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Algorand monetary experiment
A paper on the currency market of Algo
June 20, 2019
Arrington & Algorand officially authorized translation and supplement: Future brother
The English version of the original author: Ninos Mansor
Other contributions from: Michael Arrington, Ninor Mansor
Update: Previous versions of this document have been published using standard disclosure templates; this disclosure has been updated to more accurately reflect the expected nature of Arrington XRP Capital and its interest in the Algorand network.
Arrington XRP Capital and/or its affiliates (collectively \Arrington XRP Capital) have the economic benefits of Algo and are supporters of Algorand. Arrington XRP Capital will own Algos from the auction settlement on June 19, 2019. , the native token of the Algorand network.
As of the date of this report, Arrington XRP Capital, and others who contributed to the report, and those we share directly with the research, are supporters of Algorand and are willing to participate in the main network MainNet. Ways to get the benefits. All content in this report represents the opinion of Arrington XRP Capital. Arrington XRP Capital has obtained all the information here from sources they believe to be accurate and reliable. However, such information is provided "as is" and "there is no warranty of any kind, express or implied."
This document is for informational purposes only and is not an official confirmation of any transaction. All market prices, data and other information are not guaranteed to be complete or accurate, based on selected public market data and reflect current conditions and opinions of Arrington XRP Capital as of this date, all of which may be subject to change without notice. Notice.
Arrington XRP Capital is under no obligation to continue to provide reports on the project. The report was prepared on the dates indicated and may become unreliable due to subsequent market or economic conditions.
Any investment involves significant risks, including but not limited to pricing fluctuations, insufficient liquidity and the possibility of total loss of principal. This report only estimates the underlying value, represents the best effort estimate for the potential underlying valuation of a particular pass, and does not represent or imply an assessment of the quality of the pass, a summary of past performance or an investor's actionable investment strategy.
This document does not in any way constitute an offer or solicitation to buy or sell any investment or pass-through offer discussed herein.
The information contained in this document may include forward-looking statements or incorporate them by reference, and forward-looking statements include statements that are not statements of historical facts. These forward-looking statements may prove to be erroneous and may be subject to inaccurate assumptions or known or unknown risks, uncertainties and other factors, most of which are beyond the control of Arrington XRP Capital. Investors should conduct independent due diligence on all tokens discussed in this document with the assistance of professional financial, legal and tax experts and establish independent judgments in the relevant market before making any investment decisions.
Executive Summary Executive Summary
We explored the monetary experiment of the new cryptocurrency Algorand, invented by Turing Award winner Silvio Micali. Arrington XRP Capital will participate in the Algorand economy by running relay nodes and bidding in a Dutch auction at the Algorand Foundation.
Algorand combines cutting-edge cryptography with a clever economic model to guide the performance of the Algo money market. This is a new development that links censorship and technology to economic incentives that encourage effective market pricing.
The Algorand Foundation will distribute 30% of Algos through a down-protected Dutch auction. In this world, auctions are similar to monetary policy catalysts, not only to pass the certificate, but also to guide price discovery today and in the future. The smart part of the story is that any purchaser can return their Algos a year after purchase, giving them up to 90% down protection. This has a broad impact on Algo's market dynamics.
Algorand's currency experiment combines Silvio Micali's solution with the thirty-year challenge in distributed systems, drawing on foreign exchange (FX) trading, option pricing theory and traditional asset management. As these markets mature, we predict that Algo's behavior will be different from any other cryptocurrency today. It is not a stable currency; but a cryptocurrency, its economic model motivates financial markets to form rational expectations and seek a self-fulfilling equilibrium.
This downside protection clause has also opened up a new world for institutional investors, such as family offices or endowment funds, which have not yet entered the cryptocurrency market due to excessive downside risks. So the simple question for these investors and others who hold their cryptocurrency portfolio cash is: Why do you still have cash when you can hold Algos with downside protection and no obvious downside risk?
