A Brief Primer on Navigating TokenSpace
TokenSpace may be considered by analogy with our own spatio-temporal conception of reality, consisting of a three-dimensional space delineated (for convenience and visual clarity) by orthogonal axes
methods currently in development. Each asset’s location in TokenSpace is intended to be derived from a weighted scoring system based upon taxonomy, typology, intuitive, elicited and/or quantitative methods depending on the choices and assertions of the user — which may or may not be identical to those proposed in this work.
Definitions of the proposed meta-characteristics:
Example scores for a range of assets are outlined in the tables below with visual depictions. Ideal types are postulated canonical examples of particular asset types and are discussed in Section 2 of the manuscript. It is the aim of this and future research to provide suggestions for classification approaches and some examples on how TokenSpace may be utilised to comparatively characterise assets from the perspective of various ecosystem stakeholders. Time-dependence may also be significant in certain instances and can be incorporated into this framework by evaluating an asset’s location in TokenSpace at different points in time and charting asset trajectories.
TokenSpace is expected to be useful to regulators, investors, researchers, token engineers and exchange operators who may construct their own scoring systems based on these concepts. Careful review of territory-specific regulatory guidance and judicious consideration of boundary functions for example delineating “safe”, “marginal” or “dangerous” likely compliance of assets with respect to particular regulatory regimes are recommended and an example is presented in Figure 3. Parallel Industries has developed hybrid multi-level hybrid categorical/numerical taxonomies for each meta-characteristic alongside time-dependent and probability distribution functions for anisotropic score modelling.