2018中国区块链投资机构20强 2018年6⽉12⽇
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IOTA: a Cryptographic Perspective
IOTA: A Cryptographic Perspective Bryan Baek Jason Lin Harvard University Georgia Institute of Technology [email protected] [email protected] 1 Introduction IOTA is an open-source distributed ledger protocol that presents a unique juxtaposition to the blockchain-based Bitcoin. Instead of using the traditional blockchain approach, IOTA stores individual transactions in a directed-acyclic graph (DAG) called Tangle. IOTA claims that this allows several benefits over its blockchain-based predecessors such as quantum-proof properties, no transaction fees, fast transactions, secure data transfer, and infinite scalability. Currently standing at 16th place in the CoinMarketCap, it topped 7 during the height of the bullish period of late 2017. Given these claims and attractions, this paper seeks to analyze the benefits and how they create vulnerabilities and/or disadvantages compared to the standard blockchain approach. Based upon our findings, we will discuss the future of IOTA and its potential of being a viable competitor to blockchain technology for transactions. 2 Background IOTA, which stands for Internet of Things Application [1], is a crypto technology in the form of a distributed ledger that facilitates transactions between Internet of Things (IoT) devices. IoT encompass smart home devices, cameras, sensors, and other devices that monitor conditions in commercial, industrial, and domestic settings [2]. As IoT becomes integrated with different facets of our life, their computational power and storage is often left to waste when idle. David Sonstebo, Sergey Ivancheglo, Dominik Schiener, and Serguei Popov founded the IOTA Foundation in June 2015 after working in the IoT industry because they saw the need to create an ecosystem where IoT devices share and allocate resources efficiently [3]. -
Peer Co-Movement in Crypto Markets
Peer Co-Movement in Crypto Markets G. Schwenkler and H. Zheng∗ February 4, 2021y Abstract We show that peer linkages induce significant price co-movement in crypto markets in excess of common risk factors and correlated demand shocks. When large abnormal return shocks hit one crypto, its peers experience unusually large abnormal returns of the opposite sign. These effects are primarily concentrated among smaller peers and revert after several weeks, resulting in predictable returns. We develop trading strategies that exploit this rever- sal, and show that they are profitable even after accounting for trading fees and frictions. We establish our results by identifying crypto peers through co-mentions in online news using novel natural language processing technologies. Keywords: Cryptocurrencies, peers, co-movement, competition, natural language pro- cessing. JEL codes: G12, G14, C82. ∗Schwenkler is at the Department of Finance, Santa Clara University Leavey School of Business. Zheng is at the Department of Finance, Boston University Questrom School of Business. Schwenkler is corresponding author. Email: [email protected], web: http://www.gustavo-schwenkler.com. yThis is a revision of a previous paper by the two authors called \Competition or Contagion: Evidence from Cryptocurrency Markets." We are grateful to Jawad Addoum (discussant), Daniele Bianchi (discussant), Will Cong, Tony Cookson, Sanjiv Das, Seoyoung Kim, Andreas Neuhierl, Farzad Saidi, and Antoinette Schoar, seminar participants at Boston University and the Society for Financial Econometrics, and the participants at the 2020 Finance in the Cloud III Virtual Conference, the 2020 MFA Annual Meeting, the 3rd UWA Blockchain, Cryptocurrency and FinTech Conference, and the 2020 INFORMS Annual Meeting for useful comments and suggestions. -
Wallance, an Alternative to Blockchain for Iot Loïc Dalmasso, Florent Bruguier, Achraf Lamlih, Pascal Benoit
Wallance, an Alternative to Blockchain for IoT Loïc Dalmasso, Florent Bruguier, Achraf Lamlih, Pascal Benoit To cite this version: Loïc Dalmasso, Florent Bruguier, Achraf Lamlih, Pascal Benoit. Wallance, an Alternative to Blockchain for IoT. IEEE 6th World Forum on Internet of Things (WF-IoT 2020), Jun 2020, New Orleans, LA, United States. 10.1109/WF-IoT48130.2020.9221474. hal-02893953v2 HAL Id: hal-02893953 https://hal.archives-ouvertes.fr/hal-02893953v2 Submitted on 1 Oct 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Wallance, an Alternative to Blockchain for IoT Loïc Dalmasso, Florent Bruguier, Achraf Lamlih, Pascal Benoit LIRMM University of Montpellier, CNRS Montpellier, France [email protected] Abstract—Since the expansion of the Internet of Things a decentralized Machine-to-Machine (M2M) communication (IoT), connected devices became smart and autonomous. Their protocol. A security mechanism has to ensure the trust exponentially increasing number and their use in many between devices, securing all interactions without a central application domains result in a huge potential of cybersecurity authority like Cloud. In this context, the blockchain system threats. Taking into account the evolution of the IoT, security brings many benefits in terms of reliability and security. -
Cryptocurrency Speculation and Blockchain Stocks (December 16, 2017 by Dafang Wu; PDF Version)
Cryptocurrency Speculation and Blockchain Stocks (December 16, 2017 by Dafang Wu; PDF Version) After Chicago Board Options Exchange began transactions of Bitcoin future contracts last week, cryptocurrency (“coin”) is becoming mainstream. We are quite late to this game, as many coins have appreciated more than 100 times so far this year, but it is never too late. This situation is similar to the early era of internet development, so we will need to understand the situation and cautiously catch up. Similar to many articles I wrote on airport finance, this article provides information rather than recommendations. Many coins are almost scams; many publicly traded companies claiming to be in blockchain technology, especially those traded over-the-counter (OTC), are also scams. Therefore, further research is required to make investment decisions, if we call coin speculation an “investment.” Background Instead of discussing the history of coins or technology, here are the basics that we need to know: Coins are digital currencies issued by organizations or teams; ownership and transactions are recorded in a public ledger There are more than 1,000 coins, with Bitcoin having the highest market capitalization of nearly $300 billion Each coin has a name, such as Bitcoin, and a trading ticker like stock, such as BTC There are more than 7,000 coin exchanges Some exchanges allow us to purchase coins using real life money, which they refer to as fiat money Some exchanges are not regulated, and only allow us to trade among coins. For this type of exchange, Bitcoin is typically the currency. To switch between two other coins, we will need to sell the first one and receive Bitcoin, and use the Bitcoin to purchase the second one There is no customer service for any coin – if we accidentally lose it or send to a wrong party, there is no way to get back Security threat and fraud always exist for coin trading – search Mt. -
The Magnificent Seven
The Magnificent Seven A closer look at functional attributes of blockchain platforms The Magnificent Seven1 Following a whitepaper published in late 2008, the Bitcoin system came into being in 2009, and the underlying technology became what we refer to as Blockchain today. 1 The top seven cryptocurrencies covered a good variety of attributes that are essential to gain a more thorough understanding of the potentials offered by this new technology. The Magnificent Seven 1 Since then, a variety of different cryptocurrency platforms have been created, and based on data from CoinMarketCap (https://coinmarketcap.com/), as of 27 March 2021, there were 8,964 crypto tokens in existence, with a total Market Cap of over USD$1.6 Trillion. The top seven cryptocurrencies made up around 80% of the global market capitalisation: Market Cap Token Symbol (billion USD) % Bitcoin BTC 1,026.8 59.23 Ethereum ETH 0,196.2 11.32 Cardano ADA 0,040.2 02.32 Binance Coin BNB 0,039.1 02.25 Tether USDT 0,038.5 02.22 Polkadot DOT 0,030.4 01.75 XRP XRP 0,025.8 01.49 80.58 Rest of 8,957 tokens 19.42 Bitcoin alone represents nearly 60% of the total cryptocurrency value, with Ethereum being the second highest by value. However, these cryptocurrencies are not in fact the same: value aside, they differ in some interesting ways, which in turn affect their “function” and value proposition. Asset Smart Token Year Type Minable Consensus2 Limit Backed Contract BTC 2009 Native Yes POW No 21m ETH 2012 ERC-20 Yes / No3 POW | POS No Y none ADA 2017 Native No POS No Y 45bn BNB 2017 ERC-20 No Tendermint No 100m Multiple Forms: USDT-Omni, USDT 2014 USDT-TRON, No NA USD none USDT-ERC20 and USDT-EOS DOT 2017 Native NPOS No Y none Ripple XRP 2012 Native No Transaction No 100bn Protocol Source: https://icorating.com/ and https://coincodex.com/ 2 In simple terms, consensus mechanism is a means of authenticating and validating transactions on a Blockchain (or distributed ledger) without having to trust or rely on a central authority. -
