Abstract There has been a tremendous growth in cryptocurrencies, which has challenged policy makers around the globe. We obtain millisecond data of some of the most frequently traded cryptocurrencies â bitcoin, ethereum, ripple, litecoin and dash â and two cryptocurrency indices â CRIX and CCI30 â to examine their profitability. Our profitability findings suggest that cryptocurrency traders generate significant profits after considering reasonable transaction costs. We also observe that cryptocurrency market participants can expand and sustain the levels of profitability levels in the subsequent trading activity. Our robustness checks with more recent postâCovid data are consistent with the initial profitability findings, although we observe lower levels of profits for the two indices and weaker profit persistency for all digital assets.
Muhammad Muneem Shabir, Syed Muhammad Danish, Kaiwen Zhang
Video conferencing has become an essential tool for working from home. However, poor audio/video quality resulting from unstable Internet connections undermines the productivity of important tasks. Additionally, the static monetization model for ISP networks, which employs third parties, cannot support on-demand and dynamic Quality-of-Service sessions that are necessary to maximize the Quality-of-Experience (QoE) of video conferencing. To address this, we introduce BlockQoS: Fair Monetization of On-Demand Quality-of-Service using Blockchains. BlockQoS allows clients to request and manage their Quality-of-Service requirements through a blockchain-based platform operating using a smart contract. It implements a decentralized monetization model to eliminate third parties, enforce transparency in service-level agreements (SLAs), and reduce blockchain operating costs by utilizing off-chain billing validated using zero-knowledge proofs (zk-SNARK). Additionally, we propose a Quality-of-Service delivery verification mechanism that enforces service level agreements on the hardware external to the blockchain, and a dynamic evaluation method based on the concept of Nash equilibrium in game theory that prevents malicious behavior by ISPs and users. We implemented BlockQoS over Ethereum with a Ryu controller, zk-SNARK, and SGX. Our experiments show that BlockQoS offers transaction cost reduction of up to 88% (gas cost) and latency reduction of up to 87% compared to the state-of-the-art on-chain solutions.
Blockchain can support the food supply chain in several aspects. Particularly, food traceability and trading across pre-existing contracts can make the supply chain fast, error-free, and support in detecting potential fraud. A proper algorithm, keeping in mind specific geographic, demographic, and additional essential parameters, would let the automated market maker (AMM) supply ample liquidity to pre-determined orders. AMMs are usually run by a set of sequential algorithms called a âsmart contractâ (SM). Appropriate use of SM reduces food waste, contamination, extra or no delivery in due course, and, possibly most significantly, increases traceability. However, SM has definite vulnerabilities, making it less adaptable at times. We are investigating whether they are genuinely vulnerable during stressful periods or not. We considered seven SM platforms, namely, Fabric, Ethereum (ETH), Waves, NEM (XEM), Tezos (XTZ), Algorand (ALGO), and Stellar (XLM), as the proxies for food supply-chain-based smart contracts from 29 August 2021 to 5 October 2022. This period coincides with three stressed events: Delta (Covid II), Omicron (Covid III), and the Russian invasion of Ukraine. We found strong traces of risk transmission, comovement, and interdependence of SM return among the diversified SMs; however, the SMs focused on the food supply chain ended up as net receivers of shocks at both of the extreme tails. All these SMs share a stronger connection in both positive shocks (bullish) and negative shocks (bearish).
The advent of blockchain technology in the development and design of smart internet of things (IoT) systems offers the opportunity to secure and transfer data flow, preserve its integrity, and provide transparent mechanisms for its management. Blockchain has actually attracted applications in vital fields because it provides many advantages over centralized database such as traceability, confidentiality, availability and trust. A private network offers the most secure and peer-restricted environment for big data flow, specifically in IoT ecosystems. An integrated blockchain-IoT ecosystem in which three Raspberry Pi 4 nodes communicate and interact in a closed loop to control smart applications via an Ethereum platform in a secure and an efficiently emulated environment is piloted. The proposed blockchain of things (BCoT) ecosystem adds a new layer to the physical, network and application layers of a typical IoT architecture. The concept of a fully decentralized private Ethereum BCoT network may find applications in several fields that call for the removal of single-point of failure and ensures data integrity and transparency.
