Fluzcoin price stabilisation
The demand for money does not grow in a simple and linear fashion. In hindsight, It is therefore unsurprising that currencies like Bitcoin which maintain a mostly linear evolution in supply, create excess price volatility with demand being in a constant flux.
Fluzcoin escapes this trap by the above introduced steering mechanisms, which create and remove coins. These mechanisms in the traditional world of fiat currencies would be steered by a board of directors of a central bank; at Fluzcoin they are in the hands of an algorithm, The Fluzcoin Algorithm. This comes with three major advantages:
- Full Transparency: The steering target of the machine is captured and enshrined in a target function known to all market participants; there is no need for second-guessing the motivations of a board of directors or of political agendas. There are no agency costs, there is neither the possibility of bad actors or political risk in the steering.
- On Demand Price Stabilisation: Central banks have to guess the state of the economy and the development of prices from patchy and often stale data — the Fluzcoin Algorithm has access to the records of the ledger (and even more detailed price information, see below) and thus a timely and granular view of the evolution of Fluzcoin and its market prices. The Fluzcoin Algorithm can then act on much richer information and react to new developments much faster.
- Dynamic Learner: It will also learn much faster as it leverages artificial intelligence to make sense of the torrents of data in the ledger and its surrounding system. In order to not be led astray through data mining, the Fluzcoin Algorithm will start with strong priors which represent rules.
These advantages are achieved by combining the empirical knowledge of monetary economics with the adaptability of artificial intelligence and the ability of machines to learn from experience. In short, we are envisaging a Bayesian reinforcement learning system with a strong prior model based on the empirical evidence of human scholarship; the system will be set up to optimise towards a target function which is transparent to the market and will learn from its actions and the reactions in the market; we are adding an element of randomisation and surprise to guard the system against gaming by speculators. It is important to note that the ranges within the Fluzcoin Algorithm can decide and work are set at the outset so that the role of AI is one of efficient running of the system within the confines of a stable and intuitive system; this is what we mean by a strong prior above.
In order to feed the artificial intelligence of the system with data to learn from, Fluzcoin will encourage retailers to send in detailed price data on the transactions they are conducting. This data is cleaned and stripped of identifying details through an anonymising scrambler so that no PII or potentially PII data is handled.
Here is a short video on the EUNOMIA algorithm: