Bitcoin is an exciting new financial product that may be useful for inclusion in investment portfolios. This paper investigates the implications of replacing gold in an investment portfolio with bitcoin (âdigital goldâ). Our approach is to use several different multivariate GARCH models (dynamic conditional correlation (DCC), asymmetric DCC (ADCC), generalized orthogonal GARCH (GO-GARCH)) to estimate minimum variance equity portfolios. Both long and short portfolios are considered. An analysis of the economic value shows that risk-averse investors will be willing to pay a high performance fee to switch from a portfolio with gold to a portfolio with bitcoin. These results are robust to the inclusion of trading costs.
The Decentralized-Consistent-Scale (DCS) Triangle defines three dimensions that illustrate the tradeoffs of the blockchain consensus mechanism. In this paper, we propose a new hybrid consensus protocol, called Deterministic Proof of Work (DPoW), which can reach high levels of scalability and consistency without significant reduction to decentralization. Our protocol introduces a Map-reduce PoW mining algorithm to perform alongside Practical Byzantine Fault Tolerance (PBFT) verification, which together allow for transactions to be confirmed immediately, largely improving scalability. In addition, the protocol is designed such that forking cannot occur, ensuring strong consistency and security against a multitude of attacks. The Map-reduce PoW mining process ensures that no single entity can control the network, guaranteeing decentralization. We analyzed the security of our protocol by evaluating the possibility of double spending attacks, and furthermore, conducted experiments which demonstrate our claims.
Anonymity networks and hidden services like those accessible in Tor, also called the "darknet", in combination with cryptocurrencies like bitcoin provide a relatively safe environment for criminal online activities. While this is a challenge for law enforcement, it brings opportunities for researchers to monitor these activities as they are often not really hidden but rather obfuscated and/or anonymized. In this paper we discuss such a monitoring approach for product sales in the darknet. We collect bitcoin addresses and data about product offerings in a number of shops run as hidden services in Tor. We then analyze transactions in the bitcoin blockchain that can be mapped to specific product sales in these shops.
Derivatives are the âbad boysâ of modern finance: exciting, dangerous, and fundamentally misunderstood. These misunderstandings stem from the failure of scholars and policymakers to fully appreciate the unique legal and economic structure of derivative contracts, along with the important differences between these contracts and conventional equity and debt securities. This Article seeks to correct these misunderstandings by splitting derivative contracts open, identifying their constituent elements, and observing how these elements interact with one another. These elements include some of the worldâs most sophisticated state-contingent contracting, the allocation of property and decision-making rights, and relational mechanisms such as reputation and the expectation of future dealings. The resulting hybridity essentially splits every derivative into two separate contracts: one that governs under normal market conditions, and another that governs under conditions of fundamental uncertainty. In good times, derivative contracts contemplate the almost automatic determination and performance of each counterpartyâs obligations. In bad times, these contracts include various mechanisms designed to provide counterparties with the flexibility to incorporate new information, fill contractual gaps, and promote efficient renegotiation.\nThe process of splitting derivative contracts open yields a number of important policy insights. First, the bundling of contract, property, decision-making rights, and relational mechanisms makes derivatives look far more like commercial loans than publicly traded shares or bonds. The regulatory treatment of derivatives as âsecuritiesââand the resulting emphasis on market transparencyâis thus somewhat misguided and serves to distract attention from the significant prudential risks posed by the widespread use of derivatives. Second, the flexibility associated with the relational mechanisms embedded within many derivative contracts can play a useful role in promoting both institutional and broader financial stability. This has important implications in terms of the desirability of the recent push toward mandatory central clearing of derivative contracts. It also exposes the potential perils of recent proposals to use distributed ledger technology and smart contracts to execute, clear, and settle these contracts. By the same token, the widespread breakdown of these relational mechanisms can be a source of financial instability. This provides a compelling rationale for authorizing central banks to act as âdealers of last resortâ during periods of fundamental uncertainty.
Zusammenfassung Mit dem FinTech-Aktionsplan, den die EuropĂ€ische Kommission im FrĂŒhjahr vorgestellt hat, werden erste Konturen einer europĂ€ischen Agenda fĂŒr innovative Finanztechnologien (FinTech) erkennbar. So umfassend der Anwendungsbereich des Aktionsplans, so beschrĂ€nkt ist jedoch bislang sein materieller Regelungsgehalt. Die Rechtswissenschaft hat umso mehr zur kĂŒnftigen Rechtsentwicklung beizutragen, muss dabei aber dem primĂ€r ermöglichenden Charakter der europĂ€ischen FinTech-Agenda Rechnung tragen. Blockchain-basierten Smart Contracts, die in der Finanzbranche groĂes Potenzial haben, sollte insoweit besonderes Augenmerk gelten, zumal angesichts ihres selbstdurchsetzenden, regelnden GeprĂ€ges. Der nachfolgende Beitrag illustriert nach einer ĂŒberblicksartigen Darstellung des Aktionsplans die rechtlichen Grenzen, die in seiner Folge zu ĂŒberdenken sein werden; dabei konzentriert er sich auf jene Smart Contracts und deren Begrenzung, insbesondere durch mitgliedstaatliche Regeln zur privatrechtlichen Selbsthilfe.
