  Motivated by the current fears of a potentially stagflationary global
economic environment, this paper uses new and recently introduced mathematical
techniques to study multivariate time series pertaining to country inflation
(CPI), economic growth (GDP) and equity index behaviours. We begin by assessing
the temporal evolution among various economic phenomena, and complement this
analysis with `economic driver analysis,' where we decouple country economic
trajectories and determine what is most important in their association. Next,
we study the temporal self-similarity of global inflation, growth and equity
index returns to identify the most anomalous historic periods, and windows in
the past that are most similar to current market dynamics. We then introduce a
new algorithm to construct economic state classifications and compute an
economic state integral, where countries are determined to belong in one of
four candidate states based on their inflation and growth behaviours. Finally,
we implement a decade-by-decade portfolio optimisation to determine which
equity indices and portfolio assets have been most beneficial in maximising
portfolio risk-adjusted returns in various market conditions. This could be of
great interest to those looking for asset allocation guidance in the current
period of high economic uncertainty.
