window of uncertainty around it based upon characteristics of the periodic feature, and wraps the whole thing into a trade box you can actually act on. This is where the analysis stops describing the past and starts pointing at the future, so it is also where discipline matters most.

Carrying the cycle forward

The simplest part of the projection is the extension of the bandpass itself. Once the dominant cycle is isolated, the engine continues its oscillation past the present bar, drawn as the dashed forward portion of the bandpass you have already seen. How far it runs is set by ForwardCycles in the inputs, expressed in lengths of the detected short-term cycle and clamped between 0.1 and 2.0, with a default of one full cycle. One cycle ahead is the default. Confidence in any extrapolation decays with distance from nowtime and a projection two cycles out should be read as a highly uncertain sketch of rhythm (especially at the right edge), rather than a forecast of price.

It is worth being precise about what is and is not being predicted here. The bandpass projection assumes the dominant rhythm continues at roughly its current wavelength and amplitude, which is a reasonable assumption for a high-scoring, stable cycle and a poor one for a low-scoring, modulating feature. This is the entire reason the score comes first in our guides as it is the first line of filtering for the analyst. The projection is only ever as good as the detection beneath it, and the engine will happily extend a weak cycle forward if you ask it to. Comprehending the score before trusting the projection is the habit that separates using the tools well from being misled by it.

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The Sigma-MT Suite is available now for new VIP Cycle Analysts (founding members). Please contact me (on X or Substack chat) once you have joined or upgraded from standard membership to receive the software.

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Prerequisites: the quick start and the spectrogram guide. You should be comfortable reading a spectrogram, recognising a persistent band and understanding the bandpass origin.

The spectrogram guide showed you how to read power, but it left one question open: how does the engine itself decide that a particular band is worth your attention, rather than a passing flare of noise? That decision is the whole game. A projection is only as trustworthy as the detection beneath it, so this guide opens the bonnet (somewhat!) on detection, explains the score that grades it, and hands you the manual controls for when you want to override the engine’s choice.

Why a threshold has to adapt

Let’s begin with the naïve approach: The obvious way to call a peak significant is to set a fixed threshold of power: any frequency whose power rises a certain multiple above the average counts as a real cycle in this approach. This is the signal-to-noise method, and Sigma-MT offers it, although really it is a legacy of testing I thought I would leave in. You set SNRThreshold (default 3.0), the engine measures each frequency against the median power of the spectrum, and any local maximum that clears that ratio is flagged.

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The Sigma-MT Suite is available now for new VIP Cycle Analysts (founding members). Please contact me (on X or Substack chat) once you have joined or upgraded from standard membership to receive the software.

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Prerequisites: the quick start guide. You should already have Sigma-MT on a chart and recognise the spectrogram, bandpass panel and info panel by sight.

The quick start guide told you what the spectrogram is. This guide tells you what it means, and why a picture built from wavelet convolution is a fundamentally more honest way to look at market cycles than counting peaks on a chart. Everything that follows in the course (detection, projection, yield, composites, the Scanner) is built on the foundation laid here, so this is the one guide worth reading twice.

The problem with counting cycles..

Classical cycle analysis, the kind you find in most trading literature and some descending from the work of J.M. Hurst, begins by simple counting of visually apparent inflection points. You find two lows, measure the bars between them, and declare a cycle of that length. The trouble is that this is subjective and brittle. Two analysts looking at the same chart can pick different lows and arrive at different cycles, and a single noisy swing can throw the count off entirely. Indeed higher frequency features can often have bursts in power than exceed the power of the longer cycle, influencing price in a transitory and misleading (to the cycle counter) manner. Worse, it assumes a cycle has one fixed length, when real market rhythms drift in period (frequency modulation) and fade in and out of strength (amplitude modulation) over time. The real marker of a quality cycle is the minimisation of any modulation (or a high degree of stationarity), since modulation is a constant in financial market cycles.

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A reminder before the list. Several inputs have a keyboard twin, so anything you adjust live with the keys (sample size, frequency edges, panel toggles) only persists for that chart session. The inputs are where you set the values that load every time the EA attaches.

Time Series

SampleN (default 500) — The number of bars in the analysis window. Range 64 …

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Sigma-MT is driven almost entirely from the keyboard. There are no buttons cluttering the chart and no menus to dig through; once the key map is in your fingers, reshaping an entire analysis takes seconds. The keys fall into four groups, mirroring the in-app panel: analysis controls that change what the engine computes, cycle visibility toggles, display…

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What is Sigma-MT?

Sigma-MT is an advanced Expert Advisor for the trading platform Meta Trader 5, available exclusively to VIP cycle analyst members on Sigma-L (founding members).

