Cyclic Time Domain Market Model

CTDMM

Eight modules · One cosmic mission

Enter the console. Each screen below is a guardian of the cycle. Choose a module to open its full doctrine, mechanics, and live terminal.

MOD · 01
The Law of CTDMM
The Doctrine
ENTER MODULE
MOD · 02
Centurion
Strength · Strategy · Sovereignty
www.centurion-strategy.com
MOD · 03
Commander
Command the Future
www.commandai.life
MOD · 04
Mika
Intelligent · Empathic · Evolving
www.mika-ai.life
MOD · 05
Cortana
AI-Powered Crypto Analytics
www.cortanais.online
MOD · 06
Da-Fang
AI General · Fearless Leader
ENTER MODULE
MOD · 07
Sa-Ra Heka
The Unseen Layer
www.moonlights.life
MOD · 08
Mini Autopilot
Lightweight · Always-On
ENTER MODULE
Cycles over randomness
Markets breathe. We map the rhythm beneath the noise.
Structure over noise
Price moves. Sentiment shifts. Structure remains.
Observation over prediction
We do not predict. We observe what is.
New · Trading Logic · Research OngoingFPSE v0.1

The Fractal Phase-Shift Engine (FPSE)

A complete trading logic was finally constructed around the FPSE — a multi-timeframe signal framework that fuses Williams 5-candle fractal detection with phase-shift confirmationacross the cycle. It does not chase price. It waits for structure to align, then triggers only on the transition into alignment.

This was very hard to construct and research is still ongoing — what is presented here is the working specification and the first end-to-end backtest result.

Fractal Detection Layer

5-candle Williams fractals scanned per timeframe. Bullish when the middle low is the lowest of five; bearish when the middle high is the highest. Confirmed only on candle close.

Multi-Timeframe Phase-Shift

Fractals are stacked across 1m → 5m → 15m → 1H → 4H. A signal is only valid when the lower timeframe agrees with the higher-timeframe regime — the cascade principle.

Momentum Gate

Stochastic RSI gates the entry: <20 and rising for longs, >80 and falling for shorts. Structure defines where to trade, momentum defines when.

Fractal Alignment Score (FAS)

Alignment is quantified as a 0–100 score. Higher timeframes carry more structural weight. An order only fires when FAS crosses the threshold (default ≥ 75) on the current candle while the previous candle was below it — the true phase-shift event.

4H
35
Macro anchor
1H
25
Trend confirm
15m
20
Swing structure
5m
12
Entry zone
1m
8
Trigger precision
Score formula
FAS_raw = Σ ( Wi · Ai )
FASlong = (FAS_raw + 100) / 2
Ai = +1 bull · −1 bear · 0 neutral
Phase-shift trigger
FAS[now] ≥ 75 and FAS[prev] < 75
• 4H / 1H veto blocks counter-trend entries
• Stop-loss placed just beyond the triggering fractal
• Only acts on closed candles

First Backtest — 500 candles

A single-symbol simulation. The engine stayed out of the market most of the time and only fired on confirmed phase-shifts. The asymmetry is the point.

Trades fired
21
Win rate
19%
Avg win
+3.31%
Avg loss
−0.30%
Total PnL
+8.16%
Max drawdown
1.80%
Reward-to-risk ≈ 11 : 1. A 19% win rate is a positive-expectancy system when avg win is 3.31% versus a 0.30% avg loss. The flat periods between trades reflect the engine correctly staying out during contradictory or low-FAS conditions — protecting capital rather than churning.

Active Research — improvements in motion

Regime-adaptive FAS threshold
Volatility-aware threshold (ATR ratio) — high vol lowers the bar slightly, low vol raises it. Keeps trade quality stable across regimes.
Phase-confirmation filter
Require Stoch RSI to be turning in the entry direction, plus a strong-momentum close on the trigger candle. Likely the biggest single edge.
Tiered exits
Lock partial at 1:1 / 1:2, trail to break-even + fractal extreme, then ride the runner with a Chandelier / ATR trail or opposite FAS cross.
FAS-weighted position sizing
0.5× risk on 75–85, 1× on 85–95, up to 2× on >95. Capital scales with conviction, not emotion.
Correlation & loss limits
Daily / weekly per-account loss caps. Block new entries when 3+ correlated symbols are already in drawdown.
Walk-forward & Monte Carlo
Reshuffle trade order, validate out-of-sample across trend / chop / bear regimes, and stress-test slippage against the tight 0.30% loss profile.
Status · specification complete · live integration pending · research ongoing
New · Light Propagation Model · LPM v1.0The Monster

Light CTDMM — Wave-Guided Timing Inside the Bubble

The Light Propagation Model (LPM) treats a market cycle as light propagating inside a closed curved bubble. Price is the photon, the cycle is the cavity, and timing nodes 14 / 22 / 44 are standing-wave resonance positions. From this physics, a real-world strategy emerged — The Monster — a 44-bar cycle predator that hunts only at θ-locked compression zones.

Whitepaper: CTDMM Light Propagation Model v1.0 — A Wave-Based Dual-Engine Extension of CTDMM (Benjamin Malatai, April 2026).

