How It Works
From Raw Data to
Actionable Insights
Detect hidden market cycles using Goertzel DFT, Bartels significance testing, and the Hurst exponent. Turn market noise into structure you can read.
[01] The Challenge
Markets are complex. Traditional tools fall short.
Markets Are Noisy
Price data contains countless overlapping signals, trends, and random fluctuations. Traditional analysis struggles to separate meaningful patterns from noise.
Cycles Are Hidden
Recurring market cycles exist at multiple timeframes, but they are invisible to conventional charting tools. You need specialized methods to reveal them.
[02] Our Solution
A systematic four-step process
Transform raw price data into statistically validated cycle projections.
Upload Your Data
Import OHLCV from any market: stocks, FX, crypto, commodities, indices, or 800,000+ FRED economic series. CSV upload or live provider fetch.
- All timeframes (1m to monthly)
- Live data: Yahoo, FRED, more
- CSV upload for private datasets
Remove Market Noise
Three detrending methods (linear, HP filter, first-difference) strip the long-term trend and random noise so the spectrum sees the cyclic component clearly.
- Linear, HP filter, or first-difference
- Choose per analysis, no black box
- Preserves the underlying cyclic structure
Detect Hidden Cycles
Goertzel DFT scans hundreds of candidate periods and surfaces the dominant ones. Bartels test then asks: is each cycle statistically real, or is it random noise dressed up as a pattern?
- Goertzel DFT spectrum
- Bartels p-value per cycle
- Hurst exponent for regime classification
Identify Turning Points
Combine the cycles that pass the test into a composite wave projected forward. Convergence zones show where multiple cycles bottom or top together based on historical phase.
- Pick which cycles to include
- Composite wave projection
- Convergence zones (Nest of Lows / Highs)
[03] Why FractalCycles
What sets us apart
Statistically Validated
Every detected cycle gets a Bartels p-value. You see the number, you decide what to trust. The math is shown, not hidden.
Static and Dynamic Engines
Pick how the composite behaves: Static locks magnitudes at analysis time. Dynamic re-runs the math fresh on every new bar so magnitude and phase breathe with the chart.
Full Control
You pick which cycles get weight in the composite. Toggle them on or off, crop the data, swap the detrender. The math runs your way.
[04] Who Uses FractalCycles
Built for serious investors, analysts, and researchers
Swing Investors
Identify potential cycle turning points to inform your analysis. Gain additional context on positions held for days to weeks.
Position Investors
Use longer-term cycle analysis to understand market rhythms. See where you are within larger cycle patterns spanning weeks to months.
Technical Analysts
Add a quantitative cycle dimension to your existing analysis. Complement chart patterns and indicators with statistically validated cycles.
Quantitative Researchers
Explore cycle phenomena across different markets and timeframes. Export data for further analysis in your own systems and models.