Aims: To determine the investment feasibility of evaluating cryptocurrency opportunities as an investment product under the possibility of crypto price valuation selection. The study analyzes three indicators: asset price returns in unrelated time, selection of cryptocurrency investment price weights, and crypto price forward contract opportunities on ARCH-GARCH probability forecasts in the selection of price valuations by individual cryptocurrency prices. Study Design: Quantitative research. Place and Duration of Study: The period from 10 September 2021 to 4 September 2022 using sample data downloaded from the Yahoo Finance website database with metric data retrieval bound in amount, data quantity, or distance relative to writing opportunities to examine the distribution of the amount of research data. Methodology: This study employed Bitcoin (BTC), Ethereum (ETH), and Tether (USDT) cryptocurrencies as the research objects with used panel and multiple regression analysis methodologies and using forecasting the appropriate ARCH and GARCH methods Results: The results show that the prediction of future crypto price selection in BTC and ETH tokens has a probability of 78.6% and 59.6%, respectively. The study highlights the prediction of future BTC and ETH price selection with 79.21% and 78.64% forecast results as found in the ARCH-GARCH(1, 0, 1) technique. Meanwhile, USDT token has no possibility to be forecasted in the future, leaving a 7.3% possibility of crypto price selection under probability by investors in the form of high (or different) price fluctuation inequalities. Conclusion: Conclusions could state that the partial (combined) selection of crypto coin price assessments and individual crypto assets can reduce the expected return from the selection of the asset price so that this form of investment in crypto assets can reduce the level of observation of return on wealth from crypto assets for investors especially in expecting the chance on that investment.
Aims: Cryptocurrency (CC) is a digital currency innovation that has impacted the financial sector's distribution mechanism since December 2013. This research aims to discover a non-linear mathematical Quantum relationship between the escalation of the development of cryptocurrency price fluctuations and prices in CC predictors.
 Study Design: The research uses simulation techniques to operate numerical models that correspond to the process of dynamic observation behavior.
 Place and Duration of Study: Types of crypto chosen based on this research data are Bitcoin (BTC), Ethereum (ETH), USD Coin (USDC), and Binance (BNB). The data collection period coverage is required with a number per week from 2019 to 2021 or 52 weeks.
 Methodology: From the collection of crypto prices that have been selected, there are 157 data samples taken using a systematic sampling strategy with elements that are randomly selected and then followed by the next element from the column on the table after the first choice. The conceptual form of the research background is modeled by a multiple regression term equation which predicts a continuous variable unit as a non-linear mathematical function.
 Results: The results of the research study found that the most prominent altcoins traded in the market are not affected by the price of Bitcoin securities. Percentage-wise, there were 40.33% of factors that influenced the movement of crypto coin price progress, with 59.67% being the remaining limiting factors in the study. Partial results show Bitcoin and altcoin assets have arbitrage potential with significant positives on put option volatility with asset discounting producing negative results and martingale strategies arising from a Hamiltonian perspective.
 Conclusion: By time limitations, BTC and USDC have the most potential in martingale conditions, while the cryptocurrency ETH might be a solution in picking assets with growing values at medium risk. Meanwhile, crypto BNB is an asset that offers new data on many market indices.
In this paper, we investigate the co-dependence and portfolio value-at-risk of cryptocurrencies, with the Bitcoin, Ethereum, Litecoin and Ripple price series from January 2016 to December 2021, covering the crypto crash and pandemic period, using the generalized autoregressive score (GAS) model. We find evidence of strong dependence among the virtual currencies with a dynamic structure. The empirical analysis shows that the GAS model smoothly handles volatility and correlation changes, especially during more volatile periods in the markets. We perform a comprehensive comparison of out-of-sample probabilistic forecasts for a range of financial assets and backtests and the GAS model outperforms the classic DCC (dynamic conditional correlation) GARCH model and provides new insights into multivariate risk measures.
