This paper reports on how the technology behind cryptocurrency (Bitcoin) i.e. Blockchain could offer its services in distributed energy system (DES), noting on the issues related to operating conditions, energy generation monitoring, energy sharing and trading, financial flows, emission inventory, carbon emission trading and many more. Information on blockchain implication in DES is reported.
Cryptocurrencies have slowly managed to take their place in the panorama of global economic transfers, thanks to the advantages offered by traditional financial systems. By focusing on Bitcoin we can see that this cryptocurrency is global, without political, economic or social barriers. since it is based on a "person to person" system, allowing the exchange of value through the Internet without the need for a central institution or human interaction for its operation, it also has almost imperceptible transaction costs, depends on the internal movements of the platform of supply and demand, then seen in this way Bitcoin could change the current way of doing business in the world.
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.
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.
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.
With the successful application of Bitcoin, the underlying blockchain technology has been attracted the attention by more and more scholars, financial institutions and commercial companies. Blockchain technology integrates some key technologies such as finance, cryptography, computer science, and game theory, and builds a distributed record system that is decentralized, mutually trusted, and tamper-proof. This paper demonstrates the basic principles and features of blockchain, then analyzes the key technologies and characteristics of blockchain technology including asymmetric encryption, P2P, consensus mechanisms, smart contracts. In the last part of the paper, the author summarizes the potential application scenarios to blockchain and focuses on applications of the blockchain technology in the power industry.
Blockchain has many benefits including decentralization, availability, persistency, consistency, anonymity, auditability and accountability, and it also covers a wide spectrum of applications ranging from cryptocurrency, financial services, reputation system, Internet of Things, sharing economy to public and social services. Not only may blockchain be regarded as a by-product of Bitcoin cryptocurrency systems, but also it is a type of distributed ledger technology through using a trustworthy, decentralized log of totally ordered transactions. By summarizing the literature of blockchain, it is found that more papers focus on engineering implementation and realization, while little work has been done on basic theory, for example, mathematical models (Markov processes, queueing theory and game models), performance analysis and optimization of blockchain systems. In this paper, we develop queueing theory of blockchain systems and provide system performance evaluation. To do this, we design a Markovian batch-service queueing system with two different service stages, while the two stages are suitable to well express the mining process in the miners pool and the building of a new blockchain. By using the matrix-geometric solution, we obtain a system stable condition and express three key performance measures: (a) The number of transactions in the queue, (b) the number of transactions in a block, and (c) the transaction-confirmation time. Finally, We use numerical examples to verify computability of our theoretical results. Although our queueing model is simple under exponential or Poisson assumptions, our analytic method will open a series of potentially promising research in queueing theory of blockchain systems.
Changting Lin, Ning Ma, Xun Wang, Zhenguang Liu · 6 authors
Bitcoin blockchain faces the bitcoin scalability problem, for which bitcoin's blocks contain the transactions on the bitcoin network. The on-chain transaction processing capacity of the bitcoin network is limited by the average block creation time of 10 minutes and the block size limit. These jointly constrain the network's throughput. The transaction processing capacity maximum is estimated between 3.3 and 7 transactions per second (TPS). A Layer2 Network, named Lightning Network, is proposed and activated solutions to address this problem. LN operates on top of the bitcoin network as a cache to allow payments to be affected that are not immediately put on the blockchain. However, it also brings some drawbacks. In this paper, we observe a specific payment issue among current LN, which requires additional claims to blockchain and is time-consuming. We call the issue as shares issue. Therefore, we propose Rapido to explicitly address the shares issue. Furthermore, a new smart contract, D-HTLC, is equipped with Rapido as the payment protocol. We finally provide a proof of concept implementation and simulation for both Rapido and LN, in which Rapdio not only mitigates the shares issue but also mitigates the skewness issue thus is proved to be more applicable for various transactions than LN.
Sequences of random objects arise from many real applications, including high throughput omic data and functional imaging data. Those sequences are usually dependent, non-linear, or even Non-Euclidean, and an important problem is change-point detection in such dependent sequences in Banach spaces or metric spaces. The problem usually requires the accurate inference for not only whether changes might have occurred but also the locations of the changes when they did occur. To this end, we first introduce a Ball detection function and show that it reaches its maximum at the change-point if a sequence has only one change point. Furthermore, we propose a consistent estimator of Ball detection function based on which we develop a hierarchical algorithm to detect all possible change points. We prove that the estimated change-point locations are consistent. Our procedure can estimate the number of change-points and detect their locations without assuming any particular types of change-points as a change can occur in a sequence in different ways. Extensive simulation studies and analyses of two interesting real datasets wind direction and Bitcoin price demonstrate that our method has considerable advantages over existing competitors, especially when data are non-Euclidean or when there are distributional changes in the variance.