Algorand's economic experiments are unprecedented. This is where macroeconomics meets cryptocurrencies; we believe it will have a broad impact on cryptocurrency portfolio management, hedging and broader market dynamics.
table of Contents
Disclosure Disclosure. 2
Executive Summary Executive Summary. 3
1 cryptocurrency is a currency experiment… 5
2 Can the performance of digital currency be like a rational market? …. 6
3 Team and technology… 8
3.1 A life's work. 8
3.2 Management Team… 9
4.Algo market dynamics… 11
4.1 Internal Options… 11
4.3 Who will they face? … 13
4.4 Relay Nodes and Rewards… 13
5 Algo Auction is a monetary policy event… 15
6 Algo's killer DAPP: Smooth Waves Volatility. 16
7 Hedging downside risks, notes that fall into the ears of the organization… 17
8 Faith and Mobility: How about the time after the auction? …. 17
9 Conclusion: A strong and promising commitment… 19
1. The cryptocurrency is a currency experiment.
Bitcoin will be remembered as one of the greatest money experiments in human history. In the ashes of a financial crisis, a centennial bank collapse collapsed, and a pseudonym created a global currency for the world. This currency will soon inspire millions of people to rethink central banks and gold, not only on parabolic assets, but also on their economic worldview; a worldview of answers to savings, inflation and debt problems.
Bitcoin is both a currency experiment and a speculative wealth transfer. One day, economists will study the origins of Bitcoin as well as pearls and dollars. They dismantle bitcoin from cycle to disaster, from Tether's panic to hard-code catalysts such as Halvings. They will simulate an elegant supply curve and its austerity impact on investor time preferences. They will not see speculative bubbles, but profound macroeconomic experiments.
The world has already prepared for this experiment. Bitcoin has entered 11 years, and we have entered the 11 years of the global economic cycle. Whether it is quantifying QE (quantitative easing) easing, asset inflation, or trade and currency wars, economic anxiety will soon hang over central bank officials and the public. Heart. .
Which cryptocurrency will shine even more in this macroeconomic story? Thousands of projects have been launched online in the past few years, but how much is based on a real economy? Although investors often discuss encryption economics, the general economy, these ideas do not address cryptocurrency pricing and market dynamics. They are more like alchemy than monetary economics. Even the most mature and fluid smart contractual agreements like Ethereum are difficult to express economic vision, so the market is almost incomprehensible, not to mention effectively pricing these assets.
Bitcoin is simple: it is a fixed supply of assets, and its scarcity increases every four years. Today it is slowing inflation and will somehow become deflation. Its market cycle is centered on this potential economic policy (or lack thereof). Although the price of an asset is speculative, it is ultimately based on unchangeable currency characteristics, guiding its long-term economic trajectory.
For most other cryptocurrencies, including mature projects like Ethereum, it's hard to say the same thing. The 2016-18 market cycle has sparked a new wave of rhythm from Web3 to data privacy and has driven an exciting new technology boom. But how many of these stories and projects have a real economic foundation? Most narratives subtly draw on the wisdom of Silicon Valley, but unfortunately, it does not establish an economic foundation for the cryptocurrency market; pricing assets, forming the basis for anticipating and guiding monetary policy events.
2. Can the performance of digital currency be like a rational market?
Consider that most cryptocurrencies are highly related assets. Even a highly mobile digital currency like Ethereum is magically related to the bitcoin cycle. Most of the altcoin transactions are the elusive rhythm of the month.
Why is this? Because discovering and exploiting market inefficiencies is the lifeblood of any \rational market. This happens in crypto assets, but based on order flow and sentiment, these are the main major speculative. No model can use real economy. Data to price these assets makes it difficult for traders to find and exploit their underlying market inefficiencies.
Figure 1: The 90-day correlation matrix for the 250+ top cryptocurrency
Compare this with the foreign exchange market. Market transactions are expected of real economic variables such as interest rates and inflation. The game has rules, even if it is difficult to predict the outcome. When expectations deviate from reality, efficiency is reduced. However, in the short term, traders will hunt down these opportunities and squeeze out every penny for them to maintain market effectiveness. These markets are not perfect, but they have done quite well in maintaining economic stability.
For many years, cryptocurrency investors have discussed the theory of modeling the value of a protocol. Good or bad, these theories are not reliable in terms of short-term and long-term modeling of actual market dynamics. While these ideas fueled new narratives, these narratives were ultimately short-lived and did not help the market effectively price related assets. This makes Algo a new currency experiment.
The Algorand Foundation will distribute 30% of the Algo currency through a down-protected Dutch auction. The auction will inject 3 billion Algos into the market within five years, allowing participants to purchase Algos and choose to refund within one year of purchase. The extent of this downside protection depends on the clearing price as shown in Figure 2: above $1, buyers can return their Algos at 90% of the cost basis. Below $1, buyers can refund their Algos at a clearing price of 10 cents ($0.5 for $0.6, $0.3 for $0.4, etc.) 1
Figure 2. Algorand Foundation Refund Policy Management Algo Dutch Auction
One thing about these auctions is clear: they are more than just a naive way of distributing passes. The Algo auction is the first universal distribution to provide information on current and future price discoveries . These auctions are a drill for financial engineering and are the first attempt to lead a rational cryptocurrency market; not by speculative winds, but by self-fulfilling economic incentives.
3, team and technology
3.1 A life's work
In this article, we focus on Algorand's economic model, but there is one obvious point in the whole discussion. If there is no deep belief, economics does not matter. The fate of Algo's auction depends on the belief of the market, not just because of its incentives, but about the technical credibility and long-term vision of the project. This is why even in a purely monetary policy discussion, we will first unlock the origin story and technical contributions of the project.
Algorand is the brainchild of Silvio Micali, a cryptographer for Italian computer scientists and MIT for more than 30 years. Silvio won the Turing Award in 2012, the highest award in all computer sciences (known as the Nobel Prize in the computer world). One of his inventions was the Verifiable Random Function (VRF) of 1999, which he has now become the cornerstone of cryptography for Algorand competitor Dfinity. He also co-invented the zero-knowledge proofs 3 , an important encryption primitive in the privacy field.
Silvio invented Algorand as a solution to the Byzantine General Problem 4 . This is the challenge that any distributed system is facing: how does the system reach consensus in front of unknown opponents? Before Algorand, there were two broad answers, two consensus genres. The first was born in the 1970s, and the second was born after the bankruptcy of Lehman Brothers : Classic Byzantine Fault Tolerance (BFT) and Nakamoto Consensus (NC).
Each solution solves the Byzantine dilemma but needs to weigh the pros and cons. The BFT algorithm has high throughput, deterministic finality and low latency, but they sacrifice decentralization. The NC Consensus encourages decentralization, but at the expense of throughput and the ultimate sacrifice of probability. These trade-offs ultimately mean the so-called “ blockchain is unlikely to be a triangular dilemma” . For example, blockchains can be fast and secure, but not decentralized; safe and decentralized, but not fast.
Algorand completely overturned the idea and captured the best of the two worlds by a consensus algorithm that combines the two properties of BFT and NC. The protocol is a very intuitive VRF application:
1. Through the application of VRF, 1000 network participants randomly select the subcommittee of the node to vote on the next block. This is called \ Cryptographic Sortition"
2. These selected nodes agree to the next block by the Byzantine protocol, which is a very fast iteration of the classic BFT.
The idea is simple, but the result is groundbreaking. A consensus is quickly reached in the BFT algorithm, and the random node selection scales the verifier count to numbers that are only seen in networks using NC, such as bitcoin. The verifiable randomness of the core of the agreement ensures that voters can never predict in advance. This produces very powerful results: security similar to PoW, without the costly cost of capturing both sides of a distributed system. As a result, Algorand solved this problem and produced a network with fast end, high throughput, low latency and decentralization. Comparing BFT and NC with Algorand, Table 1 illustrates this technological breakthrough.
|parameter||Classic BFT fault tolerance||Nakamoto Consensus||Algorand PPoS|
|Network settings||Licensing||No license required||No license required|
|Finality Finality||Deterministic certainty (<1m)||Probabilistic probability (>50m)||Probabilistic probability (5s)|
|Scalability (node)||Low(<100)||High (thousands)||High (thousands)|
|Extensibility (Clients)||High (thousands)||High (thousands)||High (thousands)|
|Performance (transaction speed)||High(1000+TPS)||Low (3-10 TPS)||High (thousands)|
|Fault tolerant hostile voting rights||33%||51%||33%|
|Network synchronization hypothesis||Synchronous Synchoonous||Asynchronous Asynchronous||Partial synchronization|
Table 1: Comparison of BFT, Nakamoto Consensus and Algorand Consensus Mechanism
Finally, this discussion elaborates on the simple concept of the origin of Algorand. We believe that this project is not only the life work of the Turing Award winners, but also the crystallization of the difficult computer science problems in the past 30 years.
One of Algarand's most unique aspects is the diversity of the team, complementing its computer science origins through economic and business expertise. Silvio and his team of scientists also joined economists focused on macroeconomics and exchange rate theory , as well as pragmatic and experienced executives building large technology companies. It sounds too good to be true, but in reality these are the first elements that cryptocurrencies need to really achieve: technology, economy and commerce.
The economics team is led by chief economist Pablo Azar, who is also a scholar at the Massachusetts Institute of Technology. Azar's background is a rare cross-section in both academia and cryptography: he holds a dual degree in macroeconomics and computer science . His work combines market dynamics, software engineering and currency systems. The most cited paper by Azar is Momentum, Mean-Reversion and Social Media: evidence from StockTwits and Twitter 7 to study the relationship between social media and currency shocks.
As a complement to Pablo's leadership, Algorand has a number of economic advisors focused on macroeconomics, central bank and institutional finance. One of Algorand's economic advisors is Kenneth Rogoff, the world's leading macroeconomist, who served as IMF's chief economist between 2001 and 2003 . Rogoff is known for his highly quoted exchange rate theory and the contribution of the central bank’s independence.
Along with Rogoff, there are several other high-profile economic advisers, including Andrew Lo and Joseph Naggar. Lo is a professor at the Massachusetts Institute of Technology's Sloan School of Business and the founder of a Boston Quantitative Company called AlphaSimplex Group 9 . He also holds a Ph.D. in Economics from Harvard University and previously served as a Round Table member of the Federal Reserve Bank of New York.
Naggar complements Rogoff and Lo's honours and focuses on institutional finance. He is a partner in a multi-billion dollar asset management company called GoldenTree 10 . Naggar is also an alumnus of the Massachusetts Institute of Technology who has worked in fixed income risk management for companies such as Merryl Lynch and Morgan Stanley for more than 20 years.
Algorand's research foundation in computer science and economics is brought together by a strong business team. Equally impressive is that before the blockchain, their names appeared in the leadership of senior technology entrepreneurs. After announcing its $62 million stake in Union Square Ventures 11 , Algorand welcomed Steve Kokinos as CEO. Steve is the founder and CEO of Fuze, an enterprise-class cloud communications company backed by venture capital firms such as Bessemer Partners 12 . Steve has enabled the company to operate more than 500 employees.
Joining Steve to lead Algorand's business strategy is also the chief operating officer of Sean Ford 13 . Sean is also an experienced technical lead and has a long list of C-level operations, including CMO, one of the world's top 10 listed SaaS companies, LogMeIn.
4, Algo market dynamics
In this section, we interpret the market dynamics behind the auction and focus our analysis on the financial instruments in the process. We first open an auction in a vacuum and then apply this logic to several. Finally, we analyze the game steps between auction buyers and other secondary players such as speculators and relay nodes.
The downside protection clause is actually a put option that sells Algos back to the foundation within one year of purchase. This is an economic tool that has been carefully designed at the auction. The ability to return Algos and reduce downside risk means that auctions are not just a way for long-term holdings of Algos, but rather risk management, hedging and market making. In the medium term, these incentives can guide price discovery and help secondary markets find effective prices.
If Participant A purchases 1,000 Algos at a clearing price of $2, they are now hedged with a 90% exposure. Regardless of how the temporary price changes, they have the right to sell 1,000 Algos back to the Foundation for $1.80 in 365 days. This downside protection is an alternative: participants do not need to return the same "Algos". As long as they have Algos on the 365 day refund date after the auction, they can make a transaction and request a refund. (Future PS is free to buy and sell in the secondary market, but the total amount is fixed. That is to join you to auction 1000 Algos. You can make a lot of money through God-like operation. In the end, you can still refund 1000 Algos, or you can sell it. 1000, bought back 1000 during the validity period, you can also retire.)
