Putting Economics Back in Economic Scenarios

Rising complexity in the world and structural breaks across markets require new non-stochastic approaches to scenario generation. The world is also too complex for simplistic ad-hoc assessment. We demonstrate the insights gained by implementing a supply chain agent-based model (LINKS Mira) and run the “China hard landing” scenario with curious conclusions.

As the world goes through a significant economic and political transformation, the number and complexity of risks and opportunities for institutional portfolios increase considerably. Gone are the days when the direction of globalization and integration was unquestionable, the question was just the differences in pace.
Increasing complexity creates additional problems for investment management. How does one manage risk and return in an environment where history is no longer a fair guide? Typically, economic scenario analysis and stress testing are the tools of choice. The common approach is statistical: basic models rely on stochastic processes with a random variable drawn from normal distribution, while more complex approaches involve multiple distributions, decomposition into multiple trend patterns and regime switches. A less common approach is designing ad-hoc descriptive scenarios in the context of the growth-inflation framework. Both approaches fail to deliver actionable results.