We compute and compare profitabilities of stubborn mining strategies that are variations of selfish mining. These are deviant mining strategies violating Bitcoin's network protocol rules. We apply the foundational set-up from our previous companion article on the profitability of selfish mining, and the new martingale techniques to get a closed-form computation for the revenue ratio, which is the correct benchmark for profitability. Catalan numbers and Catalan distributions appear in the closed-form computations. This marks the first appearance of Catalan numbers in the Mathematics of the Bitcoin protocol.
Aug 2, 2018·Jan RĂŒth, Torsten Zimmermann, Konrad Wolsing, and Oliver Hohlfeld. 2018. Digging into Browser-based Crypto Mining. In IMC '18: Internet Measurement Conference, October 31-November 2, 2018, Boston, MA, USA. ACM, New York, NY, USA, 7 pages
Jan RĂŒth, Torsten Zimmermann, Konrad Wolsing, Oliver Hohlfeld
Mining is the foundation of blockchain-based cryptocurrencies such as Bitcoin rewarding the miner for finding blocks for new transactions. The Monero currency enables mining with standard hardware in contrast to special hardware (ASICs) as often used in Bitcoin, paving the way for in-browser mining as a new revenue model for website operators. In this work, we study the prevalence of this new phenomenon. We identify and classify mining websites in 138M domains and present a new fingerprinting method which finds up to a factor of 5.7 more miners than publicly available block lists. Our work identifies and dissects Coinhive as the major browser-mining stakeholder. Further, we present a new method to associate mined blocks in the Monero blockchain to mining pools and uncover that Coinhive currently contributes 1.18% of mined blocks having turned over 1293 Moneros in June 2018.
This paper offers an overview of the highlights of the NFAIS Conference, Blockchain for Scholarly Publishing, that was held in Alexandria, VA from May 15â16, 2018. The goal of the conference was to take a close look at the initiatives that have emerged as a result of the increasing global acceptance of blockchain technology. This technology, chiefly known as the foundation of Bitcoin and originally introduced as a means of securely managing cryptocurrency, has proven to have practical applications beyond finance. The basic technology is that of a distributed ledger and it is being broadly-adopted by multiple industries, including the scholarly publishing community. The capabilities of this new technology are prompting a direct exchange among stakeholders, as blockchain promises a more structured, decentralized, and immutably secure approach that has the potential to significantly impact researcher workflows - from data collection to peer review to access and published work. The technology inspires passion - there are those who believe that it will ultimately transform our lives while others are completely skeptical. The NFAIS conference provided a look at both sides of the coin (no pun intended).
Since Bitcoinâs launch in early 2009, the industrial and academic interest in Blockchain and other cryptocurrencies have grown rapidly. Blockchains have been applied in many areas outside of finance such as healthcare, commerce and judiciary already. This technology promotes the creation of a decentralized environment where transactions and data are not under the control of any third-party organization. Blockchain is a fundamentally new technology that could revolutionize the future of transaction-based exchanges. Extensive research is being done in order to implement this technology various sectors. Blockchain technology comes with an edge of inbuilt auditability, trust and transfer of value which also makes it irresistible. \nThis work explores an agent based Blockchain-based Education System through mathematical modeling and simulation tools. The model is constructed to explore how Blockchain technology can be used to verify credit score of students, identify the occurrence and prevention of potential attacks. Along with technical characteristics of Bitcoin and Blockchain; cost, time and behavioural considerations of the system are also made. This is followed by analysing of the number of transactions, size of blockchain, network efficiency, cost analysis of the system along with the network efficiency. The proposed model, based on the blockchain technology shifts the education grading and credit rewarding system from the analog and physical world into a globally efficient, transparent and universal version. The work contributes a foundation for advancing current understanding of blockchain systems, and to further the development of simulation models of blockchains.
The new technological advances have brought a revolution on how economic agents interact with society and markets. Nowadays, the use of virtual currencies is more frequent in the financial transactions and bitcoin has been defined as the most important world cryptocurrency due to its high market capitalization and its technological infrastructure. Several studies have been conducted to discuss bitcoin advantages and disadvantages; however, few papers in literature have examined its connection and influence on the stock market. The objective of this paper is precisely cover this gap. Firstly, by providing tools and concepts to understand bitcoinâs dynamic, and then determining its relationship with stock market indexes. In that context, this manuscript examines the definition and function of bitcoin in the global world and its presence in Ecuador. Besides, exploratory and visual analyses are provided using the evolution of bitcoin and other market indexes. Finally, a linear correlation is computed between bitcoin, other cryptocurrencies, stock exchange indexes and commodities. The results in this study, employing visual and statistical analyses, demonstrated that bitcoin has: a strong relationship with other cryptocurrencies; a lineal correlation, not as strong as the previous one, with the main stock market indexes; and no linear correlation with commodities.