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It is a direct port and enhancement of the python/numpy version I have developed over the last few years and has been seen previously in posts on Sigma-L. It is a bespoke, unique and powerful way to detect, analyse and act upon statistically significant periodic features in financial markets. It abstracts away many of the more technical aspects of this approach but retains a great degree of adaptability, alongside a streamlined interface and fast computation (processor dependent!). I hope you will enjoy using it as much as I do and discover some cyclic gems in the process.

Sigma-MT is not an indicator/expert advisor in the usual Meta Trader sense. It is a time-frequency analysis engine, drawn from the same family of mathematics used in radar and seismology, pointed at price. Rather than smoothing price and hoping a crossover means something, it decomposes the series into it’s component frequencies, watches how their power evolves through time, and tells you which cycle is dominant right now, where that cycle sits in it’s phase, and how much confidence the detection deserves.

This guide takes you from a fresh install to reading that information. Everything deeper, from the detection mathematics through projection, yield statistics, composites and the Sigma-MT Scanner has its own guide in this series. Here we simply get you on the chart.

For a complete reference to all of the controls for analysis navigation, see Sigma-MT keyboard reference.

For a complete reference to all in the input parameters, see Sigma-MT v1.0 Input Reference

1. Install

Copy Sigma-MT.ex5 into your MT5 data folder under MQL5\Experts (in MT5, go to File → Open Data Folder), then restart the terminal or right-click Expert Advisors in the Navigator and hit Refresh.

Sigma-MT places no trades. It is pure analysis, so there is nothing to configure on the trading side: no DLLs, no web requests, and no permissions beyond a standard EA attach.

2. Attach to a chart

Open a chart on anything liquid. A major FX pair or an index on H1 makes a good first run. Drag Sigma-MT onto it and the input dialog will appear. For your first analysis, change nothing. The defaults are the configuration I run daily: CFAR detection, a target range of 4 to 40 cycles across the sample window, trade boxes on, and the info panel on. Click OK.

One constraint is worth knowing up front. Sigma-MT pauses on the monthly timeframe, because there simply are not enough MN1 bars to support meaningful spectral analysis. Weekly and below is it’s territory.

Within a few seconds the engine completes its first wavelet convolution pass and the display builds at the bottom of the chart.

One aspect worth adjusting at the outset is the display resolution of the panels. This can be adjusted in several ways in the ‘Display Settings’ and ‘Information Panel’ settings. Play around with font sizes and width/height adjustments to fit your screen size as appropriate. Save as an EA preset or save the whole chart as a template named ‘default’ to automatically load this setup on every chart that is launched (not recommended!). Alternatively save as a named template, such as ‘SigmaMT’ so you can load in the settings quickly if required on future charts. This will also be needed when we come to setup the Sigma-MT Scanner workflow.

3. What you’re looking at

Three things appear, and together they carry the entire read. The spectrogram is the heart of the system. Time runs left to right, cycle wavelength runs bottom to top, and colour intensity shows spectral power. A bright horizontal band is a cycle that has persisted (it is stationary), and that persistence, rather than any single point, is what makes a cycle worth your attention for possible trading. To the right of the spectrogram, the summed spectrum shows where power concentrates across frequencies, with the detection threshold overlaid so you can see exactly what the engine considers significant.

Above/below it sits the bandpass panel (press F if you prefer it at the top of the chart). This is the dominant cycle extracted from the noise and plotted as a clean oscillation, with its projection extending past the current bar. It is the Hurst idea made explicit: isolate the dominant rhythm, then let its phase tell you where you are in the swing.

On the left you have the info panel, which summarises everything into a glance. It shows the detected wavelength in real units such as hours or days, the current phase status indicating whether the cycle is at a trough, rising, peaking or falling, and a score box grading detection quality from 0 to 1000 (1000 being a perfectly stationary sine wave and impossible in real markets!) over the recent window. Treat that score as your gatekeeper. Anything above 650 is worth attention, 800 and up is a solid detection, and 900 or more means the engine has found an unusually clean cycle. Below those levels, stand aside, and remember that the absence of a detection is also information.

4. Your first interactions

Press K and a shortcuts panel opens listing every keyboard control, grouped by function: analysis, cycle visibility, display options and utilities. You do not need to memorise anything, because K is always there. Press it again to close.

Now try the controls you will use constantly. The number keys 1, 2 and 3 toggle the short, medium and long-term cycle overlays (the medium and long-term layers activate once you enable their timeframes in the inputs, which Guide 2 covers properly). Press X to draw constant-width envelopes around price, calibrated so that price respects them roughly 95% of the time. Press B to toggle the trade boxes that mark projected inflection zones, and Z to switch on the Kalman extrapolation of the underlying trend. If you want a clean chart, G hides the spectrogram, and C captures a screenshot straight to disk.

