Fragments: A Path to Ideal Money - Evan Kuo presentation
1. Cryptocurrencies - A Path to
Evan Kuo, www.fragments.org
Mathematician and economist John Nash, famous for
his Nobel winning work on non-cooperative game
theory, first conceived Ideal Money around the early
At the time he became troubled by the fact that certain
currencies, as part of the International Monetary Fund
(IMF), had agreed to fix exchange rates with one anoth-
er. Nash’s concern was that a fixed exchange ratio be-
tween currencies would encourage hyperinflation
2. Troubled by fixed exchange ratios ...
Let’s say Alice & Bob agree to a fixed rate:
1 Alice Coin = 1 Bob Coin
1 Bob Coin = 1 Gold Nugget
• Alice can always exchange for Bob coins, and
then redeem them for gold
• So Alice stands to benefit by inflating her coins as
fast as possible, trading for Bob coins, and then
gold, before Bob catches on
3. Not a Healthy Game ...
• Thinking this was not a healthy game, Nash
immediately traded his USD for Swiss Francs
• He considered Swiss Francs “better money”
because they were not subject to fixed exchange
ratios, and were more likely to hold their value
• Nash went on to imagine what an “ideal money”
would be like and spent the last 20 years of his life
promoting the concept of Ideal Money
4. Ideal Money (Abstract)
Definition: A solution to the conflict between near-term domestic interests
and long-term international interests that occur, when using a country’s
currency to stabilize international currencies.
5. Today Independence is much easier
• We have thousands of new and government
independent cryptocurrencies like Bitcoin and
Ethereum, any of which could adopted as global
We can simplify our definition by dropping the
parts about geopolitical conflict
7. But can we state this concretely?
• This definition is simpler, but still abstract
• Many economic theories can now be empirically
tested using cryptocurrencies, but we need testable
8. Let’s think in Functions of Time
• Imagine Store of Value as a simple likelihood
function over time
• This function takes time as its input (given an
initial sum of money) and returns the likelihood of
retrieving the purchasing power committed
Fiat looks good zoomed in
Gold looks good zoomed out
Ideal Money must look good both ways
10. But How? The Inflation Paradox
We encountered this problem immediately:
• Frustrated, I reached out to Paul and Joey at
Pantera. After some thought, Joey reminded us
that when a stock splits, supply increases but your
net holdings are unaffected.
• Excited, we went on to design a protocol for crypto
currencies that split on inflation.
The mechanism of inflation that keeps fiat currencies
stable near-term is also what devalues them long-term.
A low volatility cryptocurrency that splits on inflation.
The currency is designed to store both near and long-
term value converging on the characteristics of Ideal
Money. Our first token is the USD Fragment, price tar-
geted at the US Dollar.
12. A High Level Example
Floating Price Model
Imagine you purchased 1 BTC at $1, and now have 1 BTC
Now imagine an alternate world in which you again pur-
chased 1 BTC at $1, but this time you have 10000 BTC
each worth $1.
13. In Practice ...
To prevent balances from shrinking:
• We first capitalize an ETH reserve
• And then split proportionally to token holders
This reserve capitalizes under expansion so that it can
buy back and remove tokens under contraction
14. Dynamic Reserve Ratio
The Fragments reserve intelligently computes reserve
ratio in each rebase period. It responds to two differen-
• Relative change in Supply
• Relative change in Purchasing Power
• Allocates more to reserve under rapid expansion
• Allocates less to reserve under gradual expansion
* More on this in the Appendix
15. A Buy & Hold Hedge
Major cryptocurrencies today, tend to be highly cor-
related when looking at a 90 moving average. When
dips occur, investors are faced with the frustrating di-
lemma of either.
• Accepting losses and reallocating.
• Not knowing when they can responsibly withdraw
By design, Fragments offer downside protection but
will also gain in a manner uncorrelated with major coins.
When floating price currencies dip, traders retreat into
stable currencies. In the case of Fragments, demand
pressure triggers currency splits.
16. A Platform for Stable Utility Tokens
Today’s Utility tokens are simultaneously priced based
on two very different qualities.
• Network Market Cap ( based on expected annual
rates of return over a 5-10 year time horizon)
• Utility Value (what customers are willingn to pay for
a utility or service like 1 hour of compute time).
Projects using the Fragments protocol will be able to
stabilize unit prices while maintaining network effects
for early adopters. Eventually our currency can be
pegged to a basket of commonly used utilities or com-
17. Working with Pantera
As Investors and Advisors.
• Paul Veradittakit
• Joey Krug
Other Investors Include:
• True Ventures
• Founder Collective
• FBG Capital
• Brian Armstrong
18. Appendix A - stabilization layers
We take a layered approach to stabilization.
It’s a common misconception that expansion and contrac-
tion occur in equal measure. At any given moment, there
can be infinite potential buy pressure, but only finite sell
pressure. For this reason markets tend to be heavy tailed.
• At the inner layer, a network of market makers
benefit from simple arbitrage, and are the first line of
defense against volatility.
• At the outer layer, sits our reserve and supply policy.
19. Appendix B1 - sensitivity parameter
At some threshold of change T_high, the reserve will out-
put a reserve requirement of 1.0. As a result the reserve
can be adjusted to be more or less sensitive to change.
• At low (conservative) thresholds the system behaves
like a parity reserve, overcollateralizing
• At high (liberal) thresholds, the system behaves more
like a fractional reserve.
Low thresholds optimize for fault tolerance. High thresh-
olds optimize for splitting to coinholders. Our objective is
• Maximize distribution to coinholders
• Minimize reliance on lenders of last resort
22. Appendix C - automated market making
The more robust our market making network, the more
safely we can increase our sensitivity threshold, and thus
maximize distribution of supply to token holders.
Fortunately, one of the key advantages of knowing a price
target is that corrections can occur very quickly, and some
of this trading can even be automated.
The Fragments foundation will participate as a market
maker alongside others.