That model still exists. But it’s aging out, and there’s a reason.
Human intuition, even backed by genuine expertise, breaks down under pressure. Not because discretionary managers are unintelligent—most are exceptionally sharp. The problem is structural. Our brains weren’t built for capital markets.
When a portfolio drops 15% in a week, two things happen simultaneously. Fear drives toward immediate loss avoidance—sell everything, move to cash, stop the pain. And the data consistently shows that panic selling clusters at bottoms. March 2020. Late 2022. The pattern repeats because the wiring doesn’t change.
On the flip side, after a strong rally, the brain overweights recent performance and extrapolates. Conviction builds at exactly the wrong time. Late 2021 was a masterclass in this—experienced investors loading up on risk right at the inflection point, because six months of momentum felt like a permanent condition.
Then layer in confirmation bias (you seek out research that supports your existing thesis), anchoring (you bought at $50, so $35 feels “cheap” regardless of fundamentals), and loss aversion (you hold losers too long hoping to get even). These aren’t character flaws. They’re features of human cognition. Knowing about them doesn’t make you immune to them—Kahneman’s own research confirmed as much.
A systematic strategy replaces real-time judgment with pre-tested rules. You’re not removing the human from the process—you’re relocating them. The intelligence moves from the trading desk to the design room.
The difference shows up in three places.
Risk limits that don’t negotiate. A well-built systematic portfolio defines explicit constraints: maximum single-position risk, total exposure caps, volatility-scaled sizing. When the 2018 EM crisis hit, systematic managers with these rules had already reduced exposure before the panic because the rules forced it. No committee meeting required. No debate about whether “this time is different.”
Diversification that actually works in a crisis. Most portfolios diversify across assets—60/40, spread across names and sectors. The problem is that during stress, correlations spike and everything falls together. Systematic diversification operates differently. Instead of spreading across assets, it spreads across independent drivers of return: trend-following, mean reversion, statistical signals. These strategies profit from different market dynamics, so when one struggles, others pick up the slack.
Execution without hesitation. When the system signals a trade, it executes. No second-guessing, no “maybe I should wait a day,” no rationalizing why the rules don’t apply this week. This sounds trivial. In practice, it’s where most discretionary managers give back their edge.
In calm markets, the gap between a competent discretionary manager and a systematic program might be reasonably low. Both capture trends, both avoid obvious mistakes.
When volatility spikes—when drawdown risk is real and emotions run highest—the gap widens dramatically. The discretionary manager fights their own psychology. The systematic manager follows the rules. The rules exist precisely because they were tested against historical volatility. They’ve already been through the stress, at least empirically.
The mechanism is simple: when volatility increases, systematic risk limits scale positions down. Capital gets preserved. When the bounce comes, there’s dry powder to redeploy at better prices. It’s not brilliant; it’s disciplined. And discipline compounds.
The most dangerous framing in this debate is that systematic investing removes humans. It doesn’t.
Humans design the hypotheses—which economic relationships should be tradeable, which factors are structural versus temporary. Humans monitor for regime change, reviewing whether historical signals remain relevant. AI and machine-learning models serve as signal generators within the framework, identifying patterns and informing decisions—but always operating within risk guardrails that humans establish.
The algorithm isn’t making decisions. It’s enforcing the discipline to execute decisions that human intelligence already made through rigorous testing.
At Blackworks Capital, our conviction lies not in predicting markets, but in the disciplined execution of objective, rules-based logic. The BWC Founders Fund runs multiple uncorrelated strategies through a multi-factor voting framework—where independent market forces each generate signals that determine portfolio exposure. No single factor dominates. The framework demands consensus before capital moves.
Every signal undergoes rigorous validation across multiple market cycles and regimes before deployment. We reject far more than we accept. The strategies that survive are robust to real conditions, not just favorable backtests.
Our founder, Rogan McGillis, maintains significant personal capital alongside investors. We eat our own cooking.
These results validate the core tenets of our investment philosophy: systematic discipline, multi-factor diversification, and dynamic risk management. For investors managing serious capital, the question isn’t whether systematic investing works—it’s whether your current approach enforces the discipline that volatile markets demand.
Ready to explore how systematic discipline could strengthen your portfolio? Get in touch to start the conversation.