One model for each stock in your portfolio.

CNW trains a dedicated AI model for each equity and delivers the signal without changing how you operate. More alpha. No operational cost.

CNW Research — quantitative architecture
Comparison between an unoptimized NASDAQ-6 portfolio and the same portfolio managed by the CNW model. Measuring whether the signal improves return, Sharpe and drawdown control vs. holding the assets unoptimized.
+28.4%
Optimized return
0.86
Sharpe ratio
−30.1%
Max. drawdown
+13.3pp
Outperformance

NASDAQ-6 active portfolio.

NASDAQ-6 · Igual peso 16.7% · r_atr_ha_guard · 6/6 modelos activos · May 2024 – May 2026

0.862
Sharpe ratio
+28.44%
Total return
View full analysis →
TSLA
16.7%
r_atr_ha_guard · agg.
AAPL
16.7%
r_atr_ha_guard · agg.
VSA
16.7%
r_atr_ha_guard · cons.
MCRF
16.7%
r_atr_ha_guard · agg.
ADBE
16.7%
r_atr_ha_guard · agg.
NVDA
16.7%
r_atr_ha_guard · agg.
Equity Curve · NASDAQ-6 · May 2024 – May 2026 Optimized Buy & Hold
+28.4% +15.1%
StrategyTotal returnVolatilitySharpeMax. drawdownCalmar
Optimized+28.44%33.00%0.862−30.09%0.945
Buy & Hold+15.10%37.62%0.401−38.62%0.391
Difference+13.34pp−4.62pp+0.461+8.53pp+0.554

Integrates into your process. Doesn't replace it.

CNW acts as a signal layer on top of your existing process. You receive a daily signal via API for each position, with a confidence score and suggested sizing. Your execution doesn't change.

01

You define your universe

You provide your equity universe. CNW maps each position to a dedicated model instance. The S&P 500 set is available immediately.

02

We train one model per asset

Each security has its own model trained exclusively on its own historical data: price microstructure, fundamentals, macro context and derived signals.

03

You receive the daily signal

Post-market delivery via REST API. Directional (long / flat / short) with confidence score and suggested sizing. 67% of signals are automatically filtered before reaching you.

Min. AUM
Flexible
Onboarding
2–4 weeks
Delivery
REST API
Filtered signals
67%

Validated out-of-sample results.

Three independent lines of research. Walk-forward throughout: no look-ahead bias.

View all papers →
01
NASDAQ-6 · Full coverage · r_atr_ha_guard
NASDAQ-6 Optimized
6/6 assets · +13.3pp outperformance · May 2024–May 2026
0.86
Sharpe ratio
+28.4%
Total return
View report →
02
NASDAQ-10 MVP v1.2 · Operational
NASDAQ-10 MVP
6/10 assets · +314.2% return · May 2024–May 2026
4.28
Sharpe ratio
+314%
Total return
View report →
03
NASDAQ-20 Baseline · Factor Signal
NASDAQ-20 Factor
9.3× terminal · +5.2% annual excess · 6 years
0.47
Information Ratio
9.3×
Terminal multiple
View report →

A global model learns what is true on average.

What is true on average is precisely wrong for each individual stock. CNW solves this with infrastructure that until recently didn't exist.

Idiosyncratic patterns
Each security has its own persistent patterns that cross-sectional models systematically ignore. We capture what others miss.
Scale infrastructure
Training 500+ models in parallel with daily retraining requires dedicated GPU architecture. We built it from scratch.
Per-asset confidence filter
The confidence threshold is calibrated per asset, not globally. Fewer signals, higher quality. 67% are filtered before reaching you.
No survivorship bias
Point-in-time constituent lists for the S&P 500. Backtests reflect universes that were actually tradeable at each historical moment.
CNW

The signal layer added 2.41× Sharpe while reducing maximum drawdown by nearly a third — without a single change in how we managed the book.

Backtesting validation · CNW Research, 2025 · Madrid

Signal before it reaches the price.

We aggregate and normalize 28 alternative data sources in real time — options flow, institutional sentiment, market microstructure and macro regime — to extract signal before it is reflected in the price.

View Alt Data product →
28 data sources
Microstructure, macro regime, corporate events, institutional flow and sentiment — five categories that traditional models ignore.
Real-time processing
Latency under 200ms from source to normalized signal. Data ready to ingest directly into your infrastructure.
SaaS Terminal + REST API
Access via web terminal with interactive dashboards or direct API integration with token authentication and configurable rate limiting.
For quants and institutions
Designed for hedge funds, prop desks and family offices that need institutional-quality signal without building their own infrastructure.

Frequently asked questions.

Everything you need to know before requesting access.

What type of signal does CNW deliver?+

A daily signal per asset: directional (long / flat / short) with a 0–1 confidence score and suggested sizing as a percentage of the book. Delivered post-market via REST API, ready before the next day's open.

Does it change how we execute trades?+

No. CNW acts as a signal layer on top of your existing process. Your OMS, broker and execution don't change. You simply receive an additional signal that you can incorporate with whatever weight you decide.

How long does onboarding take?+

Between 2 and 4 weeks from signing. Includes asset universe setup, API integration testing and a paper trading validation period before go-live.

Is there a minimum AUM to access?+

We don't set a fixed AUM threshold. Access is evaluated case by case: hedge funds, prop desks, family offices and managers with equity universes are the typical profiles.

How is look-ahead bias avoided in backtests?+

All published results use strict walk-forward: the model only sees data prior to the prediction point at each moment. We use point-in-time constituent lists for the S&P 500, eliminating survivorship bias.

What asset universes are available?+

The full S&P 500 set is available immediately. We also cover NASDAQ-100, Russell 1000 and custom universes from 50 positions. Models are trained specifically for each asset in the requested universe.

How do we get started?+

Fill in the access request form. We respond within 48h with an initial proposal and a diagnostic call to assess the fit with your investment process.

Start operating with statistical alpha.