The advent of blockchain technology, tokens, and crypto assets, combined with sufficient computing power to simulate interacting heterogeneous economic agents in realistic scenarios, has opened novel possibilities for management of new types of assets.

This paper presents a simplified methodology for either proprietary traders or bank trading floor strategists, to design small, transparent models based on macroeconomics that can explore potentially profitable situations through predictive analysis.

After a statement of motivations, and a brief review of macroeconomic modeling litterature, come the description of this hybrid DSGE ISLM model architecture, the set of equations at its core, and details of its construction : The process of building this model use specific Excel features to simulate and generate scenarios as sample paths of macroeconomic variables. Chosen examples of numerical results are graphically shown and commented.

Finally, some remarks and ideas of extension for this model in future works conclude this paper.