There is one mouse interaction worth learning immediately. Click anywhere on the spectrogram and the summation area shows you the frequency spectrum at that exact point in time; click outside it and the view returns to the summed spectrum. Scrubbing through spectral history this way will teach you more about how cycles emerge and decay than any paragraph I can write.

5. Shaping the analysis window

Everything Sigma-MT tells you is computed over a window of bars, and that window is entirely under your control from the keyboard. Press W to extend the sample size and S to contract it. The current size is always visible in the small label beside the dotted line marking the start of the analysis, shown as N= along with S= for the shift and I= for the increment. The engine accepts anything from 64 bars up to 1500, and it will keep the count even for you automatically, since the wavelet transform requires it.

Why would you change it? Because the window defines what the engine can see. A short window resolves recent behaviour sharply but cannot detect a cycle longer than the data it holds, while a long window reveals the slow rhythms at the cost of diluting recent changes. If the spectrogram shows strong power pressed against its upper edge, that is usually a cycle bigger than your window, and a few presses of W will bring it fully into view. The frequency targets are defined per window, so resizing also rescales what each row of the spectrogram represents in real time units; the info panel always translates the detected wavelength back into hours or days for you.

Each press moves the size by the current increment, which you control with Q to halve it and E to double it, anywhere from 1 bar up to 100. Set a coarse increment to reposition quickly, then drop it down for fine adjustment. The I= value in the start line label always shows where it stands.

Shifting through history

The window does not have to end at the current bar. Press A to slide the entire analysis into the past and D to bring it back towards the present, again moving by the increment each press. The S= value shows how many bars into history you currently sit, and when it returns to zero the engine confirms you are back at the live edge. The only limits are the data itself, since the EA will stop you when there is no longer enough history to fill the window, and one display restriction: the price envelopes are unavailable while shifted into the past, because their calibration only has meaning at the live edge.

This is one of the most instructive things you can do with the software. Park the window over a past period, look at what the engine detected and projected with only the data available at that moment, then step forward with D and watch how the cycle evolved. It is the closest thing to a flight simulator for cycle analysis, and it costs nothing.

For larger jumps there is a faster route than holding D. Hold Ctrl and click anywhere on the price chart and the analysis window recentres on that bar, placing it at the middle of the sample. One click takes you from the present to a period of interest months back, and another Ctrl+Click near the right edge, or a few presses of D, returns you home.

Moving through the spectrogram with HILO keys!

The vertical extent of the spectrogram is set by the lowest and highest frequencies the engine targets, and four keys let you reshape that band live. L and O move the low-frequency edge, which governs the longest wavelengths at the top of the spectrogram: L pushes it down towards 2, admitting longer cycles, while O raises it towards 10, trimming them away. H and I move the high-frequency edge at the bottom: H lowers it towards 15, cutting out the fastest, noisiest wavelengths, and I restores them up to the maximum of 40.

In practice these keys are how you walk up and down the frequency axis. If the action you care about lives in the slower cycles, press H a few times to discard the high-frequency clutter and the engine re-spreads its full wavelet budget across the band that remains, so resolution improves exactly where you want it. If a fast intraday rhythm is your target, push the low edge up with O instead. Every adjustment triggers a full re-analysis, and the detection, score and projection all update against the new band, so you can watch in real time how the dominant cycle call depends on where you point the engine.

A useful habit: when a detection seems ambiguous, nudge the band edges and see whether the call survives. A robust cycle keeps being found as the band shifts around it. A fragile one vanishes the moment its supporting noise is excluded, and that fragility is exactly what you want to discover before committing to the projection.

Selecting a custom band

A very useful aspect of the app is the ability to select a custom band of 2 or more frequencies (wavelengths) to examine from the spectra. Simply shift+click once on the spectra to draw one boundary of the band and whilst still holding shift, click somewhere else in the band to establish the bandwidth and second boundary. The panel will also indicate this is a custom (not automatically detected) band, selected by the user.

Press the ‘0’ (zero) key to return to auto detection and remove the custom band of selected wavelengths.

6. Read the cycle

Here is the whole workflow in miniature. First check the score and ask whether the detection deserves your trust. Then check the wavelength and ask whether this is a rhythm you can actually trade on your timeframe. Finally check the phase. A cycle at its trough and rising argues for longs into the projected peak, while a cycle peaking and rolling over argues the reverse. The trade boxes translate that phase logic into a zone on the chart where the next inflection is expected, drawn with an honest uncertainty window rather than a single line of false precision.

That is a complete first analysis, and you have touched perhaps a few keys to help you get around. What you have not yet done is understand why the detection fired, or how to audit a cycle’s historical performance with yield mode on the Y key. That is deliberate. Each of those topics earns its own guide.

