Institutional flagship program

ZEUS Engine

Quantitative Research-to-Production Systems Engineering

Arquitectura profesional para convertir datos financieros en investigación validada, señales reproducibles y ejecución algorítmica gobernada

$2,000

5 phases · 12 modules · 36 chapters · capstoneATENEA → MNEMOSINE → CHRONOS → AEGIS → TALOSOne professional courseInvitational

Course roadmap · 5 phases

Phase I

ATENEA

Quantitative Data Foundation

Phase II

MNEMOSINE

Quantitative Data Runtime

Phase III

CHRONOS

Temporal Research Governance

Phase IV

AEGIS

Quantitative Research Factory

Phase V

TALOS

Production Signal Runtime

One professional course. Five internal phases in this order. Twelve modules and thirty-six chapters live inside them. ZEUS Engine — Professional Capstone sits outside that count. Orientation is outside 12/36. Coursework clock is not sealed. Phases are not sold separately.

Mission and vision

Mission

Teach a verifiable chain that turns financial data into quantitative evidence, research artifacts, production signals, and controlled execution — a strategy is ready for production when that chain exists, not when a backtest looks good.

Vision

Practitioners who can design a governed research-to-production system: certified input, ZEUS data runtime, temporal research governance, a sealed research factory, a production signal runtime, and controlled execution.

Description

ZEUS Engine is Quantitative Research-to-Production Systems Engineering. One professional course. Public name ZEUS Engine. List $2,200.

A strategy is not ready for production because it has a good backtest. It is ready when a verifiable chain exists from known data to the signal and from the signal to execution.

Official phase chain

ATENEA → MNEMOSINE → CHRONOS → AEGIS → TALOS.

These names are the internal phases of this course. They are not independent products.

DATA to EXECUTION

DATA → KNOWLEDGE → HYPOTHESIS → VALIDATION → EVIDENCE → ARTIFACT → SIGNAL → ORDER → EXECUTION.

Five phases

ATENEA — Quantitative Data Foundation. Acceptance / certification of ZEUS input. ATENEA does not rebuild a Financial Data Center.

MNEMOSINE — Quantitative Data Runtime. Operationalize ATENEA-accepted contracts inside ZEUS: historical, incremental, multi-asset research runtime.

CHRONOS — Temporal Research Governance. Control what knowledge may enter the experiment: research cutoff, K / S applied to research, Temporal Air Gap, SV3 isolation, experimental world, research reopening, decision admissibility.

AEGIS — Quantitative Research Factory. Turn a temporally sealed universe into evidence and a sealed production candidate. This is v2 Phase IV — not v1 Phase II and not the AEGIS engine.

TALOS — Production Signal Runtime. Execute AEGIS-approved artifacts deterministically on current approved data. TALOS produces signals. TALOS does not research. Physical market execution is handled by the sovereign BIA engine via MCP.

Relation to THEMIS

ZEUS ENGINE depends on data contracts, not on THEMIS internals. THEMIS is not a ZEUS phase.

Financial Data Infrastructure (THEMIS or another compatible system) → Data Contract Boundary → ATENEA → MNEMOSINE → CHRONOS → AEGIS → TALOS.

THEMIS M12 delivers reproducible data evidence (seals, manifests, hashes, PIT delivery, M1/M2/M3). CHRONOS governs permitted research knowledge. They must not be duplicated.

Who it is for

Quantitative researchers, advanced algorithmic and systematic traders, quantitative developers, Python / Rust / C++ developers, ML-for-markets researchers, portfolio researchers, and teams professionalizing a research-to-production pipeline.

Prerequisites

Intermediate-to-advanced Python, applied statistics, backtesting, time series, systematic trading, basic Git, and quantitative-research literacy. Financial Data Engineering (THEMIS or equivalent) is ideal preparation. ZEUS ENGINE does not depend technologically on THEMIS.

Professional Capstone

ZEUS ENGINE — Professional Capstone. End-to-end Reference Implementation: Certified Data → ATENEA → MNEMOSINE → CHRONOS → AEGIS → TALOS. Controlled scope does not reduce architectural rigor.

Canonical syllabus: `courses/zeus_engine/SYLLABUS.md`. This page is a mount. Orientation remains outside 14/42 and is not rewritten here.

What you'll be able to do

Certify research input at ATENEA — ZEUS does not rebuild a Financial Data Center
Operationalize accepted contracts inside ZEUS at MNEMOSINE (historical / incremental / multi-asset runtime)
Govern permitted experimental knowledge at CHRONOS (cutoff, K/S, Temporal Air Gap, SV3, reopening)
Turn a sealed research world into evidence and a sealed production candidate at AEGIS
Execute approved artifacts as auditable production signals at TALOS with sealed contracts for sovereign execution handoff

