Performance Snapshot
Our probability-ranked, risk-adjusted top-10 portfolio targets:
Context matters. How we compare to common benchmarks:
Our approach targets higher expected return with comparable or lower volatility, and a materially higher probability of positive outcomes over a 1-year horizon.
Risk Framework
Institutional allocators deserve explicit risk language. Here is ours:
- •Downside expectations: We model full return distributions. Our 88% P(positive 1Y) implies a 12% probability of negative outcome — we do not hide tail risk.
- •Stress scenario behavior: Monte Carlo simulations (15,000+ paths) incorporate regime-aware volatility. We test under elevated vol and correlation regimes, not just calm markets.
- •Drawdown philosophy: Equal weighting reduces concentration risk. We do not use structural leverage. Drawdowns will occur; our process is designed to recover through disciplined rebalancing, not panic.
We do not claim certainty. We model distributions. We rank risk-adjusted opportunity. We equal-weight to survive reality.
Why This Strategy Matters
Most portfolios fail not because of a lack of intelligence — but because of overfitting, narrative-driven concentration, estimation error disguised as conviction, and emotional decision-making.
Markets are increasingly driven by narrative extremes, passive flows, short-termism, and crowded factor swings. Systematic, probability-weighted discipline has never been more important.
The opportunity lies in ranking reality — not forecasting headlines.
How We Do It
Every stock in our universe is modeled through multi-factor scoring, earnings growth and revision analysis, valuation discipline, quality metrics, momentum dynamics, and Monte Carlo simulations (15,000+ paths per portfolio).
We rank. We equal-weight. We validate under uncertainty.
Research supports this approach. Equal weighting reduces estimation error and often outperforms concentrated optimization under real-world noise (DeMiguel, Garlappi & Uppal, 2009).
Our Background
Investors invest in people first, process second. Merkapital Research was built by practitioners who believe capital allocation should be evidence-based, not narrative-driven.
Our domain expertise spans quantitative research, portfolio construction, and institutional risk management. We have built and operated systematic strategies in both research and live environments. We execute because we have done the work — not because we claim to have the answer.
We are forming the Merkapital Fund to deploy capital systematically, preserve risk-adjusted integrity, scale intelligently, and attract exceptional quantitative and capital allocation talent.
Capital Partnership
We are seeking seed capital partners, strategic allocators, and long-term aligned investors.
Ideal partners understand: compounding beats speculation, process beats personality, and risk-adjusted returns matter more than raw returns.
This is not high-frequency. This is not day trading. This is long-horizon, simulation-validated capital allocation.
Alignment
Our capital is invested alongside our partners. We succeed only if our investors succeed. We grow only if our process remains disciplined.
Talent & Recruitment
We are equally seeking exceptional individuals who believe: Probability > Prediction, Discipline > Ego, Structure > Narrative.
Specifically: quantitative researchers, software engineers (simulation infrastructure, portfolio automation), risk modelers, and institutional distribution strategists.
If you are building in public markets and believe humility toward uncertainty is an edge — we want to speak with you.
Next Steps
Merkapital is not a marketing story. It is a capital framework. And we are just getting started.