Where to go next

Guide 1, Reading the Spectrogram and the Time-Frequency Engine, is the natural next step. It explains what the engine is actually computing and how the short, medium and long-term layers stack into a genuine multi-timeframe read. From there the course runs through detection, projection, yield, composites and the market-wide Sigma-MT Scanner.

Licence: Sigma-MT is provided exclusively to founding members of Sigma-L and is licensed for your personal use only. Redistribution or copying, cloning or in any way reproducing the EA or Scanner files is prohibited without express prior permission.

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.

ΣL Cycle Summary

Here we have a coherent periodic feature that is highly conspicuous across multiple stock markets, including here in the S&P 500, Nikkei and Dax, amongst others. Running at a trading day wavelength of around 82 days, it is peaking now.

The low back in February of this year was likely of larger magnitude, although cycles at this scale are currently fairly noisy and not worthy of posting, yet. However, we can assume the phase of the larger feature is up so a flatter retrace is likely for this smaller cycle.

We will keep an eye on this one going forward, it appears to span the globe in terms of it’s stationarity across multiple major stock market averages and that in itself is remarkable.

Time Frequency Analysis

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ΣL Cycle Summary

As we return to look at the beautiful 80 day cycle feature in Bitcoin we can observe, in this instance, that the larger and exponentially more powerful 40 week wave has influenced the latest down leg significantly. This is standard behaviour for financial markets where the power in the frequency domain is distributed in a 1/f manner, larger features providing much more influence, especially in their acceleration phases. Smaller features can shine through but it is generally when the larger component is at or near an inflection point (a peak or trough of the larger feature, therefore neutral power).

Such is the case here where we have seen a fairly grinding period of price action with an upward bias, courtesy of the bending power of the 40 week cycle. Certainly not the explosive move that is usually characterised by two coherent features that are in phase. This more volatile characteristic is now anticipated here with the two aligned in a bullish manner toward the end of June to early July.

Trade Update

Summary of the most recent trade enacted with this signal and according to the time prediction detailed in the previous report for this instrument, linked below.

Type: Sell - Bitcoin 7th April 2026
Entry: 7th April 2026 @ 71910.20
Exit: 18th May 2026 @ 77432.02
Gain: -7.68%

Time Frequency Analysis

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ΣL Cycle Summary

After the Easter break we return to Bitcoin and what has been a subdued up leg of the lovely 80 day cycle during March. This has been somewhat surprising given the 40 week feature is also now powering up but there are some analogies in the past for this in Bitcoin, notably mid 2024. Amplitude of a cycle (or the volatility / price move amount per leg) is much harder to predict than timing, although we can possibly infer price moves nearer nowtime from the most recent leg. Focusing on what we do know about a financial market’s spectra is optimal (frequency tends to modulates slowly), let price take care of itself, so to speak.

Bulls will be hoping now the sideways price action continues or begins to shape mildly upward, indicating the 40 week is supporting with increased power as the 80 day pushes down simultaneously.

Mid May is the next inflection point (trough) for the 80 day cycle and if price does indeed remain sideways we could see an explosive move up at that point. This would take us just past mid 2026, as the two main periodic features align in phase once more.

Trade Update

Summary of the most recent trade enacted with this signal and according to the time prediction detailed in the previous report for this instrument, linked below.

Type: Buy - Bitcoin 18th February 2026
Entry: 18th February 2026 @ 66419.79
Exit: 7th April 2026 @ 68650.37
Gain: 3.36%

Time Frequency Analysis

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ΣL Cycle Summary

Those who followed the time prediction from the January update will be well satisfied — the crunchpoint flagged for mid to late February has arrived precisely on cue, with the 80 day cycle now in its trough phase and Bitcoin having shed a substantial ~25% from the peak near $90,000. The confluence of the 80 day and the larger 280 day cycle exerting their combined downside influence has played out much as anticipated, and the short trade closed out with an excellent result.

The trough is now upon us, with the frequency modulation running at +/- 5 days from the current position — a relatively tight window that lends reasonable confidence to the timing. With 17 completed iterations since June 2022 at an average wavelength of 83 days, this remains one of the more dependable cyclical features in the cryptocurrency space, and the upgraded ‘A’ class signal classification reflects that robustness. The cumulative component yield over the sample period stands at an impressive 387.71%, a testament to the consistency of this feature over time.

Looking ahead, the next peak range is projected between the 30th March and 8th April 2026, with the central time target falling around the 3rd of April. Bulls will note that this gives a window of approximately six weeks for the up leg to develop — and with the powerful 280 day cycle now set to shift from headwind to tailwind, the conditions for a more meaningful advance are considerably more favourable than they were entering the January trough.

Charts below show a variety of phasings over and above the ~ 80 day feature. Included are some screenshots of our new MT5 EA, due to be released soon. For the latest update on that please take a look at the article here.

