Quantitative Engineering · Institutional B2B

QuantEternam Your alpha. Our engineering.

You have the hypothesis. We turn it into a fully automated, rigorously validated, production-ready system — no shortcuts on methodology.

18+ years of data
1000+ Monte Carlo runs
3 anti-overfit protocols
100% automated

About

We don't sell strategies. We build yours.

QuantEternam is a collective of quantitative engineers specializing in bespoke trading strategy automation. Investment funds, prop firms, systematic traders — you bring the market hypothesis, we implement, test and deploy it with institutional engineering precision.

Our validation protocols (CPCV, WFO, Monte Carlo) ensure that measured performance is real — not a historical artifact.

What we don't do

  • We don't propose pre-built strategies
  • We don't manage funds or capital
  • We don't sell signals or track records
Investment funds Prop firms Systematic traders
Trading infrastructure
18+years of data
5+asset classes
13+timeframes

How it works

From your hypothesis to a live system

01

You describe your strategy

Market hypothesis, asset class, signal logic, timeframe. No code required — you work in your domain, we work in ours.

02

We backtest & validate

Rigorous implementation, bias-free data, WFO + CPCV + Monte Carlo. We challenge your hypothesis before you spend a cent on execution.

03

Deployed, automated, monitored

Bot delivered on IB / Zorro / FIX API. Auto-reconnect, real-time alerts, full reporting. Zero manual intervention required.

Services

What we build for you

01

Quantitative Research & Backtesting

Implementation of your strategies on historical or live data (Interactive Brokers, Zorro, proprietary APIs). Multi-asset (futures, equities, forex, crypto), multi-timeframe. Realistic modeling of execution costs, market-impact-aware slippage, and contract rolls — survivorship-bias free, no look-ahead.

PythonInteractive BrokersZorroMulti-assetBias-free
02

Optimization & Anti-Overfit Protocols

Optimization via grid search, Bayesian, or genetic algorithms. Triple validation filter: Walk-Forward Analysis, CPCV, and Monte Carlo. Every result is expressed in risk-adjusted metrics (Sharpe, Calmar, Ulcer Index) — not just raw performance.

WFOCPCVMonte CarloSharpeCalmar
03

Stress Testing & Robustness Analysis

Parameter sensitivity testing, contextual drawdown analysis (2008, 2020, flash crashes), extreme regime simulations. We verify robustness under ±15% parameter drift before any deployment.

SensitivityMax DrawdownRegime Analysis2008 · 2020
05

Reporting & Analytics Tools

Automated reports in multi-sheet Excel or PDF: equity curves, rolling Sharpe, max drawdown, correlation matrices, heatmaps. Risk-adjusted metrics readable by your investment committees.

Sharpe · Calmar · UlcerPlotlyExcelPDF
06

Data & Execution Infrastructure

Multi-source connectors (Interactive Brokers, Zorro, REST APIs, local data), real-time pipelines, ratio-adjusted continuous contracts. Integration with QuantConnect/LEAN, Zipline, and custom architectures.

IB TWS APIZorroLEANReal-time

Workflow

From hypothesis to deployment

01 Data Ingestion IB · Zorro · APIs · Local
02 Feature Engineering Indicators · ML · Transforms
03 Strategy Implementation Your hypothesis → code
04 Backtesting Bias-free · Multi-TF
05 Anti-Overfit & HPO CPCV · WFO · Monte Carlo
06 Risk-Adjusted Reporting Sharpe · Calmar · Drawdown
07 Live Deployment Paper → Production
08 Monitoring Real-time · Alerts

Technologies

Tech Stack

Languages

PythonC++SQL

Execution Platforms

Interactive BrokersZorroQuantConnect / LEANFIX API

Data

Real-time APIsMulti-decade historicalRatio-adjusted continuous

ML / AI

Scikit-learnXGBoostNeural NetworksPCAQuantile Transforms

Validation

Monte CarloWalk-ForwardCPCVSensitivity Testing

Deployment

Packaged ExecutablesGUI AppsThread-safeAuto-reconnect

Reporting

MatplotlibPlotlyExcel multi-sheetsPDF autoInteractive dashboards

Case Studies

Anonymized projects

Investment Fund · Paris Sharpe 1.4 · DD -11%

Multi-Futures Trend Following

Implementation of a trend-following strategy across 12 futures (indices, rates, commodities) described by their research team. 18-year validation, 48 WFO windows, CPCV passed. Deployed on IB with automated weekly reporting.

FuturesWFO × 48CPCV ✓IB
Prop Firm · 8 years active Sharpe 1.8 · DD -8%

Intraday Mean-Reversion Bot

Automation of an intraday mean-reversion strategy on US equities they were trading manually. ML signal selection, full GUI, FIX API connectivity, real-time alerts and monitoring.

EquitiesMLFIX APIAutomated
Systematic Trader · Multi-market CPCV p<0.01 · 1000 MC

Validation & Reporting Framework

Full backtesting framework on Forex and Crypto to validate several market hypotheses. Triple anti-overfit protocol, 1000+ Monte Carlo, automatic risk-adjusted PDF reporting.

ForexCryptoMonte Carlo ×1000PDF Reports

“Their CPCV implementation matched our internal methodology exactly. That's rare in an external partner.”

— Head of Quant Research, Paris-based fund

“We'd been trading this strategy manually for 3 years. In 6 weeks it was running automatically on IB with reporting our committee can actually read.”

— Director, prop firm · 8 years active
Infrastructure

Secure infrastructure

Deployed to institutional standards

Thread-safe architecture, auto-reconnect, real-time monitoring — every delivered system is production-ready from day one. Strict NDA on all proprietary logic.

Strict NDA · Secure infrastructure · Institutional-grade requirements — All proprietary logic is protected. We don't propose strategies — we implement yours.

Contact

Let's talk about your strategy

You have a market hypothesis to automate, a bot to harden, or a validation framework to build? Free technical discussion — 30 minutes.

Message sent — we'll reply within 24h.