Single-factor models (e.g., using only CPI data) are fragile because their inputs can break or become unreliable, as seen during government shutdowns. A robust systematic model must blend multiple data sources and have its internal components compete against each other to generate a reliable signal.

Related Insights

Many macro funds, especially quantitative ones, are facing headwinds because their models are optimized for trending markets. The current choppy, volatile environment lacks the long, clean trends seen in previous years, leading to performance dispersion across the industry.

A key second-order risk of the government shutdown is the halt of incoming economic data. This data blackout impairs the Federal Reserve's ability to make informed monetary policy decisions, creating significant uncertainty for investors and the broader economy ahead of key meetings.

Despite providing real-time labor market data, firms like Revealio Labs depend on foundational government statistics to reweight their datasets for accuracy. This calibration process is only needed about once a year, allowing their models to function for a considerable time during government data blackouts without significant degradation.

Mathematical models like the Kelly Criterion are only as good as their inputs. Historical data, such as a stock market's return, isn't a fixed 'true' value but rather one random outcome from a distribution of possibilities. Using this single data point as a precise input leads to overconfidence and overallocation of capital.

A key indirect risk of a shutdown is the delay of vital data releases on labor and inflation. This forces investors and the Fed to operate in an information vacuum, increasing uncertainty and the potential to overreact to anecdotal signals, creating outsized market effects.

The firm doesn't just decide a factor is obsolete. Their process begins by observing within their transparent 'glass box' model that a factor (like book-to-price) is driving fewer and fewer trades. This observation prompts a formal backtest to confirm its removal won't harm performance.

The Federal Reserve is not 'flying blind' during government shutdowns that halt official statistics. It uses a composite of alternative indicators for the labor market and inflation, providing enough of a signal to stick to its pre-planned policy path, such as proceeding with scheduled interest rate cuts.

While the "quad" economic outlook is crucial, the ultimate authority is the market's "signal"—a multi-factor model of price, volume, and volatility. Keith McCullough states if he had to choose only one, he would rely on the signal, as it reflects what the market *is* doing, not what it *should* be doing.

A government shutdown lasting several weeks poses a greater threat than just delayed reports. Data collection for time-sensitive indicators like the Consumer Price Index becomes impossible or unreliable, as prices can't be collected retroactively and people's recall fades, potentially forcing agencies to skip a month of data entirely.

To survive long-term, systematic trading models should be designed to be more sensitive when exiting a trade than when entering. Avoiding a leveraged liquidity cascade by selling near the top is far more critical for capital preservation than buying the exact bottom.