Trade Update

Summary of the most recent trade enacted with this signal and according to the time prediction detailed in the previous report for this instrument, linked below.

Type: Sell - Bitcoin 10th January 2026
Entry: 10th January 2026 @ 90385.54
Exit: 18th February 2026 @ 67349.26
Gain: 25.49%

Time Frequency Analysis

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Extrapolation

One of the most requested and often well discussed features is now live. Sigma-MT uses a sinusoidal tuned Kalman filter to decompose the bandpass-filtered cycle into trend and oscillatory components, then projects forward. The extrapolation respects the detected wavelength and current phase, producing a natural continuation rather than a naive repetition. A short cross-fade at the boundary prevents discontinuities where historical data meets the forecast.

Each enabled timeframe — short, medium, and long-term — extrapolates independently, with the projection length configurable in terms of forward cycles.

Inflection Points and Uncertainty

Building on extrapolation, the system identifies upcoming inflection points — peaks and troughs in the projected cycle — and marks them on the chart with estimated timing. The information panel displays a countdown to the next expected inflection alongside phase status.

Since any projection carries uncertainty, the inflection markers include a time window rather than a single bar, giving a realistic range for when the turn is expected. UTC and broker time display are both supported.

Envelopes

Amplitude envelopes now wrap each cycle component, calibrated so that approximately 95% of price action falls within the bands. The envelope width is driven by the instantaneous magnitude from the wavelet transform rather than a fixed offset, so the bands widen and narrow as cycle strength fluctuates. These extend through the extrapolation region, providing a projected price range alongside the cycle forecast. This concept, first espoused by JM Hurst in ‘Profit Magic for Stock Transaction Timing’, is a useful way to visualise the volatility in an instrument defined by the cycle feature driving it

Trade Boxes

Trade zones highlight regions around upcoming inflection points where the cycle is expected to reverse. Each box spans the uncertainty window of the inflection and uses the envelope amplitude to set price bounds. Red boxes mark projected peaks, green boxes mark projected troughs. These provide a quick visual for where the cycle analysis suggests actionable zones may develop.

Yield Mode

Pressing Y activates yield mode, which walks through historical cycle inflections and calculates what a systematic approach of buying troughs and selling peaks (and vice versa) would have produced over the analysis window. The chart displays individual trade legs with percentage gains, a running total, win rate and expectancy. Each enabled timeframe calculates its own yield independently, letting you compare how different cycle horizons have performed on the same instrument.

Composite Instruments

A new cross-instrument analysis mode examines multiple related markets simultaneously. Define a basket of instruments — for example the major USD pairs — and Sigma-MT z-score normalises each price series independently, then averages them in the time domain to produce a single composite series. This averaged series is then fed through the standard wavelet convolution pipeline — the same CFAR detection, bandpass filtering, and phase analysis that runs on any individual chart. By convolving the average rather than averaging individual convolutions, the process identifies periodicity that is genuinely shared across the basket rather than artefacts of summing unrelated cycles.

The composite average line overlays the primary chart, rescaled back into the chart instrument’s price space.

Once the dominant cycle is detected from the composite, Sigma-MT calculates a Cycle Amplitude Ratio (CAR) for each instrument in the basket. CAR measures how much of an instrument's actual price movement falls within the detected cycle band, expressed as bandpass amplitude relative to mean price. The instruments are then ranked by CAR in a volatility ranking displayed alongside the composite line. Higher CAR means a larger proportion of that instrument's price action is cyclical at the shared frequency — making it the better candidate to trade if the wavelength range around the composite cycle is your target signal.

Cycle Band Lock and Manual Selection

The detected dominant frequency band can now be locked, preventing it from jumping to any transient higher frequency power as time progresses. A lock indicator in the info panel shows the current state, toggled by clicking the box or pressing 0.

Beyond locking the auto-detected band, you can now manually define your own frequency range by shift-clicking twice on the spectrogram — once for each boundary. A dashed marker line provides visual feedback after the first click. The selection auto-locks immediately, and an Auto/User indicator next to the lock box shows whether the current band was detected algorithmically or chosen manually. A minimum bandwidth of 5% of total frequencies is enforced to ensure meaningful results

Expanded Keyboard Interface

The beta introduces a comprehensive keyboard-driven workflow. A dedicated shortcuts panel (K key) documents everything, organised into sections:

Interface: F flips the spectrogram position, G toggles spectrogram visibility, P toggles the info panel, < > adjusts panel width, C takes a screenshot.

Analysis Control: W/S adjusts sample size, A/D shifts through history, Q/E changes the increment, L/O/H/I adjusts frequency bounds, Ctrl+Click centres on a bar, and shift+click selects a custom band.