So, considering all of this, what will auction participants do after purchasing these coins? This obviously depends on why they bought them first – speculative high-frequency traders high frequency trader (HFT) looking for low-risk deals, while down-sensitive traders can also hold without the notorious 85% drop. There is Algo Pass. Everything else is equal, regardless of motivation, let us call Participant A Bob and think about his reward after his successful bid:
1. Algo exceeds his clearing price : If the price trades over $2 after Bob's bid, he can sell his Algo and book these \low risk "revenues or continue to hold them. If he decides to sell, he still holds The right to get a refund on day 365, but if he wants to apply, he needs to buy back his Algos.
2. Algos exceeds his clearing price: then falls below his clearing price: if Bob sells $3 on the 30th day, but Algos then trades below $1.80 on the 300th day – then to 90c – Bob is motivated After repurchasing his Algos and 65 days later, Algos was sold to the Foundation for $1.80. He conducted a "risk-free" deal. In this world, Bob is now a market maker with a mental algorithm to guide his decision. As he approached the 365th day, the urge to re-purchase Algos is growing.
3. Algos is below his liquidation price: If Bob never sells his Algos and the price falls below $1.80, he will not lose more than 10% of the loss. Since he has revealed his preference for downside protection when bidding at auction, Bob will continue to hold
|To sum up: 1. According to his strategy, Bob may or may not choose to sell at more than $2. 2. Bob is encouraged to repurchase Algos below $1.80, and with nearly 365 days, this incentive will also strengthen|
3. If his Algos trading price is less than $1.80, Bob may hold
One way to imagine these auctions is that each participant has its own "basic" price below which they act as holders or bookings and have the urge to re-purchase. Everyone has their own price, and everyone is a provider of liquidity. In fact, each auction is a game that invites participants to form their own price floor, regardless of the subsequent secondary market activity. Each of these auctions creates a layer of purchasers that have been motivated to participate in the Algo market (by repurchasing or holding) from day 1 until day 365.
This is an auction game. Therefore, if the auction lasts for five years, then you can imagine that the actual auction price floor is the cumulative sum of the price floor limits for each auction. As the clearing of the next auction, we add it to the model. Auctions need to be weighted according to the number of Algos sold since the auction, and the auction will have more impact and have a greater impact on market prices. For the sake of simplicity, let us assume that the price is higher than $1.
Here A n = the number of Algos sold in Auction n
P n = the final price of the Algo settled in Auction n
P average = Algos average benchmark price to Auction n
Let us look at an example. The auction rounded off 25 million Algo for $4, the auction 2 rounds to settle 50 million Algo for $3, and the auction for 3 rounds to settle 50 million Algo for $3.50. How do market participants consider the lower price limit based on the auction when simulating three auctions?
Assuming the auction price is the market price, Algos' effective reserve price is $3.06. As the economist said, this is the same as other conditions; everything is equal.
Like most things in economics, everything else is different. So far, we assume that the pass in circulation is only the certificate of the auction. We also assume that repurchasers will not face opportunity costs.
These are more complex considerations that will play a role in the actual market price of Algos. When we think about the next puzzle, it all becomes very interesting: speculators
The buyers of the auction play a game together, which in theory creates a reserve price for the total token of the auction over time. These participants have their own reference prices to determine if Algos is overvalued or undervalued. Everyone is a market maker in the Algo currency world.
This is where it becomes interesting: speculators should now enter the market by piece together the information and beat the auction participants to the line. This is where real liquidity providers see opportunities; expecting to start stirring the wheels of an efficient market, Algos deals more like foreign exchange pairs than smart contract agreements like ETH or EOS. (Future Personal PS Effective Market Hypothesis is a classic hypothesis in finance. He believes that Mr. Market will automatically correct overestimation and underestimation so that the current price is already showing the objective and real value of the product, but the actual situation is that it is effective. The market hypothesis is not so accurate)
First, smart traders will go all out. If the auction provides real economic data telling us the effective price of Algo, then any deviations are now traded. You can imagine the market \ wrong pricing "Algos and the USDT market are often the same in a short-term 1:1 failure. Although market panic and retail traders read articles about the upcoming USDT liquidity contraction, the USDT temporarily fluctuated. But smart money holders realize that the world may not end at all, and use false temporary panic to get all the USDTs they can get for less than $1.
