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Global Equities
AI-driven stock selection across US, European, and Asian markets. Our agents analyze fundamentals, technicals, order flow, and alternative data to generate long/short equity signals.
Launching 2026 — Now Accepting Early Access
The Future of Investing
is Autonomous.
House of Quant is an agentic hedge fund where AI powered trading meets autonomous investing. Our AI agents research, execute, and manage risk across global markets — 24/7, without human bias.
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AI Agents Deployed
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Market Monitoring
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Avg. Execution Latency
About the Fund
AI-Powered Investing That Never Sleeps
House of Quant is an agentic hedge fund that replaces traditional portfolio managers with a fleet of specialized AI trading agents. Each agent is purpose-built for a specific market function — from AI-driven alpha discovery to autonomous risk hedging — creating an AI powered trading engine that operates continuously across all global markets.
Multi-Strategy Architecture
Diversified across uncorrelated alpha sources — statistical arbitrage, momentum, mean reversion, and ML-driven signals — ensuring resilient returns across market regimes.
AI-Native from Day One
Not a traditional fund retrofitted with AI. Every process — research, signal generation, execution, risk management — is built around autonomous agent orchestration from the ground up.
Institutional-Grade Risk
Real-time portfolio stress testing, dynamic hedging, and drawdown controls powered by reinforcement learning agents that adapt to evolving market conditions.
Investment Verticals
Six Markets. One Autonomous Engine.
Our AI agents operate across a diversified set of global markets, identifying alpha opportunities that traditional managers miss.
02
Fixed Income
Systematic bond trading across sovereign and corporate credit. ML models forecast yield curves, credit spreads, and central bank policy to capture relative value.
03
Digital Assets
24/7 crypto trading across centralized and decentralized venues. Our agents exploit cross-exchange arbitrage, DeFi yield optimization, and on-chain sentiment signals.
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Commodities
Systematic trading in energy, metals, and agriculture futures. AI agents incorporate satellite imagery, weather data, and supply chain intelligence for alpha generation.
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Foreign Exchange
High-frequency and macro FX strategies across G10 and EM currencies. NLP agents parse central bank communications and geopolitical signals for directional and carry trades.
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Alternatives
Volatility, structured products, and cross-asset relative value. AI agents dynamically construct hedged portfolios targeting convexity and uncorrelated returns.
AI Trading Strategies
Systematic Alpha, Engineered by Agentic AI
Each AI powered trading strategy is driven by specialized autonomous agents that continuously learn, adapt, and optimize in response to changing market dynamics — delivering AI-driven investing at institutional scale.
Statistical Arbitrage
Exploiting mean-reverting relationships between co-integrated securities. Our agents monitor thousands of pairs in real-time, entering when statistical z-scores breach calibrated thresholds.
Trend Following / Momentum
Adaptive momentum strategies across all asset classes. AI agents dynamically adjust lookback windows, position sizing, and breakout thresholds based on current volatility regimes.
Mean Reversion
Capturing price dislocations across equities, FX, and fixed income. Bayesian models estimate fair value distributions while agents execute convergence trades with dynamic stop-losses.
Machine Learning Alpha
Deep learning models trained on alternative data — satellite imagery, web traffic, patent filings, earnings call transcripts — to generate non-linear predictive signals invisible to traditional quant models.
NLP Sentiment Analysis
Large language models processing real-time news feeds, social media, SEC filings, and earnings transcripts. Sentiment scores are integrated into multi-factor models for predictive edge.
Risk Parity & Hedging
Dynamic portfolio construction that equalizes risk contribution across assets. Reinforcement learning agents continuously re-balance and hedge tail risk using options and futures overlays.
Agentic AI Architecture
Autonomous AI Trading Agents
Traditional funds rely on human portfolio managers. As an agentic hedge fund, House of Quant deploys a coordinated fleet of autonomous AI agents — each an expert in its domain — orchestrated by a meta-agent that allocates capital dynamically for AI powered investing at scale.
Research Agents
Continuously scan markets, news, filings, and alternative data sources. Identify potential alpha signals and anomalies across 50,000+ instruments.
Signal Agents
Transform raw data into actionable trading signals using ML models. Validate signal quality through walk-forward testing and regime detection.
Execution Agents
Optimally route and execute orders to minimize slippage and market impact. Smart order routing across 40+ venues with sub-50ms latency.
Risk Agents
Monitor portfolio risk in real-time. Enforce position limits, correlation constraints, and dynamic drawdown controls. Auto-hedge tail risk events.
Meta-Agent
The Meta-Agent: Orchestrating Intelligence
Sitting above the specialist agents, the Meta-Agent dynamically allocates capital, resolves conflicting signals, and optimizes the overall portfolio. It uses reinforcement learning to continuously improve allocation decisions based on strategy performance, market regime, and risk budget — ensuring the fund adapts faster than any human PM could.
Dynamic capital allocation across strategies
Real-time regime detection and adaptation
Conflict resolution between competing signals
Continuous self-improvement via RL feedback loops
Backtested Performance
Engineered for Superior Risk-Adjusted Returns
Our strategies have been rigorously backtested across multiple market regimes. Past simulated performance is not indicative of future results.
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Win Rate
Disclaimer: All performance figures are based on backtested simulations and do not represent actual trading results. Past performance, whether actual or simulated, is not necessarily indicative of future results. Investing involves risk, including the possible loss of principal.
The Team
Built by Quants. Powered by AI.
Our founding team combines decades of experience from leading quant desks, AI research labs, and top-tier technology companies.
Quantitative Research
PhDs in mathematics, statistics, and financial engineering from MIT, Stanford, and Cambridge. Former quant researchers at Citadel, Two Sigma, and DE Shaw.
AI & Engineering
Machine learning engineers and infrastructure architects from Google DeepMind, OpenAI, and Meta AI. Experts in LLMs, reinforcement learning, and low-latency systems.
Finance & Operations
Seasoned fund managers and compliance experts with experience managing billions in AUM. Deep expertise in fund structuring, regulation, and institutional investor relations.
Early Access
Be Among the First Investors
House of Quant is launching soon. Join our exclusive waitlist to get early access, priority allocation, and founding investor benefits.
Get in touch:
team@houseofquant.com