The network reveals the sources of fragility, overlapping exposures, and, relevant feedback effects. For instance, it becomes clear than Ether prices are affected by changes in BTC prices and not the other way around. It also can be understood what are the shared risk drivers (e.g. the usage of X1 has an effect on both BTC and ETH), which allows for more control over aggregate factor exposure.
This approach also allows uncovering secondary effects. A bet on X11 and X3 may prove ineffective since those have a relationship of mutual dependence --but their risk profiles are different since X3 is exposed to both crypto asset prices directly; they also affect the environment differently --X3 has a higher outdegree than X11. This makes sense: in practice, a wallet service will be more affected by activity in selected exchanges, than directly by prices.
Finally, the heuristic makes tractable the nodes of systemic importance, e.g. X1, X3, and X13, all have a relationship with bitcoin prices. This is something that would be impossible to find in a traditional network representation such as Figure 1.
Regulatory and Cyber risk
The simplified network also offers an opportunity to disambiguate opaque situations. For instance, X13 appears to portrait a spurious relationship (how can a service affect the price of a decentralized currency?), but a closer inspection reveals the occurrence of a tail event. After the crackdown of the Chinese government on bitcoin exchanges in September of 2017, one of the most popular exchanges rebranded and initiated operations as an international service (but still, being accessed mainly from mainland China). As we can see in Figure 6, the remarkable growth in what would be an impossible timeframe for most online services (several orders of magnitude in less than 6 months) not only explains the behavior captured by the model, but provides evidence of the increase on the survival rate of systemically important nodes in the crypto economy. Some services prove hard to kill, even if they operate in the centralized part of the economy. In this sense, those components enhance the anti-fragile characteristics --they simultaneously boost the underlying, and may even benefit from the shocks.