Course content

Phase 1 — ATENEA 2 modules · 6 chapters

Module 1 — Financial Data Contracts 3 chapters

1.1.1.- Research Data as a Contract

1.1.2.- Financial Observation Semantics

1.1.3.- Provenance & Dataset Identity

Module 2 — Research Input Certification 3 chapters

1.2.1.- Data Quality Gates

1.2.2.- Point-in-Time Compatibility

1.2.3.- Multi-Asset Research Universe

Phase 2 — MNEMOSINE 2 modules · 6 chapters

Module 1 — Historical & Incremental Data Runtime 3 chapters

2.1.1.- Historical Data Access

2.1.2.- Incremental Data Processing

2.1.3.- Historical ↔ Production Parity

Module 2 — Multi-Asset Research Views 3 chapters

2.2.1.- Time Alignment

2.2.2.- Research Windows

2.2.3.- Data Runtime Lineage

Phase 3 — CHRONOS 2 modules · 6 chapters

Module 1 — Temporal Admissibility 3 chapters

3.1.1.- The Three Time Axes

3.1.2.- Look-Ahead Mechanisms

3.1.3.- Decision Admissibility

Module 2 — Sealed Research Environments 3 chapters

3.2.1.- Research Cutoff

3.2.2.- Dataset Sealing

3.2.3.- Experimental Worlds

Phase 4 — AEGIS 4 modules · 12 chapters

Module 1 — Hypothesis & Feature Engineering 3 chapters

4.1.1.- Research Hypothesis Engineering

4.1.2.- Feature Engineering

4.1.3.- Feature Selection

Module 2 — Statistical Validation Architecture 3 chapters

4.2.1.- Train / Validation / Test

4.2.2.- Time-Series Validation

4.2.3.- Multiple Testing & Selection Bias

Module 3 — Robustness & Failure Engineering 3 chapters

4.3.1.- Parameter Stability

4.3.2.- Market Stress Testing

4.3.3.- Failure Analysis

Module 4 — Sealed Research Artifacts 3 chapters

4.4.1.- Production Candidate

4.4.2.- Evidence Package

4.4.3.- Artifact Sealing

Phase 5 — TALOS 2 modules · 6 chapters

Module 1 — Research-to-Production Engineering 3 chapters

5.1.1.- Artifact Loading

5.1.2.- Feature Parity

5.1.3.- Deterministic Replay

Module 2 — Production Signal Runtime 3 chapters

5.2.1.- Incremental Signal Computation

5.2.2.- Signal Identity & Provenance

5.2.3.- Runtime Reliability

ZEUS ENGINE — Professional Capstone End-to-end Reference Implementation · outside 14 / 42

Certified Data → ATENEA → MNEMOSINE → CHRONOS → AEGIS → TALOS

Course content is Phase → Module → Chapter. Module numbers restart inside each phase. AEGIS has four modules; the other phases have two. Lecture bodies are not authored yet. Orientation is outside 14/42 and is not this page. ZEUS ENGINE — Professional Capstone sits outside the five phases and the 12 / 36 count.

Instructor

Elmer Niño

Founder, VTAlgo Group · Systems Engineer · MSc in Computer Science

Algorithmic trader since 2008, running trading as an enterprise. Methodology built on walk-forward analysis, genetic optimization, PCA against over-optimization, the Triple Barrier Method, and 9–12 month live validation before capital.

Programa institucional insignia

ZEUS Engine

Ingeniería de sistemas cuantitativos de investigación a producción

Arquitectura profesional para convertir datos financieros en investigación validada, señales reproducibles y ejecución algorítmica gobernada

$2,000

5 phases · 12 modules · 36 chapters · capstoneATENEA → MNEMOSINE → CHRONOS → AEGIS → TALOSUn curso profesionalPor invitación

Course roadmap · 5 phases

Fase I

ATENEA

Quantitative Data Foundation

Fase II

MNEMOSINE

Quantitative Data Runtime

Fase III

CHRONOS

Temporal Research Governance

Fase IV

AEGIS

Quantitative Research Factory

Fase V

TALOS

Production Signal Runtime

Misión y visión

Misión

Enseñar una cadena verificable que convierte datos financieros en evidencia cuantitativa, artefactos de investigación, señales productivas y ejecución controlada — una estrategia está lista para producción cuando esa cadena existe, no cuando un backtest se ve bien.

Visión

Profesionales capaces de diseñar un sistema gobernado de investigación a producción: input certificado, runtime de datos de ZEUS, gobernanza temporal de research, una fábrica de research sellada, un runtime de señal productiva y ejecución controlada.

Descripción

ZEUS Engine es Quantitative Research-to-Production Systems Engineering. Un curso profesional. Nombre público ZEUS Engine. Lista $3,000.

Una estrategia no está lista para producción porque tenga un buen backtest. Está lista cuando existe una cadena verificable desde el dato conocido hasta la señal y desde la señal hasta la ejecución.

Cadena oficial de fases

ATENEA → MNEMOSINE → CHRONOS → AEGIS → TALOS.

Estos nombres son las fases internas de este curso. No son productos independientes.

DATA to EXECUTION

DATA → KNOWLEDGE → HYPOTHESIS → VALIDATION → EVIDENCE → ARTIFACT → SIGNAL → ORDER → EXECUTION.

Five phases

ATENEA — Quantitative Data Foundation. Aceptación / certificación del input de ZEUS. ATENEA no reconstruye un Financial Data Center.

MNEMOSINE — Quantitative Data Runtime. Operationalize ATENEA-accepted contracts inside ZEUS: historical, incremental, multi-asset research runtime.