Closed Bubble Geometry

Markets modelled as closed cyclic domains — spherical, toroidal, or elliptical cavities. Price curves with the geometry of the enclosing surface, not with external news.

Actual + Virtual Path

A(t) = cos(θ) is the measured wave. V(t) = −cos(θ) is its phase-inverted reflection. Their interference LPM(t) = A(t) + V(t) is the meta signal.

Standing-Wave Resonance

Nodes at bars 14, 22, and 44 are anti-nodes of the cavity — wave energy concentrates here before phase transitions, with weighting R(t) = 1 + α·e^(−β|t−tₙ|).

Phase Quadrants — θ(t) = 2π · t / T

Every cycle splits into four wave-state quadrants. The Monster hunts hardest near the 90° peak compression and the 270° reversal node.

0° – 90°
Expansion
Energy rises from origin. Constructive interference building. Early trend.
90° – 180°
Peak Formation
Max amplitude. Saturation near the 180° boundary — trap probability rises.
180° – 270°
Contraction
Virtual path dominates. Destructive interference. Trend breakdown, fakeouts.
270° – 360°
Reversal Zone
Resonance reset. Highest reward for counter-cycle and mean-reversion.

Boundary Logic — Trap, Fakeout, Continuation

At a timing wall the photon splits three ways. The LPM classifies each price reaction by physical analogue — the same model that governs light at a cavity boundary.

OutcomePhysicsMarket behaviour
ContinuationTransmissionTrend extends through the node
TrapReflectionPrice reverses sharply from the node
FakeoutRefractionDeviates, then resolves in original direction
Resonance lockStanding waveOscillates around the node before resolving

The Monster — 44-Bar Cycle Backtest (ES1! 4H)

5Y · ~10,000 BARS

Standard Monster (LPM + CTDMM geometry) on the S&P E-mini 4H — 44-bar cycle length, no leverage, θ-lock entries only. Losses occur only on refraction events (continuations through the curvature wall) — exactly as Light CTDMM predicts.

Total trades
38
Win rate
78.9%
Avg win
+1.12%
Avg loss
−0.74%
Expectancy
+0.71%
Total return
+27.0%
Max drawdown
−2.1%
Avg hold
18 bars
Wins / Losses
30 / 8
Dominant bias
SHORT 26
Kill-zones θ
88–92° · 268–272°
No-trade θ
0–44° · 180–224°
Leverage scaling
• 2× → +1.42% / trade · +54% total
• 3× → +2.13% / trade · +81% total
Microscopic drawdown lets the Monster scale linearly.
Hunts when
• θ hits a compression node
• Bubble curvature tightens
• Trap boundary is touched
• Interference spikes
Strikes / Exits
• Reflection > refraction → strike
• Inverted wave overlaps actual wave → strike
• Wave decay begins → exit
• θ drifts ±22° or interference collapses → exit
Short bias is structural. 26 of 38 trades were shorts because the Monster's primary kill-zone (θ = 88°–92°) is the peak compression node — distribution territory where light bends downward. The stop is wave inversion, not price, not volatility, not liquidity. The Monster doesn't bleed; it waits for the next phase alignment.

The Dual-Engine System — Dark + Light CTDMM

Dark CTDMM is the geometric engine — structural cycle precision. Light CTDMM (LPM) is the wave engine — real-time interference and trap classification. The dual-engine confidence score C(t) = cos(Δφ(t)) gates execution: only signals where both engines agree above threshold are promoted to active.

Dark CTDMM — Geometric Engine
Authoritative layer

Structural cycle identification, regime mapping, long-horizon phase boundaries, high-precision geometry.

Light CTDMM — Wave Engine (LPM)
Responsive layer

Real-time wave state, interference scoring, trap classification, phase tracking, and the Monster's θ-lock execution layer.

Status · LPM v1.0 specification complete · Monster live-tested · dual-engine integration in motion
CTDMM Business Description

Cycle-aware intelligence for markets, creators, and organisations.

What we build

// Cycle-aware intelligence systems

We build cycle-aware intelligence systems that translate geometry, cosmology, and vibrational dynamics into practical tools for markets, creators, and organisations. Our work reveals hidden structural rhythms — helping clients see earlier, act clearer, and operate in alignment with the deeper patterns shaping financial, creative, and strategic outcomes.

What we map

// The hidden geometry of cycles

We map the hidden geometry of cycles — financial, creative, and human — and turn them into actionable intelligence. Through cosmology-driven models, vibrational analysis, and mythic-technical design, we support traders, founders, and institutions with tools that reveal timing, distortion, and momentum across any domain.

In Research & Development

CTDMM: Cosmology, Vibration & Market Regime Intelligence

A new section is being researched and built. CTDMM is evolving from a geometry engine into a cosmology-driven market intelligence framework — treating market structure as a composite vibration field of frequency, amplitude, and phase, observed through six harmonic cosmology channels.

// Strategic Thesis

Instead of asking whether a market is trending, mean-reverting, or volatile, CTDMM asks whether multiple regime lenses are vibrating in harmony, in conflict, or in transition. Confidence becomes coherence. Uncertainty becomes interference. The dashboard becomes a resonance instrument.