This article presents policing challenges of investigating, evidencing and prosecuting organized cybercriminals for the crimes committed using cryptocurrencies such as Bitcoin. A set of best practices is discussed to tackle these challenges in real world investigations. This work is a result of collaboration with a number of stakeholders the policing and judicial ecosystem with the objective of investigating and prosecuting the new generation of organised cybercriminals. Concrete scenarios of using Bitcoins in a range of cybercrimes were developed as part of this project and the devices were analysed to extract evidence to assist prosecution of organised cybercriminals. We have also presented our return of experience for various stages of digital forensics analysis of devices used in Bitcoin transactions.
In this report, Shakow explains how a decentralized autonomous organization functions and interacts with the U.S. tax system and presents the many tax issues that these structures raise. The possibility of using smart contracts to allow an entity to operate totally autonomously on a blockchain platform seems attractive. However, little thought has been given to how such an entity can comply with the requirements of a tax system. The DAO, the first major attempt to create such an organization, failed because of a programming error. If successful examples proliferate in the future, tax authorities will face significant problems in getting these organizations and their owners to comply with the tax laws.
Dimitris Chatzopoulos, Sujit Gujar, Boi Faltings, Pan Hui
The popularity and applicability of mobile crowdsensing applications are continuously increasing due to the widespread of mobile devices and their sensing and processing capabilities. However, we need to offer appropriate incentives to the mobile users who contribute their resources and preserve their privacy. Blockchain technologies enable semi-anonymous multi-party interactions and can be utilized in crowdsensing applications to maintain the privacy of the mobile users while ensuring first-rate crowdsensed data. In this work, we propose to use blockchain technologies and smart contracts to orchestrate the interactions between mobile crowdsensing providers and mobile users for the case of spatial crowdsensing, where mobile users need to be at specific locations to perform the tasks. Smart contracts, by operating as processes that are executed on the blockchain, are used to preserve users' privacy and make payments. Furthermore, for the assignment of the crowdsensing tasks to the mobile users, we design a truthful, cost-optimal auction that minimizes the payments from the crowdsensing providers to the mobile users. Extensive experimental results show that the proposed privacy preserving auction outperforms state-of-the-art proposals regarding cost by ten times for high numbers of mobile users and tasks.
AntĂŽnio Carlos da Silva Filho, NatĂĄlia Diniz Maganini, Eduardo Fonseca de Almeida
The recent emergence and use growth of cryptocurrencies based on Blockchain technology increased interest in the study of its economic dynamics and financial characteristics. Bitcoin is up to now the more widely known and disseminated cryptocurrency, with greater volume of transactions, market value and acceptance in exchange services. In order to contribute to the comprehension of the price behavior of the Bitcoin market, this study analyzes whether the historical series of prices of this currency, quoted every 12 h from September 14, 2011 to November 20, 2017 has multifractal behavior. The results of the research identified multifractal characteristics in the series and that both long-range correlations and fat tails distribution contribute to Bitcoinâs multifractal behavior. We compared the non-Gaussian properties and the multifractality degrees of Bitcoin series with the non-Gaussian properties and multifractality degrees of several stock market indices scattered around the world. In addition, we investigated the power of multifractal analysis in the study of volatility and forecast for this series, pointing to a possible use of multifractal parameters in Technical Analysis.
Hyesung Kim, Jihong Park, Mehdi Bennis, Seong-Lyun Kim
By leveraging blockchain, this letter proposes a blockchained federated learning (BlockFL) architecture where local learning model updates are exchanged and verified. This enables on-device machine learning without any centralized training data or coordination by utilizing a consensus mechanism in blockchain. Moreover, we analyze an end-to-end latency model of BlockFL and characterize the optimal block generation rate by considering communication, computation, and consensus delays.
