Systematic models don't attempt to forecast unpredictable shocks like policy changes. Instead, they build portfolios with 'guardrails'—diversifying away concentrated macro risks like sector or country bets—to ensure resilience and avoid being badly damaged by any single event.

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Instead of simply owning different stocks and bonds, a more robust strategy is to hold assets that perform differently under various economic conditions like high risk, instability, or inflation. This involves balancing high-volatility assets with stores of value like gold to protect against an unpredictable future.

Owning multiple stocks or ETFs does not create a genuinely diversified portfolio. True diversification involves owning assets that react differently to various economic conditions like inflation, recession, and liquidity shifts. This means spreading capital across productive equities, real assets, commodities, hard money like gold, and one's own earning power.

David Kaiser's system doesn't try to predict cyclical peaks. Instead, it mitigates the risk of buying hot cyclical stocks by owning a diversified portfolio and rebalancing consistently. This structural approach ensures that if the model over-allocates to a sector at its peak, the error is contained and corrected relatively quickly.

Conventional definitions of risk, like volatility, are flawed. True risk is an event you did not anticipate that forces you to abandon your strategy at a bad time. Foreseeable events, like a 50% market crash, are not risks but rather expected parts of the market cycle that a robust strategy should be built to withstand.

A more robust diversification strategy involves spreading exposure across assets that behave differently under various macroeconomic environments like inflation, deflation, growth, and contraction. This provides better protection against uncertainty than simply mixing asset classes.

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.

Long-term economic predictions are largely useless for trading because market dynamics are short-term. The real value lies in daily or weekly portfolio adjustments and risk management, which are uncorrelated with year-long forecasts.

The goal of diversification is to hold assets that behave differently. By design, some part of your portfolio will likely be underperforming at all times. Accepting this discomfort is a key feature of a well-constructed portfolio, not a bug to be fixed.

The goal of classifying the market into regimes like "slowdown" or "risk-on" is not to predict exact outcomes. Instead, it's a risk management tool to determine when it's appropriate to apply significant leverage (only during clear tailwinds) versus staying defensive in uncertain conditions.

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.