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/ Bretton Woods

With Money, Change is Certain

With Money, Change is Certain

The last time money changed, it happened with a whimper, then a bang. In the twilight of the Second World War, 44 nations sent delegates to Bretton Woods to build a global economic system that could avoid depression, indemnity, and hyperinflation. After a month, they had built the World Bank Group, as well as what they hoped was a stable global financial system. And it worked: for 26 years, the world had a near absence of banking crises.

But Bretton Woods had a fatal flaw.

One of the system’s core features was the dollar’s use as a reserve currency, which created for it two contradictory uses: one as liquidity within the United States economy, the other as an asset held by foreign nations. The first use required low inflation and a stable price while the second needed more appreciation to maintain value. These tensions, made of contradictory policy promises, pulled the dollar in irreconcilable directions. Rather than wait for the snap, Richard Nixon announced in 1971 that the United States Dollar would no longer be indexed to gold, ending the Bretton Woods system and moving the modern world into an era of pure fiat currency. It also triggered a decade of stagflation.

Today, Bitcoin too faces Triffin’s Dilemma. While proposed as a peer-to-peer digital cash system, the first cryptocurrency has found more lasting traffic as an extremely unstable asset, less liquid than its creators would have liked but more fitting to its profile as “digital gold.” Those long-term holders would prefer that Bitcoin continue to appreciate so they can make returns on their investment. Many early adopters would instead prefer that Bitcoin stabilize in order to facilitate mass adoption in commerce. Bitcoin, caught between these two extremes, by design lacks either a board of governors to force a resolution or an internal design that can resolve the issues of dual use.

But Ampleforth has a solution to this dilemma. With these pressures in mind, we’ve created a cryptocurrency both decoupled from Bitcoin’s fluctuations and immune to the pitfalls of a fully deflationary currency. To do that, we’re building on George Selgin’s proposal of “synthetic commodity money,” an asset with a real cost of production that can still be adjusted in response to economic forces. In short: cryptocurrency. To overcome the limits of old money, we’re making something new, with a unique structure and movement pattern that makes it not only different than bitcoin, but potentially uncorrelated as well.

It took great minds to solve the currency shocks and crises of the past century, and now we are putting their Nobel-winning theories to work by creating Amples (AMPL). To learn more, please check out our Red Book, where we outline the economic principles guiding our design. Now, as before, money is set to change. Satoshi Nakamoto took the first great step in 2009. At Ampleforth, we’re ready to make the next leap.

/ Kahneman

Great Economists: Daniel Kahneman

Great Economists: Daniel Kahneman

Daniel Kahneman is one of the most studied and accomplished economists of the second half of the twentieth century, based off his groundbreaking integration of economics and psychological research surrounding human decisions in the face of uncertainty. His work with Amos Tversky earned him a Nobel Prize in economics in 2002.

Prior to Kahneman’s research in this field, economists had found a fundamental issue with how humans estimate the probabilities of certain outcomes under uncertainty. In theory, facing uncertainty, some people should underestimate the probability of an outcome, while others should overestimate the probability, leading to the results cancelling out statistically. However, Kahneman’s findings proved this theory incorrect: in practice, most people incorrectly estimate the probability of an outcome. The two economists found two important biases people have when trying to determine the probability of an outcome.

The first bias they found was the incorrect importance people place on small sample sizes, a term they coined “the law of small numbers.” Take the example of drug use in patients. If a drug is 80% effective, people assume that if 5 patients are treated, the drug will work in 4 of those cases. However, this is not true. It is statistically unlikely that if 5 people are treated, the drug will work on 4 people. Kahneman discovered he fell victim to this bias in his early work as a military psychologist. After observing officer candidates in a short period of time, he was expecting those who performed well in the training period to perform at the same level throughout their career. He said later on the law of small numbers, “As I understood clearly only when I taught statistics, the idea that predictions should be less extreme than the information on which they are based is deeply counterintuitive.”

A second bias present in Kahneman’s findings was “availability”: if people are exposed to certain examples, they are more likely to incorrectly estimate the probabilities of those examples. For example, people are more likely to overestimate the probability of shark attack if they know someone who was attacked.