Sandi Gec, Dejan LavbiÄ, Marko Bajec, Vlado Stankovski
Today, container-based virtualization is very popular due to the lightweight nature of containers and the ability to use them flexibly in various heterogeneously composed systems. This makes it possible to collaboratively develop services by sharing various types of resources, such as infrastructures, software and digitalized content. In this work, our home made video-conferencing (VC) system is used to study resource usage optimisation in business context. An application like this, does not provide monetization possibilities to all involved stakeholders including end users, cloud providers, software engineers and similar. Blockchain related technologies, such as Smart Contracts (SC) offer a possibility to address some of these needs. We introduce a novel architecture for monetization of added-value according to preferences of the stakeholders that participate in joint software service offers. The developed architecture facilitates use case scenarios of service and resource offers according to fixed and dynamic pricing schemes, fixed usage period, prepaid quota for flexible usage, division of income, consensual decisions among collaborative service providers, and constrained based usage of resources or services. Our container-based VC service, which is based on the Jitsi Meet Open Source software is used to demonstrate the proposed architecture and the benefits of the investigated use cases.
Sandi Gec, Dejan LavbiÄ, Marko Bajec, Vlado Stankovski
Today, container-based virtualization is very popular due to the lightweight\nnature of containers and the ability to use them flexibly in various\nheterogeneously composed systems. This makes it possible to collaboratively\ndevelop services by sharing various types of resources, such as\ninfrastructures, software and digitalized content. In this work, our home made\nvideo-conferencing (VC) system is used to study resource usage optimisation in\nbusiness context. An application like this, does not provide monetization\npossibilities to all involved stakeholders including end users, cloud\nproviders, software engineers and similar. Blockchain related technologies,\nsuch as Smart Contracts (SC) offer a possibility to address some of these\nneeds. We introduce a novel architecture for monetization of added-value\naccording to preferences of the stakeholders that participate in joint software\nservice offers. The developed architecture facilitates use case scenarios of\nservice and resource offers according to fixed and dynamic pricing schemes,\nfixed usage period, prepaid quota for flexible usage, division of income,\nconsensual decisions among collaborative service providers, and constrained\nbased usage of resources or services. Our container-based VC service, which is\nbased on the Jitsi Meet Open Source software is used to demonstrate the\nproposed architecture and the benefits of the investigated use cases.\n
Price stability has often been cited as a key reason that cryptocurrencies have not gained widespread adoption as a medium of exchange and continue to prove incapable of powering the economy of decentralized applications (DApps) efficiently. Exeum proposes a novel method to provide price stable digital tokens whose values are pegged to real world assets, serving as a bridge between the real world and the decentralized economy. Pegged tokens issued by Exeum - for example, USDE refers to a stable token issued by the system whose value is pegged to USD - are backed by virtual assets in a virtual asset exchange where users can deposit the base token of the system and take long or short positions. Guaranteeing the stability of the pegged tokens boils down to the problem of maintaining the peg of the virtual assets to real world assets, and the main mechanism used by Exeum is controlling the swap rate of assets. If the swap rate is fully controlled by the system, arbitrageurs can be incentivized enough to restore a broken peg; Exeum distributes statistical arbitrage trading software to decentralize this type of market making activity. The last major component of the system is a central bank equivalent that determines the long term interest rate of the base token, pays interest on the deposit by inflating the supply if necessary, and removes the need for stability fees on pegged tokens, improving their usability. To the best of our knowledge, Exeum is the first to propose a truly decentralized method for developing a stablecoin that enables 1:1 value conversion between the base token and pegged assets, completely removing the mismatch between supply and demand. In this paper, we will also discuss its applications, such as improving staking based DApp token models, price stable gas fees, pegging to an index of DApp tokens, and performing cross-chain asset transfer of legacy crypto assets.
