The curriculum says the biggest CME mistake is 'losing sight of the economy.' What does this mean in practice, and how do I avoid it?

It sounds paradoxical, but it happens constantly — and both the tech bubble and the GFC are textbook examples. 'Losing sight of the economy' means allowing your CME process to become mechanically driven by models, data, or market prices rather than grounded in economic reality.

Three Ways It Happens:

1. Model Worship — Letting the Algorithm Decide:

An optimizer says allocate 40% to emerging market debt because the model inputs show high returns and low correlation. The analyst implements this without asking: 'Given the current global growth outlook, currency dynamics, and geopolitical risks, does a 40% allocation to EM debt make economic sense?' The model's output contradicts economic reality, but the analyst trusts the math.

2. Data Dependency — Extrapolating Without Thinking:

An analyst uses 10 years of data showing real estate returns of 9% with 8% volatility and 0.15 correlation with equities. She plugs these numbers into CME without asking: 'Were those 10 years representative? Has monetary policy changed? Are valuations sustainable?' The data describes the past; the economy determines the future.

3. Price-as-Truth — Confusing Market Prices with Fundamentals:

Pre-GFC, tight credit spreads on mortgage-backed securities were taken as evidence that the housing market was safe. The logic was circular: spreads are tight → risk is low → spreads should be tight. Nobody asked: 'What economic scenario would make these spreads appropriate, and how likely is that scenario?'

Example — Oakbridge Institutional's Annual Review:

Oakbridge's CME committee meets annually to set expectations. Two approaches:

Approach A (Loses Sight of Economy):

1. Download 20 years of returns for each asset class
2. Calculate historical means, volatilities, correlations
3. Apply minor adjustments based on recent momentum
4. Feed into optimizer
5. Implement allocation

Approach B (Economically Grounded):

1. Start with a macroeconomic assessment: Where are we in the business cycle? What is the growth outlook? What policy responses are likely? What exogenous risks exist?
2. Derive asset class expectations from economic analysis: If growth slows and the central bank eases, bond returns should benefit while equity earnings face headwinds
3. Check for consistency: Do the equity, bond, and credit forecasts tell a coherent economic story?
4. Stress-test against exogenous shocks: What if a trade war escalates? What if a technological breakthrough accelerates growth?
5. Only then optimize and implement

Approach A will work during normal times and fail spectacularly during transitions. Approach B adapts to changing conditions because the economy — not the data — drives the forecast.

The Practical Test:

After setting your CMEs, ask one question: 'What economic scenario is implied by these numbers, and do I believe that scenario is the most likely outcome?' If you can't articulate the implied scenario, you've lost sight of the economy.

Explore economic analysis in CME in our CFA Level III question bank.