Blog

The Hierarchy of Time: Why Multi-Timeframe Analysis Comes First in Cycle Research

Weekly before daily, 4H before 1H, 1H before 15M. Markets are a stack of nested cycles, and that structure dictates the order of analysis. The full top-down method, illustrated on live Bitcoin data across five timeframes.

Why Your Turn Marker Missed (and the Live Analysis Didn't)

A subscriber's manually-marked turn kept missing while re-running the live analysis converged on the actual turn. Why the date shifts between runs, and when a saved screenshot is still safe to use.

Hurst Exponent for Bitcoin: What the Data Actually Shows

Bitcoin's Hurst is 0.56 over 900 daily bars. Four methods, a rolling read across 30 monthly snapshots, and a side-by-side against SPY and gold: trending in 83% of windows, mean-reverting in zero.

Why Most Cycle Analysis Fails (And How Statistical Validation Fixes It)

Four documented failure modes account for nearly every spurious cycle in retail trading content: Slutsky-Yule filter cycles, wavelength drift, regime mismatch, and uncorrected multiple testing. Each has a fix in the spectral-analysis literature.

Why Static and Dynamic Cycle Analysis Both Matter

Static cycle analysis anchors structural rhythm. Dynamic analysis re-estimates period and phase each bar. See why serious analysts use both, with motion-graphic examples.

Spotting Hurst Cycles in the Spectrum: A Conversion Table from Weekly to Intraday

A conversion table and a three-layer gating rule for matching detected periods to J.M. Hurst's eleven named cycles, on any instrument and any timeframe.

Where Is the 80-Day Cycle Right Now? Cross-Asset May 2026 Snapshot

A daily-bar snapshot across 22 instruments asks one question: which markets show a cyclic component in the 70-90 day band J.M. Hurst named "80-day," and where are they in it.

Stop Chasing the One Perfect Cycle: How Confluence and Alignment Changed Everything

Most traders who discover cycle analysis make the same mistake: they look for a single dominant cycle that explains everything. Here is why confluence of well-aligned cycles, confirmed by DEMA, produces far better results.

FractalCycles Dashboard Controls: What Every Card and Button Does

A practical walkthrough of the five key controls on the FractalCycles analysis dashboard.

How to Read the Regime Dashboard

The regime cards tell you what kind of market you are in before you trade. Here is what each card measures, how they cross-validate, and what to do with the result.

How to Confirm Cycle Turns with FLD and DEMA

The Hurst Envelope shows where price sits in each cycle. FLD and DEMA confirm when the turn actually happens. Here is how to add and customize both.

How to Use the Hurst Envelope for Cycle Analysis

Learn how to read the Hurst Envelope on FractalCycles. Covers the classical default method and the advanced approach using detected cycle periods from spectral analysis.

How to Select the Right Cycles: The Frequency Band Method

Detected cycles are only useful if you select the right ones. The Frequency Band method picks the strongest short, medium, and long-term cycle for a composite that captures structure at every timescale.

What If Most Technical Analysis Starts Too Late?

Most analysts react to price after it moves. But what if the structure driving that movement was already measurable? A look at Bitcoin through the lens of cycle analysis and why timing beats narrative.

What Crude Oil's Cycles Look Like Right Now

We ran Crude Oil through the FractalCycles spectral analysis engine. Here is what 24 detected cycles, a Hurst exponent of 0.522, and a 2-cycle composite projection reveal about crude oil's structural rhythm.

How Composite Wave Projections Work (Tesla Demo)

What is a composite wave, and how do you read one? We walk through the concept step by step using a real Tesla (TSLA) cycle analysis, from detecting cycles to building and interpreting the projection.

Why causal explanations dominate despite structurally driven price behavior

Narrative explanations dominate financial discourse not because they govern price behavior, but because human cognition seeks linear causality. In contrast, structural analysis emphasizes the recursive, phase-dependent nature of price behavior across scales, where explanation follows emergence rather than precedes it.

Markets as self-similar, fractal systems of price discovery

Markets are best understood not as linear processors of information but as systems exhibiting recursive structure. Price reflects nested cycles of expansion and contraction across timeframes. This structural view prioritizes patterns that recur across scales, irrespective of narrative explanations.

Bitcoin Cycles: What If Time Matters More Than Price?

Markets move through time before they move through price. What looks like noise is often a cycle completing its phase.

Cycles Are the Ultimate DCA Tool for Crypto Investors

Hourly Forex Price Action Observed Through Composite Cycle Structure

Bitcoin observed through a 99-week composite cycle