Cycle Visibility: 1/2/3 toggle short/medium/long-term cycles, 0 toggles band lock, X toggles envelopes, B toggles trade boxes.

Modes: Y activates yield mode.

Score Threshold Filtering

A configurable score threshold now filters longer-term cycles, suppressing medium and long-term overlays when their detection score falls below a chosen level (700, 800, or 900). This keeps the chart clean when only the short-term cycle has strong evidence, avoiding visual clutter from marginal detections on higher timeframes.

What’s Next

The beta is currently with founding members for testing. As we work toward a stable release, the focus is on refinement — edge cases, performance, and ensuring everything behaves predictably across instruments and timeframes. Sigma-MT will be listed on the MetaTrader market at release, and for future founding members of Sigma-L.

More to follow.

David

ΣL Cycle Summary

This robust ‘B’ class cycle in TSLA persists, delivering consistent performance across 14 iterations since May 2020, with an average wavelength of approximately 158 days at the current sample. The signal has yielded an impressive 716.31% over the sample period, a testament to it’s stability. Currently, the cycle is troughing, showing mild frequency modulation of +/-14 days, in line with a very stationary periodic feature. Following the recent fairly sideways down leg, the next bullish phase of this cycle is upon us with the upcoming peak anticipated toward the middle of April 2026.

Trade Update

Summary of the most recent trade enacted with this signal and according to the time prediction detailed in the previous report for this instrument, linked below.

Type: Sell - TSLA October 21st, 2025
Entry: 21st October, 2025 @ 442.60
Exit: 30th January, 2025 @ 429.34
Gain: 3.00%

Time Frequency Analysis

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Since the initial alpha announcement, development on Sigma-MT, a Meta-Trader 5 expert advisor, has progressed steadily and is nearing beta. This update covers some improvements to the underlying time-frequency analysis, visual refinements, and how the tool integrates with the recently announced scanner.

Time-Frequency Engine Updates

The multi-timeframe analysis system performs independent wavelet convolutions for each enabled timeframe - short, medium, and long-term. Each process transforms the price series into the frequency domain, applies a rapid convolution process and returns a time-frequency power matrix showing how spectral energy evolves across the analysis window.

When analysing higher timeframes, the system retrieves the appropriate bar data, performs the full convolution at that resolution, then interpolates the resulting bandpass signal back to the chart timeframe for overlay. This interpolation maps the higher timeframe’s filtered output onto the short-term bar structure, accounting for the timeframe ratio. A cycle detected on H4 while viewing an M15 chart will display correctly aligned with the underlying price bars.

Dominant cycle detection begins by using CFAR (Constant False Alarm Rate) as the default method - the same adaptive thresholding technique used in radar systems. Rather than applying a fixed SNR threshold across all frequencies, CFAR calculates a local threshold for each frequency bin based on the surrounding spectral energy. Reference cells on either side of each bin establish the local noise floor, with guard cells preventing the signal itself from contaminating the estimate. The detection threshold adapts to the spectral shape, maintaining consistent false alarm probability regardless of whether you’re examining a flat spectrum or one with significant slope.

The ranking score combines multiple metrics: peak prominence above the CFAR threshold, spectral isolation from neighbouring frequencies, amplitude stability across the recency window, and consistency of the instantaneous frequency estimate. A high score indicates a cycle that stands clearly above the noise, maintains stable characteristics, and persists through the analysis period rather than appearing transiently.

Wavelength display throughout the interface now uses adaptive unit conversion. The base unit is determined by your chart timeframe - minutes for M1-M30, hours for H1-H12, days for daily charts. Values then convert upward when they exceed natural thresholds: minutes to hours beyond 120, hours to days beyond 24, days to weeks beyond 100. This ensures the Y-axis labels, information panel, and cycle readouts all express wavelengths in immediately meaningful terms.

Workflow with Sister Scanner App

Sigma-MT and the Sigma-MT Scanner serve different analytical needs within the same workflow.

The scanner processes your entire market watch, applying the same wavelet convolution engine across every instrument and ranking results by cycle strength. It answers the question of where to focus attention. Which markets are exhibiting periodicity now?

Sigma-MT provides the detailed examination. The full spectrogram reveals how cycle strength evolves through time, the bandpass filter isolates the dominant component and the information panel displays phase status, wavelength, and detection score. A cycle flagged by the scanner will appear with identical characteristics when examined in Sigma-MT - the underlying detection will be consistent across both tools.

Keyboard Configuration

So far we have added some very useful keyboard shortcuts to help the user navigate the spectra in an analysis.