CHRONOS — Temporal Research Governance. Controlar qué conocimiento puede entrar al experimento: research cutoff, K / S aplicados al research, Temporal Air Gap, aislamiento SV3, mundo experimental, reapertura de research, admisibilidad de decisión.

AEGIS — Quantitative Research Factory. Convertir un universo temporalmente sellado en evidencia y un candidato productivo sellado. Esta es la Fase IV v2 — no la Fase II v1 ni el motor AEGIS.

Relation to THEMIS

ZEUS ENGINE depends on data contracts, not on THEMIS internals. THEMIS is not a ZEUS phase.

Financial Data Infrastructure (THEMIS or another compatible system) → Data Contract Boundary → ATENEA → MNEMOSINE → CHRONOS → AEGIS → TALOS.

THEMIS M12 delivers reproducible data evidence (seals, manifests, hashes, PIT delivery, M1/M2/M3). CHRONOS governs permitted research knowledge. They must not be duplicated.

Who it is for

Prerequisites

Professional Capstone

Canonical syllabus: `courses/zeus_engine/SYLLABUS.md`. This page is a mount. Orientation remains outside 14/42 and is not rewritten here.

Qué vas a ser capaz de hacer

Certificar el input de research en ATENEA — ZEUS no reconstruye un Financial Data Center
Operationalize accepted contracts inside ZEUS at MNEMOSINE (historical / incremental / multi-asset runtime)
Gobernar el conocimiento experimental permitido en CHRONOS (cutoff, K/S, Temporal Air Gap, SV3, reapertura)
Convertir un mundo de research sellado en evidencia y un candidato productivo sellado en AEGIS
Execute approved artifacts as auditable production signals at TALOS with sealed contracts for sovereign execution handoff

Contenido del curso

Fase 1 — ATENEA 2 módulos · 6 capítulos

Módulo 1 — Contratos de datos financieros 3 capítulos

1.1.1.- El dato de investigación como contrato

1.1.2.- Semántica de observación financiera

1.1.3.- Provenance e identidad de dataset

Módulo 2 — Certificación del input de research 3 capítulos

1.2.1.- Compuertas de calidad de datos

1.2.2.- Compatibilidad point-in-time

1.2.3.- Universo de research multi-activo

Phase 2 — MNEMOSINE 2 módulos · 6 capítulos

Módulo 1 — Runtime de datos histórico e incremental 3 capítulos

2.1.1.- Acceso a datos históricos

2.1.2.- Procesamiento incremental de datos

2.1.3.- Paridad histórica ↔ producción

Módulo 2 — Vistas de research multi-activo 3 capítulos

2.2.1.- Alineación temporal

2.2.2.- Ventanas de research

2.2.3.- Lineage del runtime de datos

Fase 3 — CHRONOS 2 módulos · 6 capítulos

Módulo 1 — Admisibilidad temporal 3 capítulos

3.1.1.- Los tres ejes de tiempo

3.1.2.- Mecanismos de look-ahead

3.1.3.- Admisibilidad de la decisión

Módulo 2 — Entornos de research sellados 3 capítulos

3.2.1.- Research cutoff

3.2.2.- Sellado de dataset

3.2.3.- Mundos experimentales

Fase 4 — AEGIS 4 módulos · 12 capítulos

Módulo 1 — Ingeniería de hipótesis y features 3 capítulos

4.1.1.- Ingeniería de la hipótesis de research

4.1.2.- Ingeniería de features

4.1.3.- Selección de features

Módulo 2 — Arquitectura de validación estadística 3 capítulos

4.2.1.- Train / Validation / Test

4.2.2.- Validación de series de tiempo

4.2.3.- Multiple testing y sesgo de selección

Módulo 3 — Robustez e ingeniería de fallos 3 capítulos

4.3.1.- Estabilidad de parámetros

4.3.2.- Stress testing de mercado

4.3.3.- Análisis de fallos

Módulo 4 — Artefactos de research sellados 3 capítulos

4.4.1.- Candidato productivo

4.4.2.- Paquete de evidencia

4.4.3.- Sellado del artefacto

Fase 5 — TALOS 2 módulos · 6 capítulos

Módulo 1 — Ingeniería research-to-production 3 capítulos

5.1.1.- Carga del artefacto

5.1.2.- Paridad de features

5.1.3.- Replay determinista

Módulo 2 — Runtime de señal productiva 3 capítulos

5.2.1.- Cómputo incremental de señal

5.2.2.- Identidad y provenance de la señal

5.2.3.- Confiabilidad del runtime

ZEUS ENGINE — Professional Capstone End-to-end Reference Implementation · outside 14 / 42

Certified Data → ATENEA → MNEMOSINE → CHRONOS → AEGIS → TALOS

Instructor

Elmer Niño

Fundador, VTAlgo Group · Ingeniero de sistemas · MSc en Computer Science

Trader algorítmico desde 2008, operando el trading como empresa. Metodología construida sobre walk-forward analysis, optimización genética, PCA contra la sobreoptimización, el Triple Barrier Method y validación live de 9–12 meses antes de capital.