Ethereum Price Prediction

The Value Investor's Guide

Percy Venegas

• Publisher: EconomyMonitor.com
• eBook ISBN: 9781537858449
• Topic: Business
• Subtopic: E-Commerce
• Index: Business

Can the price direction of Ethereum be predicted for periods of days, using non-financial measurements of demand, to facilitate hedging against emerging financial risks?

On July 25th 2017 the SEC published guidance indicating that US securities laws may apply to token sales, effectively recognizing crypto coins associated with entities such as the DAO as a new asset class. In Mutual Distributed Ledgers, or Blockchains, trust is embedded and no explicit chain of trust is necessary. Smart contracts running on a Blockchain allow to create objects with various degrees of liquidity and to automate the operations of a fund, enabling trustless crypto markets.

However unpredictable the price of financial instruments (including cryptocurrencies) might be, what lies at the heart of the issue is a matter of demand-side economics: the coders who contribute to the public project, the ones who develop decentralised applications on the Ethereum blockchain, and those who peruse knowledge of the development community for private projects, all are suppliers of technology –but consumers of Ethereum related-content. Likewise, the miners who validate transactions are suppliers to the ecosystem (they create Ether, the fuel of the Ethereum blockchain), but consume information about mining pools, mining calculators, and the like. Finally, end-users signal demand by using wallets, exchanges, and retailers that accept ETH as a payment method. Investors looking for Ethereum price predictions in 2017, 2018, 2020 or 2030 will therefore benefit from approaching the subject with a demand economics mindset. This approach is not confined to managers: counsels and other trusted advisors can benefit from the insights provided by simple models based on mainstream economic concepts (with no need for a trained data scientist). Finally, the possibility of predicting a seemingly unpredictable thing -the price of a crypto security- within knowable error margins and defined time frames, not only offers opportunities for value, but provides an useful risk management tool.

Contents:

*Ethereum Price Prediction: What matters in the long term?

*Expanding the Ethereum price model

-Ethereum wallet online

-Ethereum wallet download

-Ethereum mining

-Ethereum mining rig

-Ethereum classic

-Ethereum Dapp

-Ethereum investing

-Ethereum ICO funders selloffs

-Ethereum whales

-Ethereum trading

-Ethereum CFD

-Ethereum news

-Ethereum going down

-Ethereum coin

-What is Ethereum coin?

-Bitcoin's scaling deadlock

-Ethereum tokens

-Ethereum Name Service

-Ethereum risk

Resources

-Ethereum wallets (Russian, Italian, Arabic, French, Spanish, Dutch). Hardware wallets

-How/where to buy ether (ethereum coin)

--Buy Ethereum in Australia

--Buy Ethereum in India

--Buy Ethereum in Canada

--Buy Ethereum in France

--Buy Ethereum with Credit Card

--Buy Ethereum with Paypal

Implementation of Price Analytics at Scale

Appendix: Initial Coin Offering (ICOs) in Blockchain Trustless crypto-markets

-Appendix to the paper: a brief history of The DAO

APPENDIX: INITIAL COIN OFFERING (ICOS) IN BLOCKCHAIN TRUSTLESS CRYPTO-MARKETS

Percy Venegas ([email protected])

Economy Monitor

Abstract

On July 25^th 2017 the SEC published guidance indicating that US securities laws may apply to token sales, effectively recognizing crypto coins associated with entities such as the DAO as a new asset class. In Mutual Distributed Ledgers, or Blockchains, trust is embedded and no explicit chain of trust is necessary. Smart contracts running on a Blockchain allow to create objects with various degrees of liquidity and to automate the operations of a fund, enabling trustless crypto markets. Despite great promise, the sources of uncertainty and risk in such trustless settings are not yet well understood; for instance “The DAO” (Decentralised Autonomous Organisation), which was the world’s first decentralised investment fund, went from being the largest crowdfunding event in history to get about a third of its assets compromised due to an attack from a shareholder. The dual nature of money shared by a Blockchain calls for a novel approach: a DAO is a listed entity by default, and its projects might be financial instruments as well, so we use network correlations to study portfolio risk diversification. Furthermore, automated corporations are essentially about decentralized intelligence, so we need to consider the strategic nature of the social world; for this we map the vector field and use signal processing to investigate volatility in traffic flows. The primary objective of the study is to determine factors that affect cash flows in decentralized applications, to enhance the understanding on whether decentralized organizations are perceived as truly “trustless entities”, or, if investors are rather forced to “trust in the design”. The target audiences of this paper are Government regulatory authorities, Banking sector and Stock markets.

Keywords: Blockchain, Smart Contracts, Econophysics, Behavioral Finance, Fields Finance.

JEL Codes: G02, G32, G18, G21, G23

“The term money has two very different meanings in popular discourse. We often speak of someone “making money,” when we really mean that he or she is receiving an income...In this use, money is a synonym for income or receipts; it refers to a flow... We also speak of someone’s having money in his or her pocket or in a safe-deposit box or on deposit at a bank. In that use, money refers to an asset”

-Milton Friedman

“…although we usually assume there is a sharp line of distinction between what is money and what is not-and the law generally tries to make such a distinction- so far as the causal effects of monetary events are concerned, there is no such clear difference. What we find is rather a continuum in which objects of various degrees of liquidity, or with values which can fluctuate independently of each other, shade into each other in the degree to which they function as money”

-F.A Hayek

Introduction

In essence, money is a system of trust: we believe on the belief of others. Money also has two functions: facilitate transaction flows (as a currency), and, store value (as an asset). Until the introduction of peer-to-peer technologies in the practice of finance, a centralized banking system and the rule of law could instrumentalized these principles; today with Blockchain we face with a landscape in flux, underpinned by both uncertainty and dynamism. At the core is the issue of trust convertibility: in a decentralized system that can execute both transactions and contracts, in principle, trust is not needed.