Equally interesting, you can imagine HFT building an economic model to price Algos, creating a “catalyst” schedule to “track the refund date and the associated price bottom line. These models will be based entirely on mathematics to calculate the reasonable price of Algos. As the Algos market matures, these models will mature, pricing inefficient and fluctuating over time. For example, as demand should increase to 365 days, the closer we are to the refund date, the likelihood that these models will be priced among auction participants The greater the sex – the purchase, which drives the market to equilibrium.
Thanks to these speculators, you can see how this all becomes a self-fulfilling prophecy. Regardless of the behavior of the actual auction participants, the market can find reasonable prices for Algos. There is even reflexiveness in the incentives of auction participants; they now have a stronger incentive to achieve equilibrium because they face direct competition from speculators who are observing their every move.
The above two sections describe how market price Algos forms expectations based solely on auction data. However, this analysis suggests that these auctions and speculators are in a vacuum. The reality is that price generation and pricing will be a wave of dance between the auction and the secondary market. The latter is not only known through auctions, but also enters circulation through relay nodes and rewards. As shown in Figure 3, the relay node will reach 2.5 billion Algos 14 in two to five years.
The short answer is that no one can predict what this will do. Note that the relay node cannot access the put option, which produces a lower psychological price limit and liquidity incentives. Will relay node inflation undermine auction game theory? Or the auction will provide firm expectations for speculators, especially when the number of auction passes begins to exceed the relay node pass in circulation?
The behavior of the relay node is more difficult to predict than the behavior of the auction participants. They have other incentives that we can't model. Some of them may want to hold their Algos for five years 14; others may want to sell them regularly on a regular basis.
It is almost impossible to understand who they are or what they want to achieve, and all the intentions and intentions that actually come out. For this reason, speculators are likely to adjust their strategies over time based on the true behavior of these participants, and when they feel how relay nodes participate in this rhythm, they will become more or less radical. Or depression.
Figure 3. Project Algo Pass 5 Year Circulation Chart
5. Algo Auction is a monetary policy event
Once a month, the Fed announced a change in interest rate policy. A group of economists and the Federal Open Market Committee (FOMC) 15 decided whether interest rates should be changed. In anticipation, the market is expected to be loose or tight; experts argue that if the Fed is a hard-line or dovish, traders have a price-aware flow effect. This process takes place on a global stage, with dozens of central banks simultaneously modifying monetary policy, and the global money market responds at the same time.
Every time Algo Dutch auctions are a catalyst for monetary policy. The economic data disclosed in the auction leads the money market. Each auction is like a FOMC meeting, except that it is not run by a closed PhD team, but an open network of participants expressing the need for falling-protected Algos. Algo put is Algorand's monetary policy; this is Greenspan put's policy for decentralized capital investment. If the Algo market matures, you can even imagine that the market will be priced in the expected clearing price of the next auction, and speculators bet on future demand based on their perception of Algorand's technology, community and market perception.
When speculators are optimistic, they expect future liquidation prices to be higher. When pessimistic, they expect future liquidation prices to be lower. When the auction is liquidated and the real bid is entered, we will find out whether the market is right or wrong. As we all know, investors are not performing well in predicting the Fed's next move, and we suspect that this will not change, even if the central bank is decentralized. In the end, these speculators are betting on Algo, just as they bet ETH, but this speculation is related to the basic economic policy of the agreement. With the advent of real data, there is a way for the market to prove whether they are right or wrong.
The Algo money market is linked to the actual, regular phased monetary catalyst. The market price is a consolidated merger of future clearing prices, the total price limit determined by the cumulative auction, and the expected supply and demand sources of the relay nodes and speculators. Over time, as the market matures, this will create a fluid but reliable process to price the Algo currency.