Hyperledger Fabric is a popular permissioned blockchain system that features a highly modular and extensible system for deploying permissioned blockchains which are expected to have a major effect on a wide range of sectors. Unlike traditional blockchain systems such as Bitcoin and Ethereum, Hyperledger Fabric uses the EOV model for transaction processing: the submitted transactions are executed by the endorsing peer, ordered and batched by the ordering services, and validated by the validating peers. Due to this EOV workflow, a well-documented issue that arises is the multi-version concurrency control conflict. This happens when two transactions try to writes and read the same key in the ledger at the same time. Existing solutions to address this problem includes eliminating blocks in favor of streaming transactions, repairing conflicts during the ordering phase, and automatically merging the conflicting transactions using CRDT (Conflict Free Replicated Data) techniques. In this paper, we propose a novel solution called Early Detection for MVCC Conflicts. Our solution detects the conflicting transactions at an early stage of the transaction execution instead of processing them until the validation phase to be aborted. The advantage of our solution is that it detects conflict as soon as possible to minimize the overhead of conflicting transaction on the network resulting in the reduction of the end-to-end transaction latency and the increase of the system's effective throughput. We have successfully implemented our solution in Hyperledger Fabric. We propose three different implementations which realize early detection. Our results show that our solutions all perform better than the baseline Fabric, with our best solution SyncMap which improves the goodput by up to 23% and reduces the latency by up to 80%.
Liang Yang, Rong Jiang, Xuetao Pu, Chenguang Wang · 8 authors
Abstract The centralized storage and centralized authorization approach in medical information systems can lead to data tampering and private information privacy leakage, while the traditional access control model has an overly simple authentication approach, relies excessively on trusted third-party organizations for the enforcement of access control policies, and has low efficiency in processing access requests. To address these problems, this paper proposes an access control model based on the collaboration of blockchain main and side chains, AC-BMS. Firstly, a password-based authentication scheme is designed based on doctorsâ identity information; then Polygon side chain is designed to enhance the storage scalability of the blockchain; finally, the access node information on the main Ethereum chain is located on the side chain, and resources are obtained by executing Roll-up contracts deployed on the side chain. It is confirmed by simulation experiments in Hyperledger Fabric that the access efficiency and throughput of the blockchain access model proposed in this paper are improved when the number of accesses is multiplied, the average access time is saved by 2â3 s, the latency time is floating and stable, and the security, scalability, and availability are enhanced.
In Ethereum, miners are responsible for expanding the blockchain ledger by appending new blocks of transactions in exchange for incentives. Within the current Ethereum incentive mechanism, miners can still receive a significant amount of reward when creating non-full or even empty blocks, despite their negative impact on the system performance. We provide an extensive data-driven analysis of the impact of non-full blocks on the system performance, with the help of the BlockSim simulation tool. We collect the data for 500,000 Ethereum blocks and fit the appropriate probability distributions to the data to provide input suitable for the simulator. We show that the performance of Ethereum can be improved by over 50% if all blocks were filled with transactions. We propose an adjustment to the current Ethereum incentive model to assure the received incentive is always proportional to the block utilization level. Using our proposed approach, the incentive for non-full blocks is significantly reduced, making this behavior less attractive for miners. This implies that miners would be enforced to fill their blocks with transactions, and thus the performance is pushed to its optimal level. We show that our approach can work in practice without any crucial security issues.
NFTs are non-fungible, one-of-a-kind digital assets that are enabled by blockchain technology. Digital encrypted assets known as non-fungible tokens are one-of-a-kind, rare, and impossible to duplicate. A greater variety of use cases, including as digital art, domain names, gaming, collectibles, and others, have been observed recently for NFTs. On a blockchain, like Ethereum, NFTs are created (i.e., minted), and they can be used to confirm ownership of an asset (where it came from, who is the owner, etc.). Data from a joint analysis by Nonfungible.com and L' Atelier BNP Paribas indicates that 2020 In 2018, the overall market value of the NFT market was around $ 338,035,012 with an annual growth rate of 299%. This excludes wash trading and abandoned projects. Some NFTs cost millions of dollars, which is quite expensive. How can the value of NFTs be fairly honestly evaluated is a common question. Let's analyze the history of NFT's evolution before responding to this query.
