Hadron Capital is an end-to-end systematic portfolio management platform that fuses 18+ quantitative signals, a gradient-boosted machine learning (ML) alpha model, and institutional-grade multi-constraint optimisation — delivering reproducible, out-of-sample-validated strategies from signal to executable trade list.
The Platform
From raw price data to executable trade orders — the full systematic investment process in one platform, built to institutional standard without institutional overhead.
Momentum, value, quality, sentiment, technical, and macro signals computed with vectorised, look-ahead-bias-free pipelines. IC attribution weights every signal by realised predictive power at each rebalance.
Gradient boosting model with hyperparameter tuning trained on 60+ cross-sectional features with purged walk-forward CV. Scores integrate into the composite via dynamic IR weighting.
Min variance, Max Sharpe, Risk Parity, Black-Litterman, Mean-CVaR, Max Return, and Transaction-Cost-Aware optimisation — all under tri-dimensional constraints (sector, region, asset class).
VaR / CVaR, Kelly criterion, regime-conditional Sharpe, stress testing, factor risk decomposition, liquidity scoring, and TC sensitivity — six analytics tabs on every backtest.
Full Brinson–Hood–Beebower sector attribution with selection, allocation, and interaction effects at every rebalance. Audit trail logs every pre- and post-trade snapshot.
From final portfolio weights to share-level executable orders in one step. Handles new portfolios and rebalances, incorporates live prices, commissions, and slippage.
The Hadron Principle
"In physics, we look for the fundamental particles of the universe. In finance, we look for the fundamental factors of wealth."
Every decision is traceable. Every result is reproducible. Every strategy is stress-tested before it touches a portfolio.
The Founder
Quantitative Equity Researcher · Quantitative Risk Analytics Professional · Physicist
Kingsley Emelideme is a quantitative finance professional with a rare dual foundation in experimental particle physics and systematic asset management. Trained as a physicist at the University of Alberta, he contributed to the ATLAS experiment at CERN's Large Hadron Collider before pivoting to quantitative equity research — bringing the rigour, precision, and statistical toolkit of high-energy physics directly to portfolio construction.
His work sits at the intersection of factor-based investing and institutional-grade risk analytics. He designs and back-tests multi-signal systematic strategies, builds constrained optimisation frameworks, and develops production-ready tooling that bridges the gap between academic factor research and executable trade instructions.
Embedded in the ATLAS collaboration at CERN's Large Hadron Collider — the instrument that discovered the Higgs boson. Dissertation focused on trigger efficiency studies for missing transverse energy (MET), a critical observable for detecting new physics beyond the Standard Model.
The analysis required modelling Standard Model backgrounds — QCD, tt̄, and W/Z+jets — to isolate genuine invisible-momentum signatures. The same discipline of separating signal from noise maps directly onto extracting persistent alpha from financial time series.
Hadron Capital is named after the composite particles studied at the LHC — a deliberate nod to the idea that the most interesting phenomena emerge from collision: the intersection of data, models, and disciplined execution.
The platform is built around a single principle: trust nothing you cannot verify. Data is cross-checked across multiple sources before a single position is sized. Signals earn their weight through demonstrated predictive power, not assumption. Every portfolio decision is traceable back to a quantifiable reason — because in physics, as in finance, an untested assumption is not a model; it is a liability.
Languages
Quant Finance
Data & ML
Physics
Mortgage ALM & Strategy Framework
Asset-Liability Management · Stochastic Simulation · Hedging Optimization
When the terminal closes, a different kind of exploration begins. Kingsley is drawn to the complexity of the natural world — navigating mountain trails, covering long distances by bike, and chasing the kind of stillness only the outdoors can offer. He is equally fascinated by robotics and autonomous systems, finding the same elegance in a precisely programmed machine as in a well-optimised portfolio. Throw in a chess board and a passport, and you have a man who believes that the best thinking happens far from a desk. For him, curiosity is not a hobby — it is an operating system.
Get in Touch
Whether you want a walkthrough of the platform, need help with your strategy, or have questions about institutional access — we're happy to help.
Ready to explore?
Hadron Capital IPMS — systematic equities, institutional quality, fully transparent methodology.
Hadron Capital © 2026 · Created & designed by Kingsley Emelideme