6, Algo's killer DAPP: smooth fluctuations Smoothing Volatility
Algo is not a stable currency. Especially in the early days, it may trade with great volatility like most cryptocurrencies. However, with the development of the currency experiment, the market will fine-tune this process. We have described above that the rhythm and style of dance have become clearer and clearer over time; the market has gradually formed a unified consensus. The consensus they form is not about what Algo's price should be, short-term underestimation or low efficiency will always exist – but about how to auction, relay nodes and speculators between games. As speculators better understand the process over time, the market will continue to mature.
If the market can find a consensus, Algos will trade in a completely different way than any other cryptocurrency. This will not eliminate volatility; but the Algo economic experiment will show smooth price volatility, just as the free floating exchange rate 16 helps the domestic currency absorb economic shocks.
This is where the Algo money market eventually looks more like an FX pair than a deal. Domestic currencies like the Australian dollar will have price fluctuation terms in the short and long term. Despite this, the volatility curve of the Australian dollar is relatively stable. Market forces know how to price expectations through tangible economic information. Speculators fluctuate smoothly. Until a black swan wiped out the Australian dollar overnight, we didn't have many days to wake up, and the Australian dollar fell by 10% in the intraday or even in the month.
As a result, Algorand will be the first local cryptocurrency and compete with Ethereum as the world's DAPP construction developer with a smooth volatility curve. This opens the door to a whole new world and applications that are not very viable in traditional areas.
A calmer ebb and flow can make the Algorand platform superior to its competitors, and its economy is hampered by wild fluctuations. Algo may look like CAD, while ETH behaves like PESO, up and down. If these pricing mechanisms work, Algo may slowly become an irrelevant asset whose market price is affected by these internal currency catalysts rather than market trends. This is the killer DAPP of Algorand.
7. Hedging the downside risk, the notes that float into the ear of the organization
These Algo puts also have a significant impact on cryptocurrency asset management and institutional investment. Asset managers can now get long-term cryptocurrencies through Algos, while still maintaining the risk of a large-scale decline in the notorious cryptocurrency.
This may not be as interesting for retail investors or just a lot of crypto funds, as they are more sensitive to the potential opportunity cost of holding Algo. On the other hand, these Dutch auctions are a good thing for large institutional investors who think carefully about risk management and hedging.
If you are a new endowment fund, hedge fund or family office looking for cryptocurrency investment feasibility |, when you can hold Algo, get income, and fall protection hedge, why do you still have cash?
As you can imagine, Algos is the primary tool for portfolio and risk management, especially as the organization's AUM (asset management scale) grows. This is the first time that a native cryptocurrency has become a native hedging tool. More mature investors will enter the field, seeing the Algo currency as a very convenient way to gain the exposure of the rising potential advantage of innovative projects, while hedging limits its downside.
8. Faith and Mobility: How about the time after the auction?
The beauty of the Algo experiment is that it guides the most difficult currency for any monetary system: belief and mobility. Each financial system relies on the beliefs of the participants and the fluidity that proves this belief. Beliefs are the energy of the system, whether it is fiat money or bitcoin; and mobility allows us to live.
Algorand's economic experiments aim to guide liquidity in the early stages of the most difficult to build. Combining the distribution of certificates with the lessons of foreign exchange transactions and monetary economics, combined with the distribution of certificates, allows the Algo market to guide the most important elements of the long-lasting vitality of any cryptocurrency.
But there is an imminent problem that hangs over this model. What happens after puts expires? If puts creates a game theory that motivates self-realization equilibrium, what happens when they disappear?
A monthly auction means that the expiration takes place on a rolling basis. As the old model expires, new buyers have just entered the market. However, at some point, it is important that the party stops or has actually slowed down too much.
In the end, the incentives are exhausted. Will economic magic end? This is Algorand's Day 365 issue. This is a very interesting hypothesis that has little to do with the next few years, but the answer is very important. Ultimately, living after “choice” “returns to the fundamentals of the web. The Algorand team and foundation will have a five-year auction that will drive the self-fulfilling currency market. Can they build real economic value during this period? The questions are: By the time the final put option expires, the Algo currency is actually a medium of exchange (MoE) and a value store of value (SoV) that goes beyond complex network balance hunting speculators?