We propose a new distributed-computing model, inspired by permissionless distributed systems such as Bitcoin and Ethereum, that allows studying permissionless consensus in a mathematically regular setting. Like in the sleepy model of Pass and Shi, we consider a synchronous, round-by-round message-passing system in which the set of online processors changes each round. Unlike the sleepy model, the set of processors may be infinite. Moreover, processors never fail; instead, an adversary can temporarily or permanently impersonate some processors. Finally, processors have access to a strong form of message-authentication that authenticates not only the sender of a message but also the round in which the message was sent. Assuming that, each round, the adversary impersonates less than 1/2 of the online processors, we present two consensus algorithms. The first ensures deterministic safety and constant latency in expectation, assuming a probabilistic leader-election oracle. The second ensures deterministic safety and deterministic liveness assuming irrevocable impersonation and eventually-stabilizing participation. The model is unrealistic in full generality. However, if we assume finitely many processes and that the set of faulty processes remains constant, the model coincides with a practically-motivated model: the static version of the sleepy model.
Internet of Things (IoT) enables communication among objects to collect information and make decisions to improve the quality of life. There are several unresolved security and privacy concerns in IoT due to multiple resource constrained devices, which lead to various cyber attacks. The conventional access control techniques depend on a central authority that further poses privacy and scalability issues in IoT. Various problems with access control in IoT can be resolved to prevent various cyber attacks using the decentralization and immutability properties of the blockchain. This study explored the current research trends in blockchain-enabled secure access control mechanisms and also identifies their applicability in creating reliable access control solutions for IoT. The basic properties of blockchain, such as decentralization, auditability, transparency, and immutability, act as the propulsion that provides integrity and security, disregarding the participation of an external entity. Initially, the application of blockchain was created only for cryptocurrencies but with the introduction of Ethereum, which allows the writiting and execution of smart contracts, applications other than cryptocurrencies are also being created. As various research articles have been written on the usage of different types of blockchains for creating secure access control solutions for IoT, this study intends to find and examine such primary researches as well as come up with a systematic review of various findings. This study perceives the most frequently utilized blockchain for creating blockchain-based access control solutions to prevent various cyber attacks and also discusses the improvement in access control mechanisms using blockchain along with smart contracts in IoT. The present study also discusses the obstacles in building decentralized access control solutions for IoT systems as well as future research areas. For new researchers, this article is a nice place to start and a strong reference point.
Most current cross-blockchain approaches focus on exchanging or transferring tokens between networks. While some concepts foster smart contract invocations across blockchains, they require multiple transactions and operate asynchronously. We present a concept enabling instant smart contract calls by creating synchronized client contracts on arbitrary blockchains. Other smart contracts can query these client contracts on the target blockchain for retrieving information without requiring cross-chain message queues. With this, we reduce the dependency of smart contracts on their host blockchain, as remote contracts become available as read-only instances. The synchronization process does not require trust in the executing intermediary since Merkle proofs based on shared state roots are utilized to guarantee correct execution. We propose a novel concept called transition proofs for efficiently proving the correctness of state updates. The prototypical implementation permits smart contract synchronization between EVM-compatible blockchains. Our evaluation shows the approachâs applicability regarding execution costs and delay. Further, we conduct a case study by synchronizing one of the largest decentralized exchanges deployed to the Ethereum network.
Blockchain technology has been successfully exploited for deploying new economic applications. However, it has started arousing the interest of malicious actors who deliver scams to deceive honest users and to gain economic advantages. Ponzi schemes are one of the most common scams. Here, we present a classifier for detecting smart Ponzi contracts on Ethereum, which can be used as the backbone for developing detection tools. First, we release a labelled data set with 4422 unique real-world smart contracts to address the problem of the unavailability of labelled data. Then, we show that our classifier outperforms the ones proposed in the literature when considering the AUC as a metric. Finally, we identify a small and effective set of features that ensures a good classification quality and investigate their impacts on the classification using eXplainable AI techniques.