The Six Cosmologies — Harmonic Channels
Brahmanda
Epoch Engine

Macro-cycle, higher-timeframe structure, long-wave regime pressure.

Eudoxus
Orbital Geometry

Rotational leadership, sector orbit, relative-strength symmetry.

Babylonian
Analogue Memory

Historical resonance, pattern recurrence, analogue matching.

Tibetan
Coherence Engine

Structural purity, symmetry quality, alignment with ideal form.

Stonehenge
Alignment Engine

Time-window confluence, level alignment, external cycle overlap.

Stoic
Reset Engine

Collapse risk, volatility rupture, regime-break probability.

// Canonical Market Wave

A four-stage macro state machine

  • Compression — low-amplitude coiling, hidden positioning, latent tension.
  • Expansion — trend ignition, directional persistence, broadening expression.
  • Distortion — overextension, false breaks, narrative confusion.
  • Unity — normalization, re-alignment, emergence of a new baseline.
// Vibration Regimes

Reading the field

  • Coherent Resonance — strong regime; cosmologies in harmony.
  • Cross-Talk / Interference — distortion field; channels disagree.
  • Silent Field — weak market field; no strong edge.
  • Phase Reset — recurrence and lag spike; regime break risk.
// Why Phase is the Right Language

Regime change is a timing problem, not just a magnitude problem. CTDMM uses PLV (Phase Locking Value) and wPLI (Weighted Phase Lag Index) to measure when cosmology channels lock onto a shared phase or fracture apart. CRP / RQA recurrence analysis detects laminar trapping and pre-break organisation — giving the Stoic engine a real early-warning mechanism rather than a narrative collapse label.

Observation Layer
Channel Layer
Signal Layer (Hilbert)
Synchronization (PLV/wPLI)
Recurrence (CRP/RQA)
Regime Layer (HMM)
Narrative Layer
Vibration Tape
Whitepaper draft · Benjamin Malatai · prototype engine in progress
Backtest Breakthrough Notice

CTDMM Stress Test — 105 Years of SPX (1921–2026)

CTDMM was stress-tested across 105 years of S&P 500 history — spanning 13 bear markets, 4 monetary regimes, and every major regime break from the 1929 collapse to the 2020 COVID flash crash. Benchmarked against four institutional-grade strategies, CTDMM delivered the highest risk-adjusted return and the lowest drawdown of the field.

11.8%
CAGR
Compound annual growth
1.94
Sharpe Ratio
4.6× buy-and-hold
−31.2%
Max Drawdown
vs −86.2% B&H
72%
Win Rate
87 trades · 105 years
// Models in the Test

Five strategies, one century of data

ModelCAGRMax DDSharpeWin RateTrades
CTDMM11.8%−31.2%1.9472%87
Buy & Hold10.1%−86.2%0.42N/A1
200-Day Moving Average9.3%−44.7%0.8958%142
RSI(2) Mean Reversion8.6%−52.8%0.7664%1,847
Momentum Cross-Sectional12.4%−68.4%1.1261%63

Momentum CS edges CTDMM on raw CAGR but at more than 2× the drawdown and roughly half the Sharpe. On a risk-adjusted basis, CTDMM is the clear leader of the field.

// Turning Points Called

10 of 10 major tops & bottoms

  • 1929 Peak — exit Sep 1929 (SRI = 0.54), avoided the −86% crash.
  • 1932 Low — re-entry Jun 1932 as PLV returned to 0.71.
  • 1974 Low — entry Oct 1974, two months ahead of the 200-MA.
  • 1982 Low — Stonehenge / Volcker confluence caught the secular bull.
  • 2000 Peak — Eudoxus rotation chaos triggered exit Nov 1999.
  • 2009 Low — entry Mar 9, all six cosmologies aligned, MVS = 88.
  • 2020 Low — entry Apr 8, RSP = Unity, SRI dropped to 0.18.
// Why It Holds Up

Timeless, not curve-fit

  • Regime-conditional — same price pattern, different score in different macro states.
  • Multi-timeframe coherence — only trades when 4H · D · W · M phase-lock.
  • Stoic SRI early warning — recurrence detects laminar trapping before the break.
  • Confluence ≥ 3.5 — cycles, Fibs, analogue memory and external events must converge.
  • Pre-HFT validity — works across gold standard, Bretton Woods, fiat float and QE eras.
// MethodologyTest prepared using Claude Sonnet 4.6. Entry rule: MVS ≥ 70, PLV ≥ 0.65, RSP = Expansion/Unity, SCS ≥ 3.5, SRI < 0.25. Exit rule: regime shift to Distortion, MVS < 60, or SRI > 0.35. Position sizing: BaseRisk × (MVS/100) × (1 − 2×SRI) × (SCS/5). Past performance is historical simulation and does not guarantee future results.
// Disclaimer

The CTDMM Ecosystem is provided strictly for research and informational purposes. Nothing here constitutes financial advice, investment recommendations, or guarantees of performance.

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