The paper provides an operational strategy design tool that allows asset managers variously to increase information ratios, better understand the performance implications of design choices, and use what-if scenarios to make more informed risk-return decisions. The scenario approach is well-known in risk management: the design formulae here allow us to apply it to information ratio management. They include active risk, active return, turnover, signal and factor exposures, position size and other quantities. A straightforward investment model underlies the tool, and the formulae are quickly evaluated using standard software.

Several examples illustrate their use: incorporating Environmental, Social and Governance considerations; blending Smart Beta investing with active asset-selection; using custom risk controls; exploiting differences in predictive power across sectors; and determining the performance impact of inter-asset correlations both between returns, and between return forecasts.

These last results reverse common consensus. They show that cross-sectional correlations, while reducing independence, improve rather than impair investment performance. All else equal, active managers should be more aggressive when return correlations are expected to be high, not low, and should embrace, not avoid, forecasts that are correlated across assets. This disrupts our understanding of breadth, but other core insights of the fundamental law of active management remain part of our investing DNA.

Monte Carlo simulations verify the design formulae, and qualitative descriptions provide the intuition behind the observed behaviors.