Goldman Sachs forecasts low long-term S&P 500 returns (3-6.5% annually). The key reason is that today's high market concentration implies higher future volatility, yet investors aren't being compensated for this risk because current valuations are already historically high and likely to contract.

Antti Ilmanen contrasts two forecasting methods. Objective forecasts (e.g., using market yields) predict higher returns from low valuations. Subjective forecasts (from investor surveys) extrapolate recent performance, becoming most bullish precisely when objective measures signal the most caution, creating a dangerous conflict for investors.

Analysts projecting markets decades out, like Morgan Stanley's $5T humanoid robotics market by 2050, are effectively admitting profound uncertainty. These predictions are too far-reaching to be credible and serve more as speculative placeholders than as actionable intelligence for investors.

While institutional capital market assumptions align with objective, yield-based models, their actual portfolio actions can deviate. Many institutions, despite models suggesting caution on expensive US stocks, maintained market weight, benefiting from the prolonged bull market. This highlights a critical inconsistency between their stated process and real-world behavior.

When predicting major economic shifts like a bond market crisis or an AI stock correction, being wrong in a specific year doesn't invalidate the thesis. The underlying pressures may still exist, with the predicted event simply postponed. This reframes forecast misses as primarily errors in timing rather than analysis.

The market for financial forecasts is driven by a psychological need to reduce uncertainty, not a demand for accuracy. Pundits who offer confident, black-and-white predictions thrive because they soothe this anxiety. This is why the industry persists despite a terrible track record; it's selling a feeling, not a result.

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.

While being a market Cassandra can build a reputation, being too early is costly. Charles Merrill of Merrill Lynch famously warned of a crash in 1928, but investors who heeded his advice missed a 90% market run-up before the October 1929 peak, illustrating the immense financial downside of exiting a bubble prematurely.

In 2025, economic forecasts were incredibly accurate on monthly job growth (predicting 124K vs. an actual 125K) but significantly missed the stock market's performance, predicting a 10% gain versus the actual 15%. This highlights the disparity in predictability between fundamental economic data and sentiment-driven financial markets.