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description: A Stable Cryptocurrency for New Economics Opportunities
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# Native Stable Cryptocurrency

The evolving decentralized commerce necessitates stable cryptocurrencies. Yet, the emerging cryptocurrency market is afflicted with significant volatility. Unlike its centralized counterparts, the cryptocurrency market is not subject to centralized policy making via fiscal and monetary policy tools that ensure the management and stability of purchasing power of cryptocurrencies. Decentralized commerce, in turn, is less likely to evolve if the average consumer cannot rely on the enduring purchasing power and stability of cryptocurrencies over time. &#x20;

The Semada native low-volatility cryptocurrency (SEM) is pegged to a CPI with 0% inflation. In the beginning this will be estimated by pegging to an inflation adjusted average of USD, Swiss franc, and Singapore dollar. To ensure that the SEM/US Dollar exchange rate is stable at around one US Dollar, the Semada Stability Mechanism (SSM) provides core policy tools that help adjust the supply of SEM in response to  SEM price movements. Similar to earlier attempts in the Basis model, the mechanism enabling price and purchase power stability in SSM involves 3 tokens: 1. SEM, 2. BONDS, and 3. SHARES. SSM uses the Semada core voting algorithm for decentralized autonomous organizations (Stability DAO or SDAO) to improve the Basis model in several core policy functions in a fully decentralized and autonomous way. We illustrate the mathematical limits of crash and burn scenarios of earlier attempts and contrast them with our own stability mechanism and its theoretical limits.



## Background

According to the IMF, 80% of countries in the world are in a developing state and face economic uncertainty, financial volatility, lack of financial infrastructure and are defenseless against ineffective monetary policies. Stable cryptocurrencies can help address economic uncertainty and financial volatility and support building a modern economic infrastructure for afflicted countries and economies.

As cryptocurrencies evolve, they can provide core functions that are currently suboptimally provided in centralized economies. Cryptocurrencies can provide more than just stability for the cryptocurrency market as safe-harbor for investors. It is possible that in certain countries stable cryptocurrencies can function as a replacement for paper fiat currency. Countries with high inflation and year to date currency devaluation, such as Venezuela (2018: -99%), Argentina (2018:-53.2%), Turkey (2018: -38.4%), and Brazil (2018: -20.6%), among others, have started to evaluate currency alternatives to offset some of the effects of currency devaluation in their economies. In fact, some governments have already started experimenting with government sponsored digital- and cryptocurrencies. Examples include Tunisia (eDinar), Venezuela (Petro), Senegal (eCFA), Sweden (eKrona), Dubai (EmCash), Japan (Jcoin), and Estonia (Estcoin), and Ecuador, among others. These early attempts by some countries suggest that the countries that are most in need may some day decide to issue their own digital/cryptocurrencies by pegging it to an existing stable cryptocurrency. As such, stable cryptocurrencies can provide a stability mechanism for modern economies.

We examine stable cryptocurrency design from the perspective of economic experimentation. Emerging decentralized economic incentive designs allow unprecedented economic experimentation. Each of these new economies are created with the design of a currency and can have unique monetary and fiscal policies and regulations. The infrastructure for these economies is computational. Establishing a stable currency design in an emerging decentralized crypto-economic environment is mostly free from the real-world constrictors that curtail central banking. We examine the quantity theory of money and expand the existing models.

## Related Research

### Quantity Theory of Money

The quantity theory of money predicts that money growth should be neutral in the long run in its effects on the growth rate of production and should affect the inflation rate on a one-for-one basis. In David Hume's pioneering essays of 1752, Of Money and Of Interest,  Hume stressed that changes in the number of units of money in circulation will have proportional effects on all prices that are stated in money terms. In turn, Hume suggests that  changes in the number of units of money in circulation have no effect on economic output, e.g. on how much people produce or on the goods they produce or consume.

The quantity theory of money has evolved dramatically since the beginnings of modern monetary theory in Hume’s pioneering essay. Especially the issue of underlying assumptions and the kinds of changes that can result in neutral monetary changes have been evaluated in significant academic contributions. Of at least equal importance, academics have made significant progress with an enormous amount of evidence on money, prices, and production over the past two centuries. Similarly,  issues of measurement have been explored and continue to occupy a large parts of econometrics.