GJR-GARCH Volatility Modeling Under NIG and ANN for Predicting Top Cryptocurrencies
Journal of Risk and Financial Management Article GJR-GARCH Volatility Modeling under NIG and ANN for Predicting Top Cryptocurrencies Fahad Mostafa 1,* , Pritam Saha 2, Mohammad Rafiqul Islam 3 and Nguyet Nguyen 4,* 1 Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409, USA 2 Rawls College of Business, Texas Tech University, Lubbock, TX 79409, USA; [email protected] 3 Department of Mathematics, Florida State University, Tallahassee, FL 32306, USA; [email protected] 4 Department of Mathematics and Statistics, Youngstown State University, Youngstown, OH 44555, USA * Correspondence: [email protected] (F.M.); [email protected] (N.N.) Abstract: Cryptocurrencies are currently traded worldwide, with hundreds of different currencies in existence and even more on the way. This study implements some statistical and machine learning approaches for cryptocurrency investments. First, we implement GJR-GARCH over the GARCH model to estimate the volatility of ten popular cryptocurrencies based on market capitalization: Bitcoin, Bitcoin Cash, Bitcoin SV, Chainlink, EOS, Ethereum, Litecoin, TETHER, Tezos, and XRP. Then, we use Monte Carlo simulations to generate the conditional variance of the cryptocurrencies using the GJR-GARCH model, and calculate the value at risk (VaR) of the simulations. We also estimate the tail-risk using VaR backtesting. Finally, we use an artificial neural network (ANN) for predicting the prices of the ten cryptocurrencies. The graphical analysis and mean square errors (MSEs) from the ANN models confirmed that the predicted prices are close to the market prices. For some cryptocurrencies, the ANN models perform better than traditional ARIMA models. Citation: Mostafa, Fahad, Pritam Saha, Mohammad Rafiqul Islam, and Keywords: artificial neural network; cryptocurrency; GJR-GARCH; NIG; Monte Carlo simulation; Nguyet Nguyen. -
PWC and Elwood
2020 Crypto Hedge Fund Report Contents Introduction to Crypto Hedge Fund Report 3 Key Takeaways 4 Survey Data 5 Investment Data 6 Strategy Insights 6 Market Analysis 7 Assets Under Management (AuM) 8 Fund performance 9 Fees 10 Cryptocurrencies 11 Derivatives and Leverage 12 Non-Investment Data 13 Team Expertise 13 Custody and Counterparty Risk 15 Governance 16 Valuation and Fund Administration 16 Liquidity and Lock-ups 17 Legal and Regulatory 18 Tax 19 Survey Respondents 20 About PwC & Elwood 21 Introduction to Crypto Hedge Fund report In this report we provide an overview of the global crypto hedge fund landscape and offer insights into both quantitative elements (such as liquidity terms, trading of cryptocurrencies and performance) and qualitative aspects, such as best practice with respect to custody and governance. By sharing these insights with the broader crypto industry, our goal is to encourage the adoption of sound practices by market participants as the ecosystem matures. The data contained in this report comes from research that was conducted in Q1 2020 across the largest global crypto hedge funds by assets under management (AuM). This report specifically focuses on crypto hedge funds and excludes data from crypto index/tracking/passive funds and crypto venture capital funds. 3 | 2020 Crypto Hedge Fund Report Key Takeaways: Size of the Market and AuM: Performance and Fees: • We estimate that the total AuM of crypto hedge funds • The median crypto hedge fund returned +30% in 2019 (vs - globally increased to over US$2 billion in 2019 from US$1 46% in 2018). billion the previous year. -
OCC Interpretive Letter 1174: DLT and Stable Coins
