Artificial Intelligence, Law and Finance
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Economy Monitor Guide to Smart Contracts
Blockchain Examples
by Percy Venegas
Part 1 of the Artificial Intelligence, Law and Finance series
Although the interest around smart contracts is generally defined in a narrow way, centered in applications terms such as Bitcoin contracts, Ethereum contracts or Smart Contracts Bitcoin, or even just in technical trading aspects such as Ethereum price, in reality the field is more diverse. A number of companies and nonprofit organizations are serving governments, institutional and private clients implementing distributed ledger technology. In this accessible book, we present the detailed corporate profile of several smart contracts companies, their trading and social network volumes, and provide a gentle introduction to smart contracts examples. ECONOMY MONITOR Guide to SMART CONTRACTS offers a demonstrably effective way to diversify risk when investing in cryptocurrency securities by focusing on companies that are offering products with actual demand in the real economy. The book is also useful for managers seeking to learn about vendors of fintech, blockchain, and computable contracts technology.
Inside this book:
I Companies
(Corporate profile, Funding, Team, Clients, Leverage points, Regulatory compliance information)
Interbit (BTL)
Symbiont
Counterparty
Lisk
BitShares
R3CEV
Ripple
Ethereum
Stellar
Chain
Clearmatics
II Social Signals
What is breakdown of followers and influence by twitter handle?
What is the trend of the number of Tweets over Day?
What is the trend of author favorite count over month?
What is the contribution of Retweet count over month by Sentiment?
What is the breakdown of sentiment negative signals?
What are the values of author friend count by country?
III Appendix
Examples (Programming smart contracts)
About Consensus
About the author
Percy Venegas is a former Intel engineer, co-founder of Economy Monitor, and member of the founding advisory board of the Social Venture Capital Conference, Latin America, Caribbean and South Florida.
He has published in journals such as International Advances in Economic Research and Financial Assets and Investing, and more recently he has been a speaker on the topic of Trust-less Crypto Markets at the Cambridge Centre for Risk Studies Seminars.
Percy holds an MBA in International Business from MIB School of Management in Trieste, Italy. He attended the MIT Sloan China Program, Lingnan University College at Sun Yat Sen University in Guangzhou, and earned an Executive Master in Sustainable Development and Corporate Responsibility from EOI Business School, Campus Universidad Complutense de Madrid. He's also lived in New York and is currently based in Costa Rica.
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Ethereum Price Prediction
The Value Investor's Guide
by Percy Venegas
Part 2 of the Artificial Intelligence, Law and Finance series
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 a 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.
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