Analysis Window:

• A / D - Shift analysis left/right through price history

• W / S - Increase/decrease sample size (N)

• Q / E - Decrease/increase increment value

• Ctrl + Click - Centre analysis on clicked bar

Frequency Bounds:

• L / O - Decrease/increase lowest frequency of analysis

• I / H - Increase/decrease highest frequency of analysis

Display:

• F - Flip spectrogram/bandpass to top or bottom of chart

• P - Toggle information panel

• Left click on spectrogram - show spectral summation and detection threshold at the clicked timepoint

• < / > - Increase/decrease panel width

Cycles:

• 1 / 2 / 3 - Toggle short/medium/long-term cycle visibility

• 4 - Toggle composite cycle overlay
  

Availability

Sigma-MT remains available to a small group of founding members for testing and I thank them for their help. As we approach a stable release, it will also be listed on the Meta-Trader market for all, in addition to being available for all new founding members of Sigma-L at release.

More updates to follow and exciting features to add, not least extrapolation, which everyone seems to love!

David

The scanner applies the same robust wavelet convolution engine that powers Sigma-MT across every instrument in your market watch, simultaneously analysing multiple timeframes and ranking results by cycle strength. In seconds, you have a prioritised list of instruments exhibiting the most statistically significant cyclical behaviour.

Under the Hood: Time-Frequency

Under the hood, the scanner leverages the same frequency-domain convolution that makes Sigma-MT so fast in MT5. Each instrument undergoes a full wavelet transform, with automatic cycle detection using either a simple SNR (Signal-to-Noise Ratio) and filter or CFAR (Constant False Alarm Rate) algorithms - the same detection methods used in radar systems for picking signals out of noise.

The cycle ranking score then combines multiple factors: peak prominence above the noise floor, spectral isolation, amplitude stability, frequency consistency, and persistence across the analysis window. To be clear this isn’t just finding any cycle - it’s finding cycles that exhibit the characteristics of genuine periodic phenomena rather than random fluctuations.

A scan of several hundred instruments across multiple timeframes completes in seconds.

Intelligent Phase Grouping

This is where the scanner becomes more than just a ranking tool. When analysing multiple timeframes, the scanner can automatically identify phase confluence - instruments showing aligned cycle phases across different time horizons.

When the same symbol exhibits similar phase, these groups lock to the top of the results, immediately drawing your attention to potential multi-timeframe confluence setups.

However, matching phases alone isn’t enough. To ensure meaningful alignment rather than the same cycle detected at different resolutions, the scanner validates that each higher timeframe shows a wavelength greater than at least 1.5 times the previous timeframes’ detected cycle. This filters for genuine nested cycle structures - the kind of fractal patterns that Hurst and others identified as characteristic of market behaviour.

Multi-Timeframe Analysis

The scanner has capacity for up to five timeframes running at simultaneous analysis. The scanner will evaluate every market watch instrument against each timeframe, giving you a comprehensive view of cyclical activity from intraday through to longer-term structures, if required.

Results display the detected wavelength (automatically formatted in minutes, hours, days, or weeks), the cycle rank score, timeframe, and current phase status. Click any row to instantly open a chart with that symbol and timeframe - ready for deeper analysis with the main Sigma-MT EA.

Filtering & Configuration

Focus your attention with built-in filtering (more features to come):

• Minimum Rank Threshold - Hide weak cycles below a specified score

• Minimum Wavelength - Filter out very short cycles that may represent noise rather than tradeable features

• Recency Bias - Weight the analysis toward recent price action

All active parameters display clearly at the top of the interface, so you always know exactly what you’re looking at:

Bars: 500 | Frequency Range: 5-40 | Detection: CFAR | Recency Bias: 50% | Analysis on Median Price | Min Wavelength: 30 min | Timeframes: M1, M15, H1

The Workflow

The scanner and Sigma-MT EA are designed to work together although one can use the scanner standalone if you have a system already setup to identify periodicities in markets.

1. Scan - Run the Scanner to identify instruments with strong cyclical behaviour. Set the scan to loop continuously after completion, manually by pressing ‘R’ or at set intervals.

2. Filter - Use phase grouping and rank thresholds to surface the most interesting opportunities

3. Click - Open a chart directly from the scanner results

4. Analyse - Apply Sigma-MT for detailed time-frequency analysis, phase projection, extrapolation and cycle visualisation. Automatic trading will also be in place further along the development process.

This workflow transforms cycle analysis from a manual, instrument-by-instrument process into a systematic scan of the entire market.

The scanner is currently in development alongside the main Sigma-MT EA and will be available to new founding members on Sigma-L in addition to being directly available on the MQL store. I believe this combination of tools - broad market scanning paired with deep individual analysis - represents something genuinely new for retail cycle analysts. I am excited to finally be able to share the insight I have been using for the past few years with others.

More updates to follow as development progresses. Thank you for your continued support.