OCC interpretive letter 1174: DLT and stable coins Author: Ousmène Jacques Mandeng, Senior Advisor, Blockchain and Multiparty Systems, Accenture Table of Contents OCC interpretive letter 1174: DLT and stable coins .................................................. 2 OCC’s position on DLT and stable coins ................................................................. 2 DLT-platforms .......................................................................................................... 3 Tokens ..................................................................................................................... 4 Stable coins ............................................................................................................. 4 Token payments ...................................................................................................... 5 Token networks ....................................................................................................... 5 Bank balance sheet tokenization ............................................................................ 6 Next steps ................................................................................................................. 7 Copyright © 2021 Accenture. All rights reserved. 1 United States OCC interpretive letter 1174: DLT and stable coins The United States Office of the Comptroller of the Currency (OCC), a federal supervisor of national banks and cooperative banks, issued new general guidance about stable coins and distributed ledger technology (DLT) -
Defending Against Malicious Reorgs in Tezos Proof-Of-Stake
Defending Against Malicious Reorgs in Tezos Proof-of-Stake Michael Neuder Daniel J. Moroz Harvard University Harvard University [email protected] [email protected] Rithvik Rao David C. Parkes Harvard University Harvard University [email protected] [email protected] ABSTRACT Conference on Advances in Financial Technologies (AFT ’20), October 21– Blockchains are intended to be immutable, so an attacker who is 23, 2020, New York, NY, USA. ACM, New York, NY, USA , 13 pages. https: //doi.org/10.1145/3419614.3423265 able to delete transactions through a chain reorganization (a ma- licious reorg) can perform a profitable double-spend attack. We study the rate at which an attacker can execute reorgs in the Tezos 1 INTRODUCTION Proof-of-Stake protocol. As an example, an attacker with 40% of the Blockchains are designed to be immutable in order to protect against staking power is able to execute a 20-block malicious reorg at an attackers who seek to delete transactions through chain reorga- average rate of once per day, and the attack probability increases nizations (malicious reorgs). Any attacker who causes a reorg of super-linearly as the staking power grows beyond 40%. Moreover, the chain could double-spend transactions, meaning they commit an attacker of the Tezos protocol knows in advance when an at- a transaction to the chain, receive some goods in exchange, and tack opportunity will arise, and can use this knowledge to arrange then delete the transaction, effectively robbing their counterparty. transactions to double-spend. We show that in particular cases, the Nakamoto [15] demonstrated that, in a Proof-of-Work (PoW) setting, Tezos protocol can be adjusted to protect against deep reorgs. -
Governance in Decentralized Networks
Governance in decentralized networks Risto Karjalainen* May 21, 2020 Abstract. Effective, legitimate and transparent governance is paramount for the long-term viability of decentralized networks. If the aim is to design such a governance model, it is useful to be aware of the history of decision making paradigms and the relevant previous research. Towards such ends, this paper is a survey of different governance models, the thinking behind such models, and new tools and structures which are made possible by decentralized blockchain technology. Governance mechanisms in the wider civil society are reviewed, including structures and processes in private and non-profit governance, open-source development, and self-managed organisations. The alternative ways to aggregate preferences, resolve conflicts, and manage resources in the decentralized space are explored, including the possibility of encoding governance rules as automatically executed computer programs where humans or other entities interact via a protocol. Keywords: Blockchain technology, decentralization, decentralized autonomous organizations, distributed ledger technology, governance, peer-to-peer networks, smart contracts. 