From a banker’s perspective, the problem with crypto currencies is not having insight into cashflows, which is needed if one wants to both take deposits and lend -cashflow performance equals credit worthiness. In this sense, banks have a competitive advantage over crowdfunding and other decentralised innovations, including Bitcoin (Dimon, 2016). Nevertheless, regular cash payments can be programmed into a Blockchain as an added protocol layer (Wyatt, 2014), with start-ups such as 21.co providing software that turns any computer into a Bitcoin Computer (Popper, 2016). Online communities are creating fully programmatic organizations following an open source software approach, such entities can be seen as the prototypical example of a new organisational paradigm: the ‘Decentralised Autonomous Corporation’; which is owned and operated by its workforce (Colony Foundation, 2016), is publicly traded by default, and distributes equity to itself on a constant and ongoing basis in direct proportion to the value each member of its workforce has contributed. The substrate for such organizations is provided by open source Blockchains as Ethereum (Buterin, 2014), which incentivizes computer users to run software programs distributed on its network, in essence, creating a global, single computer capable of executing any type of computation (what is known as a Turing complete, decentralized computer), transacting on its own currency, Ether (du Rose, 2016). One of the first decentralized organizations of this type is “The DAO”, was the world’s first decentralised investment fund: A smart contract based investment club where the Ether used to purchase DAO tokens could be used to finance proposals made to it. The DAO token holders could then vote on whether to accept each proposal (du Rose, 2016). In other words, The DAO was a hybrid of crowdfunding and investment fund.

Ethereum, and in general, decentralized organizations, are not without trouble. The DAO, the code-based and leaderless investment vehicle that crowd-funded a record-breaking 150 million USD worth of ether, was unexpectedly drowned by an unknown user at the end of June 2016, just a few days after its successful funding round closed. About a third of all invested Ether, around 4% of the total Ether supply (worth about $55m at the time of the attack), was waiting until it could be withdrawn –due to security safeguards, funds could not be withdrawn immediately. However, several other attacks followed, highlighting the fallibility of human design: on programmatic agreements, implicitly the market participants have to trust in both the system design and the consensus mechanism. This means that additional degrees of automation not necessarily translate into freedom from decision-making: at some point the community has to consider tradeoffs (is the attack theft, despite being permitted by the code? Can the organization lawfully alter an immutable Blockchain to recover funds?). Moreover, the fact that initial coin offering (for The DAO tokens) generated much enthusiasm and was allowed to go beyond the $500k initial target, possibly raising conflicts of interest, underlines the weaknesses that such organizations will have to overcome (van Wirdum, 2016). As of July 27^th 2016, only one Ethereum startup was listed as having received more than one million dollars in funding (Crunchbase, 2016).

In this paper we will study factors that affect cash flows in decentralized applications. We will study cost, risk and value from various points of view and on a real The DAO portfolio, using traditional analysis artifacts and also introducing novel techniques, perhaps better suited for the “in flux” conditions of the decentralised economy –and more broadly, the digital economy.

Literature

Key concepts

Cost and Value

One of the most widely used valuation methods among crypto currency professionals is pure technical analysis (e.g. historical price) and correlation analysis (e.g. correlations to stocks, gold, fiat currencies). Figure 1 shows the market capitalization of Ethereum (Wyatt, 2014), and Figure 2 shows The DAO market cap on July 2016.

Figure 1. Ethereum Market Cap . Source: CoinMarketCap

Figure 2. The DAO Market Cap. Source: CoinMarketCap

As we can see, Ethereum gained strong market validation around April 2016, when the market capitalization of Ether (ETH) first reached the $1B mark -or 1/7 of Bitcoin’s (BTC) market cap at that time, to position itself as a viable currencyto diversify on. However, the exchanges can only inform a partial appreciation of value, and most importantly, of risk. As a sign of the volatility of such emerging technology, a large portion of that value was erased on June 17^th soon after ETH surpassed the $1.5B market cap, amidst a spike on trading volume due to the attack on The DAO. On July 20^th an Ethereum hard fork was implemented, effectively bailing out The DAO and removing all tokens from circulation. Such dramatic chain of events provides an ideal setting to prove the various approaches we are investigating in this paper.

A way of thinking about fair value is to focus only on the medium of exchange role of crypto currencies: recognizing the potential value of the technology of trustless exchange, but also incorporating some of the risks. Using Bitcoin as an example, Blundell (Blundell-Wignall, 2014) proposes the following approach: Let M reflect the (constant) electricity, hardware time and human capital cost of mining a Bitcoin (that is, solving the underlying cryptography problem to discover new blocks, for which crypto currency is itself awarded as a reward), and ε be a random add-on to that cost depending on the degree of difficulty of the algorithm at the time, random ‘luck’ and other one-off factors. This is the underlying value to which market prices should gravitate, with the mining supply of Bitcoin rising or falling in response to whether the market price sits above or below it – provided of course that the crypto-currency is always ‘acceptable’ with no risk of being worthless due to: fraud, a better substitute coming...

Table of contents

• Ethereum Price Prediction: What matters in the long term? : Introduction
• Expanding the Ethereum price model: Ethereum wallet online
• Appendix: Initial Coin Offering (ICOs) in Blockchain Trustless crypto-markets
• About the author
• More by Percy Venegas