Price stability has often been cited as a key reason that cryptocurrencies\nhave not gained widespread adoption as a medium of exchange and continue to\nprove incapable of powering the economy of decentralized applications (DApps)\nefficiently. Exeum proposes a novel method to provide price stable digital\ntokens whose values are pegged to real world assets, serving as a bridge\nbetween the real world and the decentralized economy.\n Pegged tokens issued by Exeum - for example, USDE refers to a stable token\nissued by the system whose value is pegged to USD - are backed by virtual\nassets in a virtual asset exchange where users can deposit the base token of\nthe system and take long or short positions. Guaranteeing the stability of the\npegged tokens boils down to the problem of maintaining the peg of the virtual\nassets to real world assets, and the main mechanism used by Exeum is\ncontrolling the swap rate of assets. If the swap rate is fully controlled by\nthe system, arbitrageurs can be incentivized enough to restore a broken peg;\nExeum distributes statistical arbitrage trading software to decentralize this\ntype of market making activity. The last major component of the system is a\ncentral bank equivalent that determines the long term interest rate of the base\ntoken, pays interest on the deposit by inflating the supply if necessary, and\nremoves the need for stability fees on pegged tokens, improving their\nusability.\n To the best of our knowledge, Exeum is the first to propose a truly\ndecentralized method for developing a stablecoin that enables 1:1 value\nconversion between the base token and pegged assets, completely removing the\nmismatch between supply and demand. In this paper, we will also discuss its\napplications, such as improving staking based DApp token models, price stable\ngas fees, pegging to an index of DApp tokens, and performing cross-chain asset\ntransfer of legacy crypto assets.\n
In proof-of-stake based consortium blockchain networks, pre-selected miners compete to solve a crypto-puzzle with a successfully mining probability proportional to the amount of their stakes. When the puzzle is solved, the miners are encouraged to take part in mined block propagation for verification to win a transaction fee from the blockchain user. The mined block should be propagated over wired or wireless networks, and be verified as quickly as possible to decrease consensus propagation delay. In this letter, we study incentivizing the consensus propagation considering the tradeoff between the network delay of block propagation process and offered transaction fee from the blockchain user. A Stackelberg game is then formulated to jointly maximize utility of the blockchain user and individual profit of the miners. The blockchain user acting as the leader sets the transaction fee for block verification. The miners acting as the followers decide on the number of recruited verifiers over wired or wireless networks. We apply the backward induction to analyze the existence and uniqueness of the Stackelberg equilibrium. Performance evaluation validates the feasibility and efficiency of the proposed game model in consensus propagation.
In many developing countries, politicians often turn to private firms for illicit election finance. In sectors where firms are highly regulated, politicians can exchange policy discretion or regulatory favours for financial support during elections. This chapter explores this dynamic by focusing on the role of the construction sector in India, a domain where regulatory intensity is high. Specifically, we argue that builders will experience a short-term liquidity crunch as elections approach because of their need to re-route funds to campaigns as a form of indirect election finance. We use variation in the demand for cement, the indispensable ingredient for construction, to investigate the presence of an electoral cycle in building activity consistent with this logic. Using a novel monthly-level dataset, we demonstrate that cement consumption does exhibit a political business cycle supportive of our hypothesis.
Most cryptocurrency systems or systems based on blockchain technology are currently using the elliptic curves digital signature algorithm (ECDSA) on the secp256k1 curve, which is susceptible to backdoors implemented by the curve creator (secp256k1). The paper proposes a multiple elliptic curves digi-tal signature algorithm (MECDSA), which allows not only for setting the number of elliptic curves according to practical security requirements, but also for editing the parameters of each elliptic curve. The performance analy-sis proves that the scheme is secure and efficient, and can avoid any back-doors implemented by curve creators. We suggest that the systems based on blockchain should operate in two elliptic curves considering the contradic-tion between security and efficiency.
This thesis focuses on aspects related to the functioning of the gossip\nnetworks underlying three relatively popular cryptocurrencies: Ethereum, Nano\nand IOTA.\n We look at topics such as automatic discovery of peers when a new node joins\nthe network, bandwidth usage of a node, message passing protocols and storage\nschemas and optimizations for the shared ledger. We believe this is a topic\nthat is often overlooked in works about blockchains and cryptocurrencies.\nVulnerabilities and inefficiencies attain a higher significance than ones in a\nregular open source project because of the rather direct financial implications\nof these projects. Barring Bitcoin, a network that has been around for nearly\n10 years, no other project has substantial documentation for its operational\ndetails other than scattered and sparse pages in the source code repositories.\nAlmost all of the content described here has been extracted by studying the\nsource code of the reference implementations of these projects.\n We evaluate the use of Invertible Bloom Lookup Tables and the Graphene\nprotocol to decrease block propagation times and bandwidth usage of certain\nmessages. We perform realistic simulations that show significant improvements.\nWe provide a complete implementation of Graphene in Geth, Ethereum's main node\nsoftware and test this implementation against the main Ethereum blockchain.\n We also crawled the chosen cryptocurrency networks for publicly visible nodes\nand provide an Autonomous System-level breakdown of these nodes with the end\ngoal of estimating the ease of performing attacks such as BGP hijacks and their\nimpact.\n Code written for implementing Graphene in Geth, performing various\nsimulations and for other miscellaneous tasks has been uploaded to Github at\nhttps://github.com/sunfinite/masters-thesis.\n
We test the presence of regime changes in the GARCH volatility dynamics of Bitcoin logâreturns using Markovâswitching GARCH (MSGARCH) models. We also compare MSGARCH to traditional singleâregime GARCH specifications in predicting oneâday ahead ValueâatâRisk (VaR). The Bayesian approach is used to estimate the model parameters and to compute the VaR forecasts. We find strong evidence of regime changes in the GARCH process and show that MSGARCH models outperform singleâregime specifications when predicting the VaR.