In the context of a broad economic outlook, downside protection may be more important than we think. We believe that the long-term success of an experiment ultimately depends on the team's ability to achieve true network value. They need to achieve what they call a "borderless economy." “What is the actual GDP at the end of the experiment? What is the application of this network imagination, and how much economic value does it represent?
Before the launch of the network, we have seen hints of this strategy. Algorand has so far announced four ecosystem partners. One of them is OTOY 17 , an award-winning cloud graphics company that plans to introduce high-end GPU rendering services on Algorand. Another announcement partner is Syncsort 18 , a big data company focused on the enterprise with more than 800 employees. We will pay close attention to how these partnerships have evolved over time and how they fit into the broader field of the Algorand ecosystem.
One of the most important indicators for determining monetary value after the expiration of the bearish period is network decentralization. Economic management will be needed early, but the Algo currency and network are ultimately decoupled from the foundation? As we see in Bitcoin, it needs its own life.
On the other hand, we may ask the wrong question. Maybe this problem already has a smart currency solution. With a world-class team of macroeconomists, we probably didn't think of Algorand's 365-day question. We will pay close attention to whether the Foundation will release the long-term economic roadmap for Algo monetary policy to resolve economic policies after the auction ends.
The last point to consider is the foundation's cash reserve on day 365. After years of auctions, the Foundation will have a very large cash position on its balance sheet, so it has the flexibility to apply new currency pressures to support the Algo market. The Foundation takes strict governance measures on the funds themselves, segregating bank accounts and providing a factual audit every quarter19, pointing out this possibility.
What will this monetary policy evolve like? One thing is clear: these auctions are not just for raising a lot of money. They are not EOS-style fundraiser 20 , but a way to develop real economic policies. Therefore, it is reasonable to reserve Reserves to play an important role in long-term economic stability. We will pay close attention to the official position of the Foundation.
9. Conclusion: A strong and promising commitment
Algorand's economic experiment is the first in the same type of public chain. Led by an impressive group of macroeconomists, Algo Auctions is the first symbolic distribution associated with an economic model that inspires rational and balanced markets. More similar to foreign exchange rather than speculative utility, the behavior of the Algo market does not work in any other cryptocurrency market.
However, this experiment does not apply to any project. These auctions are ultimately designed to build faith and guide the currency, but the market needs to believe in the underlying technology, the vision and values of the project.
This high quality team and technical level is suitable for Algo's market dynamics. In addition to economics, the Algorand project represents the lifelong career of Silvio Micali as a cryptographer and Turing Award winner, and represents a challenge that has plagued distributed systems for more than three decades.
We are very happy to see this experiment unfold and participate in Algorand's economy, and more importantly, support a smart and creative team. In addition, we are pleased to see that Algorand's originality has inspired new projects to rethink monetary policy and apply new creative macroeconomic concepts to its agreements.
3 https://en.wikipedia.org/wiki/Zero-knowledge_proof Leslie Lamport, Robert Shostak, and Marshall Pease. The Byzantine Generals Problem . SRI International, 1982.
5 Marko Vukolic. The Quest for Scalable Blockchain Fabric: Proof-of-Work vs. BFT Replication . IBM Research, 2015.url: https://allquantor.at/blockchainbib/pdf/vukolic2015quest.pdf.
6 Vukolic, The Quest for Scalable Blockchain Fabric: Proof-of-Work vs. BFT Replication .
7 Pablo Azar et al. Momentum, Mean-Reversion, and Social Media: Evidence from StockTwits and Twitter . The Journal of Portfolio Management, 2018. url: https://jpm.iijournals.com/content/44/7/85.
16 http : / / www .economicsdiscussion . net / international – trade / finance / floating – exchange – rates -advantages-and-disadvantages-currencies/26267.
20 https://www.cnbc.com/2018/05/31/a- blockchain- start-up- just- raised- 4-GDP- without- a- liveproduct.html
▌ Author: Future little brother (the same name as the public number)