1. Introduction This paper is a survey of governance models in decentralized networks, and specifically in networks which make use of blockchain technology. There are good reasons why governance in decentralized networks is a topic of considerable interest at present. Some of these reasons are ideological. We live in an era where detailed information about private individuals is being collected and traded, in many cases without the knowledge or consent of the individuals involved. Decentralized technology is seen as a tool which can help protect people against invasions of privacy. Decentralization can also be viewed as a reaction against the overreach by state and industry. -
Blockchain & Cryptocurrency Regulation
Blockchain & Cryptocurrency Regulation Third Edition Contributing Editor: Josias N. Dewey Global Legal Insights Blockchain & Cryptocurrency Regulation 2021, Third Edition Contributing Editor: Josias N. Dewey Published by Global Legal Group GLOBAL LEGAL INSIGHTS – BLOCKCHAIN & CRYPTOCURRENCY REGULATION 2021, THIRD EDITION Contributing Editor Josias N. Dewey, Holland & Knight LLP Head of Production Suzie Levy Senior Editor Sam Friend Sub Editor Megan Hylton Consulting Group Publisher Rory Smith Chief Media Officer Fraser Allan We are extremely grateful for all contributions to this edition. Special thanks are reserved for Josias N. Dewey of Holland & Knight LLP for all of his assistance. Published by Global Legal Group Ltd. 59 Tanner Street, London SE1 3PL, United Kingdom Tel: +44 207 367 0720 / URL: www.glgroup.co.uk Copyright © 2020 Global Legal Group Ltd. All rights reserved No photocopying ISBN 978-1-83918-077-4 ISSN 2631-2999 This publication is for general information purposes only. It does not purport to provide comprehensive full legal or other advice. Global Legal Group Ltd. and the contributors accept no responsibility for losses that may arise from reliance upon information contained in this publication. This publication is intended to give an indication of legal issues upon which you may need advice. Full legal advice should be taken from a qualified professional when dealing with specific situations. The information contained herein is accurate as of the date of publication. Printed and bound by TJ International, Trecerus Industrial Estate, Padstow, Cornwall, PL28 8RW October 2020 PREFACE nother year has passed and virtual currency and other blockchain-based digital assets continue to attract the attention of policymakers across the globe. -
![Can Ethereum Classic Reach 1000 Dollars Update [06-07-2021] 42 Loss in the Last 24 Hours](https://docslib.b-cdn.net/cover/0683/can-ethereum-classic-reach-1000-dollars-update-06-07-2021-42-loss-in-the-last-24-hours-490683.webp)
Can Ethereum Classic Reach 1000 Dollars Update [06-07-2021] 42 Loss in the Last 24 Hours
1 Can Ethereum Classic Reach 1000 Dollars Update [06-07-2021] 42 loss in the last 24 hours. At that time Bitcoin reached its all-time high of 20,000 and so did Ethereum ETH which surpassed 1,000. 000 to reach 1; Tezos XTZ is priced at 2. In the unlikely event of a significant change for the worst, we expect the Bitcoin price to continue appreciating. ERC-721 started as a EIP draft written by dete and first came to life in the CryptoKitties project by Axiom Zen. ERC-721 A CLASS OF UNIQUE TOKENS. It does not mandate a standard for token metadata or restrict adding supplemental functions. Think of them like rare, one-of-a-kind collectables. The Standard. Institutions are mandating that they invest in clean green technologies and that s what ethereum is becoming, she said. Unlike bitcoin s so-called proof of work, which rewards miners who are competing against each other to use computers and energy to record and confirm transactions on its blockchain, ethereum plans to adopt the more efficient proof of stake model, which chooses a block validator at random based on how much ether it controls. Kaspar explained her thesis Friday on Yahoo Finance Live, citing new updates coming to the cryptocurrency s network later this year. 42 loss in the last 24 hours. At that time Bitcoin reached its all-time high of 20,000 and so did Ethereum ETH which surpassed 1,000. 000 to reach 1; Tezos XTZ is priced at 2. In the unlikely event of a significant change for the worst, we expect the Bitcoin price to continue appreciating.