Abstract This research presents a decentralised incentiveâbased demand response (DR) program using blockchain technology. Consumers selfâreport baseline to the system operator (SO), the smart contract confirms the validity of the data to execute transactions and finally the validators record the information on the blockchain network. During the DR event, a set of consumers are randomly selected to deliver the required load reduction. The signalled consumer who delivers the load reduction is rewarded, and the nonâcalled consumers who diverge from their reported baseline are penalised. The randomness of choosing the consumers and penalty function restrict the baseline inflation. Here, we create a blockchain network and deploy a smart contract on the Ethereum build platform. A DR event scenario is adopted with residential houses data sets, all consumers report their baseline information to the SO through the Internet and smart meter. The SO calls four users to deliver the essential load reduction according to the probability of choosing a consumer. The smart contract verifies the received information to start transaction execution. We use proof of authority mechanism to select validation nodes from the participants using voting system. They validate each block before adding it to the blockchain. Last, the monetary transactions settle in participants' wallets. Our results confirm that decentralised systems like blockchain can significantly improve transparency, openness, and customer participation in the DR program. Also contributes to the security and privacy of user information with a minimal investment in new infrastructure.
Efficiency is a fundamental property of any type of program, but it is even more so in the context of the programs executing on the blockchain (known as smart contracts). This is because optimizing smart contracts has direct consequences on reducing the costs of deploying and executing the contracts, as there are fees to pay related to their bytes-size and to their resource consumption (called gas). Optimizing memory usage is considered a challenging problem that, among other things, requires a precise inference of the memory locations being accessed. This is also the case for the Ethereum Virtual Machine (EVM) bytecode generated by the most-widely used compiler, \texttt{solc}, whose rather unconventional and low-level memory usage challenges automated reasoning. This paper presents a static analysis, developed at the level of the EVM bytecode generated by \texttt{solc}, that infers write memory accesses that are needless and thus can be safely removed. The application of our implementation on more than 19,000 real smart contracts has detected about 6,200 needless write accesses in less than 4 hours. Interestingly, many of these writes were involved in memory usage patterns generated by \texttt{solc} that can be greatly optimized by removing entire blocks of bytecodes. To the best of our knowledge, existing optimization tools cannot infer such needless write accesses, and hence cannot detect these inefficiencies that affect both the deployment and the execution costs of Ethereum smart contracts.
The Decentralized Autonomous Organization (DAO), a group organized by governance rules programmed on a blockchain, has recently been attracting attention as a novel organizational form. The effectiveness of a DAOâs decentralized governance mechanism and transparency, as secured by its code, has generally been discussed in contrast with traditional stock companies. However, the potential of a DAO for non-profits, which provide goods and services that profit-seeking organizations do not offer, has been less discussed. This paper presents a proof-of-concept implementation to demonstrate the advantages of utilizing a DAO governance framework for non-profits. To this end, this study developed a DAO governance framework incorporating a reputation-based decision-making system, a peer evaluation system, and a transparent, real-time accounting system for the Ethereum blockchain. Most current decentralized governance systems rely heavily on token-based voting using governance tokens with stock-like features. However, there is a need for a voting mechanism beyond token-based voting for non-profits, which do not have owners. Therefore, the developed application applies an existing reputation-based voting mechanism and integrates additional features, such as a membership system with mutual evaluation and a reputation NFT to visualize contributions. Several exemplar demonstrations were conducted to evaluate its key functionalities. This application enabled discussions across the boundary between technology and society in terms of the key aspects of non-profits: i) transparency of finance and governance, ii) participatory governance by diverse stakeholders, and iii) equity and inclusiveness of the consensus mechanism. The results indicated that blockchain technology compensates for a non-profitâs vulnerabilities, and illustrated that the proposed reputation-based governance mechanisms are well-motivated. However, the results also revealed that blockchain-based governance involves as many potential risks and limitations as it brings benefits. Lastly, by providing several possible solutions to these constraints as well as recommendations for future research, this paper contributes to the sustainable development of non-profits as one of the foundations of democratic governance.