The economic turmoil of the 1930s shifted attention away from problems of monetary neutrality and lead to a focus on monetary policy for short-term economic stimulus. By the 1960s, economists started to use two closely related general equilibrium frameworks to think about economic dynamics. Hicks (1939), Arrow (1951), McKenzie (1954), and Debreu (1959) developed the mathematical model of general equilibrium which defines the commodity vector to include dated claims to goods. In 1982, in a paper that dominated the research agenda for the next decade, Kydland and Prescott (1982) utilized a version of the stochastic growth optimal growth model of Brock and Mirman (1972) as an operational model of a competitive economy undergoing recurrent and technology innovation induced business cycles. While the potential of such models without money as the centerpiece is still being realized today, these models only marginally help economists who investigate monetary forces and their effects on business cycles.

Samuelson (1958), introduced another general equilibrium framework that was better suited to the study of monetary questions. Samuelson’s paper introduced the idea of an economy in which money had no direct use in production or consumption and yet played an important role in economic life. Lucas (1972), used the Samuelson model to evaluate how monetary neutrality can be reconciled with a short-term stimulus from a monetary expansion.

Sims (2012) examines the evolution of monetary policy and its effects since the 1950s. Sims underscores that views strongly held in earlier decades of policy making and scholarship have since been shown to be mistaken. He encourages skepticism of consensus views without consulting new data or examining old data with new methods.

### Existing Stablecoin Designs

The evolution of stable cryptocurrencies creates a new opportunity to reexamine earlier decades of monetary policy making and scholarship. It allows an expansion of the existing quantity theory of money and associated models.  In 2014, Sams (2014) introduced the first attempt at creating a stability mechanism for cryptocurrencies. Sams’s early academic attempt was quickly followed by commercial applications and expansions of his earlier vision.\


Several active projects are attempting to create stable cryptocurrencies. Existing projects fall into two broad approaches, e.g. collateralized and non-collateralized tokens. Both are subject to significant downsides. Collateralized projects use either fiat currencies or cryptocurrencies as collateral. Both have downsides. Collateralized fiat currency pegs bear the brunt of expensive capital requirements and collateralized cryptocurrency pegs face heavy volatility pressures and swings.

Most fiat currency collateralized projects claim to be 100% backed because otherwise they run the risk of attacks similar to what Financier George Soros used to “break the bank of England”. Fiat currency collateralization is expensive and inefficient because all of the value that is backing the cryptocurrency needs to be liquid, otherwise arbitrage opportunities, such as the Soros attack, are possible. Therefore, the price tag of fiat-backed tokens is, at a minimum, the interest rate of the pegged fiat currency.

Cryptocurrency-backed tokens, are even more expensive, since the stability is achieved with the (currently) much more unstable cryptocurrencies. The stable coin must be backed with much more than 100% of the current value of the cryptocurrency in case the crypto currency’s value drops. For example, in MakerDAO, if a token is backed by Ether, and Ether drops by half at any moment, then the automated scheme will punish anyone who has not backed their tokens by more than 200%.

The non-collateralized schemes include Basis and NuBits, which follow the quantity theory of money, algorithmically minting and burning tokens in order to maintain a peg.

## Cryptocurrency Stability Mechanism

Stable cryptocurrencies are afflicted by several fundamental problems. Without strong privacy for the currency the currency is not truly fungible as a currency from questionable sources is not as valuable if there is a chance it can be confiscated in the users’ jurisdiction. The psychology of general users who do not trust a currency that is not backed by anything (most people still think fiat money is backed by gold) undermines market adoption of stable cryptocurrencies. And, rational self interested actors as stable cryptocurrency owners can create risks to the success of the stable coin.

After review of the leading stable coin mechanisms and associated literature, we use the Basis paper with the majority of assumptions therein as the foundation for the SSM. Yet, several important critiques of the Basis stability design lead us to desire core improvements over the Basis paper. Problems with the Basis mechanism include: 1) a lack of clear governance for the oracle and mechanism optimization functions, 2) a lack of clear governance for security in the face of eventualities when the algorithmic model fails to maintain stability, e.g., a) black swan events, b) long-term constant or decreasing demand leading to unbounded bond queue growth, 3) lack of fundamental value to the token, 4) lack of a reserve mechanism that functions as a backup if the bond sales fails as a stability mechanism.  \
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