Credit spreads are leading indicators of real activity but only capture pricing information. I show that quantity-based indicators, specifically net flow into open-end funds primarily investing in leveraged loans, provide additional predictive content. Using monthly indicators and conditioning on a broad set of controls, credit spreads reduce out-of-sample forecast errors in the next two years by up to 9%, while loan fund flow further reduces these errors by up to 7%. A dynamic corporate investment model with a slow-moving financing capacity state, which lags behind fast-moving fund flows, explains this price-quantity timing asymmetry in the forecasting power.