Besides the biases present under uncertainty, Kahneman is also known for his introduction of “prospect theory.” Essentially, they found the circumstances surrounding decisions matter. Take for example the case of a person choosing between two identically performing funds. The advisor of the first firm tells the customer they have 25% returns over the last 5 years. The second advisor tells the same person they have returned well above the market over the past 25 years, but recently have fallen off slightly. Even if they still had 25% returns over the past 5 years, the customer is more likely to put his money in the first fund, based off the circumstances and framing of the decision.

How is Kahneman relevant to crypto? If a person bought into bitcoin when it was at $18,000, then proceeded to lose much of their investment, they are more likely to stay away from crypto, as the small interaction they had cost them their hard-earned money. Likewise, if a person either bought into Bitcoin early, or knows many people who did, the small sample they have relating to crypto would lead them to overestimate the probability of crypto currencies succeeding. Small sample sizes and personal examples drive many people’s decisions under uncertainty, which in the case of crypto, means sentiment drives much of the market value.

As for Kahneman's influence on Ampleforth, you may have noticed a chapter in our Red Book named Thinking Fast & Slow. One of Kahneman's most popular works is a book he wrote with that title.
/ John B. Taylor

Famous Central Bankers: John B. Taylor

Famous Central Bankers: John B. Taylor

John B. Taylor is one of the greatest economic minds of the 20th and 21st centuries. His work in macroeconomics and monetary policy helped create one of the most important Macroeconomic tools today, The Taylor Rule, which is used as an interest rate forecasting tool. He served as an  economic advisor to President’s Ford, Carter, George H. W. Bush, and George W. Bush. Currently, Taylor is a professor of economics at Stanford University and has won numerous awards in the field of economics, including the 2016 Adam Smith Award and 2015 Truman Medal for economic policy.

The Taylor Rule, as coined following his 1993 research paper, proposed that manipulation of short-term interest rates by the central bank could serve as a counter and pro cyclical force on the economy. He proposed to raise rates when growth and inflation was excessive and cut rates if they fell below targets. His simple interest rate equation is now largely used as an effective formula for interest rate levels.

Besides his work on monetary policy and what the central bank should attempt to manipulate, Taylor has also done extensive research on the financial crisis of 2008. In particular, Taylor focuses on the actions of the Federal reserve, noting how interest rates were kept too low for too long, allowing for an excessive amount of output growth and inflation to occur. He proposed that the economic crisis was a direct result of government inactions, actions, and interventions, rather than a failure by the private economy.

Following the crisis, Taylor has stressed the importance of a stable monetary policy, rather than the quantitative pro and counter cyclical measures that the Fed had been using. Balance in the economy is of the utmost importance to Taylor, and his work reflects that.

Ampleforth’s protocols and automatic expansions as well as contractions serve to create the stability in the Ampleforth network that John B. Taylor believes should be present in the US economy. Fiat counter cyclical pressures are driven by those in charge of the Fed and can be influenced by any number of factors. The countercyclical pressures present in Ampleforth are market drive, rules-based, and non-dilutive for anyone holding the token, creating a static, stable policy. There is not an easing due to external pressures, rather, the policy to absorb shocks in the Ampleforth Network is constant, just as Taylor wants of US economic policy.

To understand more about creating a stable system that is less prone to biases and human driven overcorrection and error, read our chapter on Rules vs. Discretion.

/ FA Hayek

Great Economists: Friedrich August Hayek

Great Economists: Friedrich August Hayek

Friedrich August Hayek has been hailed as one of the preeminent economists from the latter half of the twentieth century. His work on monetary theory and the interdependence of economic, social, and institutional phenomena won him a Nobel Prize in 1974, and his writings from the early twentieth century is still read heavily by graduate economic students today.

FA Hayek

Besides his Nobel Prize work on monetary theory and interdependence, Hayek was one of the pioneers and strongest advocates for the Austrian school of economics, along with Gottfried Haberler and Fritz Machlup. Furthermore, after becoming the director of the Austrian Institute of Business cycle research, Hayek became a professor at the London School of Economics.