Bitcoin is a decentralized crypto-currency, which is based on the peer-to-peer network, and was introduced by Satoshi Nakamoto in 2008. Bitcoin transactions are written by using a scripting language. The hash value of a transactionâs script is used to identify the transaction over the network. In February 2014, a Bitcoin exchange company, Mt. Gox, claimed that they had lost hundreds of millions US dollars worth of Bitcoins in an attack known as transaction malleability. Although known about since 2011, this was the first known attack that resulted in a company loosing multi-millions of US dollars in Bitcoins. Our reason for writing this paper is to understand Bitcoin transaction malleability and to propose an efficient solution. Our solution is a softfork (i.e., it can be gradually implemented). Towards the end of the paper we present a detailed analysis of our scheme with respect to various transaction malleability-based attack scenarios to show that our simple solution can prevent future incidents involving transaction malleability from occurring. We compare our scheme with existing approaches and present an analysis regarding the computational cost and storage requirements of our proposed solution, which shows the feasibility of our proposed scheme.
Current citation indexes such as Scopus and the Web of Science rely on centralized curation to function. This creates a series of potentially negative incentives, both financial and academic, which could be addressed through the creation of an unpermissioned, distributed ledger of citations. This paper explores this possibility using Bitcoin as a model.
Blockchain technology is ushering in another break-out year, the challenge of blockchain still remains to be solved. This paper analyzes the features of Bitcoin and Bitcoin-NG system based on blockchain, proposes an improved method of implementing blockchain systems by replacing the structure of the original chain with the graph data structure. It was named GraphChain. Each block represents a transaction and contains the balance status of the traders. Additionally, as everyone knows all the transactions in Bitcoin system will be baled by only one miner that will result in a lot of wasted effort, so another way to improve resource utilization is to change the original way to compete for miner to election and parallel mining. Researchers simulated blockchain with graph structure and parallel mining through python, and suggested the conceptual new graph model which can improve both capacity and performance.
Virtual currencies are on the rise and so is money laundering. While there are efforts to combat money laundering through various intergovernmental bodies, many have expressed concern over the rise of virtual currencies. Some cryptocurrencies such as Bitcoin have played a major role in the proliferation of online money laundering as it possesses characteristics that criminals are fond of. Bitcoin and other cryptocurrencies are decentralised, anonymous/pseudonymous and irreversible. They provide the means to skirt the Anti-Money laundering safeguards that have been put in place. \nThis paper discusses the intersection between Anti-Money Laundering efforts and the challenges that are introduced by cryptocurrencies such as Bitcoin. It also looks at the case of Liberty Reserve to highlight these challenges.
In blockchain systems, especially cryptographic currencies such as Bitcoin, the double-spending and Byzantine-general-like problem are solved by reaching consensus protocols among all nodes. The state-of-the-art protocols include Proof-of-Work, Proof-of-Stake and Delegated-Proof-of-Stake. Proof-of-Work urges nodes to prove their computing power measured in hash rate in a crypto-puzzle solving competition. The other two take into account the amount of stake of each nodes and even design a vote in Delegated-Proof-of-Stake. However, these frameworks have several drawbacks, such as consuming a large number of electricity, leading the whole blockchain to a centralized system and so on. In this paper, we propose the conceptual framework, fundamental theory and research methodology, based on artificial intelligence technology that exploits nearly complementary information of each nodes. And we designed a particular convolutional neural network and a dynamic threshold, which obtained the super nodes and the random nodes, to reach the consensus. Experimental results demonstrate that our framework combines the advantages of Proof-of-Work, Proof-of-Stake and Delegated-Proof-of-Stake by avoiding complicated hash operation and monopoly. Furthermore, it compares favorably to the three state-of-the-art consensus frameworks, in terms of security and the speed of transaction confirmation.
Bitcoin is the first implementation of a technology that has become known as a 'public permissionless' blockchain. Such systems allow public read/write access to an append-only blockchain database without the need for any mediating central authority. Instead, they guarantee access, security and protocol conformity through an elegant combination of cryptographic assurances and game theoretic economic incentives. Not until the advent of the Bitcoin blockchain has such a trusted, transparent, comprehensive and granular dataset of digital economic behaviours been available for public network analysis. In this article, by translating the cumbersome binary data structure of the Bitcoin blockchain into a high fidelity graph model, we demonstrate through various analyses the often overlooked social and econometric benefits of employing such a novel open data architecture. Specifically, we show: (i) how repeated patterns of transaction behaviours can be revealed to link user activity across the blockchain; (ii) how newly mined bitcoin can be associated to demonstrate individual accumulations of wealth; (iii) through application of the naĂŻve quantity theory of money that Bitcoin's disinflationary properties can be revealed and measured; and (iv) how the user community can develop coordinated defences against repeated denial of service attacks on the network. Such public analyses of this open data are exemplary benefits unavailable to the closed data models of the 'private permissioned' distributed ledger architectures currently dominating enterprise-level blockchain development owing to existing issues of scalability, confidentiality and governance.