David

So many people have asked me over the last few years whether they can use my software and I am always flattered by this. I developed it initially for myself to examine the claims by Hurst and others of the existence of periodic features in financial markets. I never really intended it to be used by others although we successfully built a multi instrument live scanner which was somewhat useful! Since then I am grateful to have shared many analyses with subscribers here and on X for those who are interested in this rather niche but fascinating area.

I am pleased to say, therefore, over the holiday period and just before, I began development work on porting over the familiar time frequency analysis readers have seen over many years on Sigma-L, to Metatrader’s MQL language. The main question was one of speed. I wanted to ensure that this new version would be fast enough to use intraday (it updates on every new bar) and also flexible enough to perform the many computations required for a robust time frequency analysis. The underlying process is already highly optimised, performing the calculations and wavelet formation all in the frequency domain.

Fortunately, with MQL’s C based language the vectorisation present in the python/numpy version was fairly easily transferred and has produced excellent results. A convolution over 1000 points and 100 frequencies takes less than a quarter of a second.

Enhancements

Over the last few years I have collated a large list of enhancements I want to bring to this kind of market analysis, both from a user experience point of view and from a signal processing point of view. Some of the expectations for features on this expert advisor, as we move toward release, will be (non exhaustive):

• Ability to shift analysis anywhere on the chart (currently live in alpha 1.0)

• Ability to quickly move up and down the frequency spectra to inspect any features of interest (currently live in alpha 1.0)

• Automatic intraday updating (currently live in alpha 1.0, updates on each new bar)

• Time frequency analysis on return series

• Multi length analysis and composite lines, combining multiple cycles of influence and true, numerically evidenced based compositing / extrapolation

• Auto detection at all timeframes

• Tuned Kalman filter extrapolation

• Composite analysis of many instruments for phase correlation

• Aesthetic configuration (colours, spectrogram etc)

• High pass filtering at the touch of a button

• Future time phase estimation for all detected features

• Social media sharing

Currently the alpha is available for testing to founding members only but as we draw closer to something I feel is ready, we will likely list it on the Metatrader shop and also make it available to future founding members here. The exact format remains to be decided.

I can’t wait to see lots of very cool cycle charts coming up on my X feed over 2026 as you guys get your hands on one of the most powerful analysis techniques out there!

Do continue to watch this space for updates, thank you all for your continued support.

David

ΣL Cycle Summary

Happy new year to all!

In this much anticipated update we take a look, once again, at one of the few markets providing cyclical dominance at the moment, the ubiquitous 80 day cycle in Bitcoin and the wider spectra going forwards.

The up leg from late November was a damp squib of a move, suggesting the now more apparent ~ 280 day cycle (shown below) is still exerting downside influence. This much larger wave is considerably more powerful than the 80 day feature, such is the nature of power distribution in financial markets. Over the course of the last few years it has featured a rather wide and therefore unpredictable, practically speaking, modulation. For that reason it has not featured on Sigma-L before although I have mentioned it briefly on X. That modulation has diminished somewhat recently and even more so when the addition of other liquid cryptocurrencies is analysed in a composite, also shown below.

The crunchpoint appears to be ahead of us in mid - late February with troughs of the 80 day and 280 day broadly aligning in phase. That said, the modulation is still quite wide in the larger feature so it may well be a case of sideways until then, which is even better for bulls. The 30 day carries on regardless, making excellent undulations at the lower resolution and is easily discerned by our time frequency method, see below. Useful for traders with a shorter time horizon I have no doubt.

In summary, not long to wait for the more bullish crypto enthusiasts with the powerful 280 day cycle set to provide an excellent guide in 2026. Alongside that the 80 day looks to be maintaining it’s power, providing even more granularity to the swings.

Trade Update

Summary of the most recent trade enacted with this signal and according to the time prediction detailed in the previous report for this instrument, linked below.

Type: Early Buy - Bitcoin 17th November 2025
Entry: 17th November 2025 @ 92100.60
Exit: 10th December 2025 @ 90646.30
Gain: - 1.58%

Time Frequency Analysis

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ΣL Cycle Summary

In this sample of Gold (XAUUSD) over the last 12 years we reveal a periodic feature that has been present throughout, exhibiting excellent spectral spacing within a bandwidth spanning ~ 1000 to 100 days. Sporting a wavelength around 500 days (or 16 months) this feature has maintained it’s power even through the tremendous and linear uptrend since early 2024. The phase is currently peaking with the next trough due late 2026. Indeed this feature is also clearly present in PHYS and GDX (shown below via composite), something that may be obvious but is not always the case at the shorter wavelengths.

The highpass filtered series below also reveals the spectacular amplitude increase passed through to the cycle around 500 days from underlying trend. A breach of the red standard deviation line is a high probability reversal signal and indicative of a peak for this wave.

Time Frequency Analysis

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