Systematic Insights

The 'Black Box' Challenge: Demystifying Systematic Transparency

The ‘Black Box’ Challenge: Demystifying Systematic Transparency

The skepticism is understandable. You hand capital to a systematic fund and get a monthly report with performance numbers and strategy exposures. Meanwhile, the discretionary manager sends a detailed letter explaining their thesis, what they see in the companies they own, and why they’re positioned the way they are.

A Violent Rotation In A Quiet Market

The index looks calm. Underneath it, sector correlation just hit its lowest level since September 2000. We ran 27 years of data to ask the question everyone is asking: does this mean top?

Turning Human Psychology Into a Systematic Edge: Force 5 of Our Five Forces Framework

I spent a decade as a founder and Chief Financial Officer before I started Blackworks Capital, working through acquisitions with our executive team and our board. What stayed with me is how differently the same business gets valued by different parties, sometimes vastly different. Every bidder would work from the same pitch book, the same financials, the same management presentation, and arrive at a different number. So would our team, debating it internally. The asset never changed, the valuations did; all because each party saw the risk and upside differently and to a large extend had higher or lower emotional investment in wanting to win the deal. 

The Engine Room: How Systematic Strategies Are Built, Backtested, and Deployed

Behind every algorithmic trading decision is a process. Not a guess, not intuition, not an idea shouted across a trading floor. A disciplined, repeatable process that moves from hypothesis to tested algorithm to live capital.

Most investors never see inside this process. They see monthly statements and performance reports. Understanding how the engine works isn't about running backtests yourself—it's about distinguishing managers who've genuinely stress-tested their systems from those who've optimized for historical data and hope it persists.

Algorithms vs. Intuition: Why Code Wins in a Volatile Market

The hedge fund of the 1980s ran on conviction. Hire the smartest person in the room, give them capital, trust their gut. The floor trader with decades of experience, synthesizing fragments of information into decisive trades—that was the edge.

That model still exists. But it’s aging out, and there’s a reason.

Overfitting Risk: When a Model Learns the Past Too Well

A student memorizes every practice test for a standardized exam. They can recite 500 answers perfectly. Then they sit the actual test and score mediocrely. They memorized the questions, not the principles.

What Exactly is a Hedge Fund? Dispelling the Myths

The term "hedge fund" carries baggage. Aggressive traders, excessive leverage, secretive strategies, astronomical fees, returns that are either dazzling or catastrophic. Hollywood hasn't helped.

The reality is considerably more mundane. And that's good news.

Decoding Investment Performance: A Guide To Portfolio Metrics

A 25% annual return means nothing in isolation. Was it earned on a smooth ride or through stomach-churning drawdowns? Could you have gotten a similar result from a leveraged index fund? Did the manager deliver it consistently, or was it one brilliant quarter propping up three mediocre ones?

Why Small Systematic Funds Can Be More Nimble Than Multi-Strategy Giants

The financial industry venerates size. A $50 billion AUM figure reads as a badge of competence. Investors have been trained to believe bigger equals safer, more established, more stable.

When it comes to generating alpha, this assumption inverts entirely. Size becomes friction.

True Diversification: The Low Correlation of Systematic Strategies

September 2008. A portfolio manager looks at their statement: 60% stocks, 40% bonds. Diversified by the textbook. Then Lehman collapses. Stocks drop 40%. Bonds—the safe haven—down 15%. Everything falls together.