Beginning in the 1920s, and progressing through the 1940s, Hayek’s work on business cycles, capital theory, and monetary theory as well as the connection between the three brought him international acclaim. According to Hayek, markets evolve due to people- that is to say, markets were never planned, they came to be due to the actions of people involved in the markets. His theories on business cycles caused him to become well acquainted with the work of John Meynard Keynes.

The two battled over the differences in their economic theories, with Keynes an obvious proponent of Keynesian policies, while Hayek believed Keynes’s policies to combat unemployment would inevitably lead to unemployment.

Following his work on business cycles, Hayek turned to the study of social planning, concluding it could not work, as data is necessary to create a functioning market, but it is the markets themselves that generate data. If there were no markets, there would be no data. Hayek turned to combat the growing socialist sentiment in Britain following WW2, in his book The Road to Serfdom (Which you can read for free here, provided by the Mises Institute). It was then one of his strongest opponents, Keynes, who gave him the most praise for his anti-socialism work.

Following his Nobel Prize win in 1974, Hayek became more radical, and began to advocate for the denationalization of money, as an early proponent for the idea behind digital assets. Hayek argued privatized enterprises distributing currency would incentivize them to keep up their purchasing power, as users could choose between different currencies. Hayek pioneered the ideas behind the denationalization of currencies, and his theories can be seen in use today across digital assets.

You can watch his take on the denationalization of money here:

/ Ampleforth

Ray Dalio: Correlation 'Holy Grail'

Ray Dalio: Correlation 'Holy Grail'

In the video “Ray Dalio breaks down his ‘Holy Grail’”, he sets out to break down what were the marginal benefits of diversification within a portfolio. Ultimately, using the graph below, Ray Dalio broke it down into 3 pieces: Risk, which he called the standard deviation, the number of assets or the sample size, and the correlation of the bets.

Ray Dalio Discusses His Diversification "Holy Grail" 

What he found in doing so was the higher the correlation between assets in a portfolio, the lower the ability to reduce risk by increasing the number of investments. Essentially what this means is if you take a group of investments that are 60% correlated, there is no real reduction in risk after adding more than 4 investments to the portfolio. It’s only in diversifying your portfolio that allows you to cut your risk.

Correlation of Assets Impact on Risk and Return

Dalio says for an ideal return on investment, investors should find 15-20 good, uncorrelated return streams, as that will allow for the most return on investment while cutting risk. In taking 15-20 good investments, with a 0% correlation, using Dalio’s chart, the return to risk ratio is 1.25, meaning the probability of losing money in a year is 11%. With any one investment with a 10% risk, the probability of losing money in any given year is 40%, almost 4 times as much.

What this all boils down to is the power of diversification in balancing risk. There is no great 1 best investment, but you are able to improve your return to risk by 5 times as much when diversifying across 15-20 good investments.

Since Bitcoin was created, it has shown to be an asset that is uncorrelated to the stock market. This provides investors with a tool for diversifying their portfolio, but many investors prefer to have more than one tool. Since Bitcoin thousands of altcoins have come onto the scene. Combining Bitcoin, all altcoins and all future projects has the resulting effect of an entirely new asset class: Digital Assets.

That begs the question: How does this relate to digital assets? You need only look at Bitcoin and the subsequent other similar coins found in the market to see the issue in diversifying your digital assets. Correlations within the crypto space are for the most part high, but there are a few different coins that break the mold of digital assets, which allows investors to diversify and improve their return to risk. One such token is Ampleforth, whose movement pattern in reality should have a much lower correlation to Bitcoin. For those who subscribe to modern portfolio theory and have a mindset like Ray Dalio, seeking out digital assets that don’t correlate strongly with Bitcoin may allow investors to improve their return to risk, while digital assets on the whole may help reduce correlation to other traditional holdings.

To learn more about modern portfolio theory and how it can apply to digital assets, check out our piece on the subject which you can find here.