About Algotude

Algorithms built by traders, for traders

We combine quantitative research, machine learning, and decades of market experience to surface high-conviction signals — so you can trade with an edge, not a guess.

4.2B+
Data points processed daily
71%
Average signal win rate
12K+
Active traders
2019
Year founded

Our mission

Retail traders have always been at a disadvantage. Institutional desks run proprietary quant models, hire PhDs, and process data feeds that cost millions a year. Meanwhile, individual investors are left with lagging indicators and gut instinct.

Algotude was built to close that gap. We believe every serious trader deserves access to the same caliber of algorithmic analysis that hedge funds use — without the overhead, the jargon, or the six-figure price tag.

Our platform runs continuously, scanning thousands of instruments across equities, crypto, and forex. Every signal is backtested, confidence-scored, and delivered with full transparency on the methodology behind it.

How our algorithms work

Every signal goes through a rigorous multi-stage pipeline before it reaches you.

01

Data ingestion

We ingest tick-level price data, order book depth, on-chain metrics, and macro indicators from over 40 data providers — updated in real time.

02

Feature engineering

Raw data is transformed into 200+ engineered features: momentum scores, volatility regimes, volume anomalies, cross-asset correlations, and sentiment signals.

03

Model ensemble

An ensemble of gradient-boosted trees, LSTM networks, and mean-reversion models vote on each signal. Disagreement between models reduces confidence scores automatically.

04

Walk-forward validation

Every model is validated on out-of-sample data using rolling walk-forward testing — never in-sample curve fitting. We publish our validation methodology openly.

05

Risk filtering

Signals are filtered through a risk engine that checks position sizing, correlation to existing signals, and current market regime before publication.

06

Continuous retraining

Models retrain weekly on fresh data. Signals that degrade in live performance are automatically retired and replaced with improved versions.

What we stand for

Transparency first

We publish our backtesting methodology, confidence scoring logic, and model performance history. No black boxes.

Edge over noise

We only surface signals with statistically significant edge. We'd rather show you fewer, better signals than flood you with noise.

Continuous improvement

Markets evolve. Our models retrain weekly and we retire underperforming signals without hesitation.

Trader-first design

Every feature is designed with active traders in mind — fast, dense, and built for decision-making under pressure.

The team

MC
Marcus Chen
Co-founder & CEO

Former quant at Citadel and Two Sigma. 14 years building systematic trading strategies across equities and derivatives.

PN
Priya Nair
Co-founder & CTO

ML research lead at Google Brain before founding Algotude. Specializes in time-series forecasting and reinforcement learning for finance.

JO
James Okafor
Head of Research

PhD in Financial Mathematics from MIT. Previously ran systematic macro strategies at a $4B AUM fund.

SR
Sofia Reyes
Head of Product

10 years in fintech product at Robinhood and Interactive Brokers. Obsessed with making complex data legible to every trader.

Ready to trade with an edge?

Join 12,000+ traders using Algotude to find high-conviction setups.