Valuation in a volatile market: practical adjustments
In volatile regimes, valuation requires explicit scenario layering to capture differing macro outcomes. This post explains an approach that combines discounted cash flow with macro state probabilities and market-implied signals to form a blended expected-return estimate. We show how to calibrate growth and discount-rate paths to observable market data while preserving judgment overlay for idiosyncratic factors. The method produces a return distribution rather than a single point estimate, enabling investors to quantify downside thresholds and the marginal contribution of each assumption. By documenting inputs and running sensitivity matrices, advisors can present governance-ready narratives that identify which assumptions drive portfolio-level changes and which are relatively immaterial for allocation decisions.