(1) Background: As Patient-reported outcome measures face challenges with low response rate on surveys, different incentive mechanism have been proposed to achieve a higher response rate. However, it seems that monetary incentives are the only mechanism with proven effect. Nevertheless, it is less likely to be used than other mechanisms due to the monetary cost. (2) Methods: In this research work, a cryptographic scheme for rewarding patients with cryptographic tokens is developed and implemented on the Ethereum test network. (3) Results: The model is able to distribute decentralised tokens to patients who complete the PROMs in a fair, private, decentralised approach. The token can be further used by patients to exchange more healthcare services, encouraging more patients to participate in PROMs. At the same time, an IER detection method is built to improve the quality of PROMs, avoiding the healthcare provider paying for meaningless PROMs from patients who barely participate for incentives. (4) Conclusions: This work provides an privacy-preserving incentive model to increase the response rate for PROMs surveys. Our model prevents patients providing invalid responses to gain rewards.
<p>The last few years have seen a steep increase in blockchain interoperability research. Most solutions connect public blockchains; hence, the main cross-chain use case is token transfer. By-design platform transparency, tamper-resistance, and auditability make blockchains an infrastructure candidate for Central Bank Digital Currencies (CBDCs), but bridging CBDCs is an important missing piece in general. In this paper, we leverage an asset transfer protocol, ODAP/SATP, to define an extendable and dependable blockchain interoperability middleware that can bridge CBDC from Hyperledger Fabric to EVM-based permissioned blockchains. The key interoperation enabler in the solution is a shared asset definition enforced by both sides of the bridge, accompanied by a mapping between Fabric Identities and Ethereum addresses for Identity management. We implement our design for the CBDC use case utilizing Hyperledger Cactus. Through a preliminary performance evaluation, we show that the underlying ledgers heavily influence the latency of the solution, not the bridging components.</p>
The metaverse gradually evolves into a virtual world containing a series of interconnected sub-metaverses. Diverse digital resources, including identities, contents, services, and supporting data, are key components of the sub-metaverse. Therefore, a Domain Name System (DNS)-like system is necessary for efficient management and resolution. However, the legacy DNS was designed with security vulnerabilities and trust risks due to centralized issues. Blockchain is used to mitigate these concerns due to its decentralized features. Additionally, it supports identity management as a default feature, making it a natural fit for the metaverse. While there are several DNS alternatives based on the blockchain, they either manage only a single type of identifiers or isolate identities from other sorts of identifiers, making it difficult for sub-metaverses to coexist and connect with each other. This paper proposes a Multi-Identifier management and resolution System (MIS) in the metaverse, supporting the registration, resolution, and inter-translation functions. The basic MIS is portrayed as a four-tier architecture on a consortium blockchain due to its manageability, enhanced security, and efficiency properties. On-chain data is lightweight and compressed to save on storage while accelerating reading and writing operations. The resource data is encrypted based on the attributes of the sub-metaverse in the storage tier for privacy protection and access control. For users with decentralization priorities, a modification named EMIS is built on top of Ethereum. Finally, MIS is implemented on two testbeds and is available online as the open-source system. The first testbed consists of 4 physical servers located in the UK and Malaysia while the second is made up of 200 virtual machines (VMs) spread over 26 countries across all 5 continents on Google Cloud.
Fernando Henrique Antunes de Araujo, Leonardo H.S. Fernandes, JOSà W. L. SILVA, Kleber E. S. Sobrinho · 5 authors
Abstract This paper has investigated the predictability of the top ten cryptocurrenciesâ price dynamics, ranked by their daily market capitalization and trade volume, via the information theory quantifiers. Our analysis considers the Complexity-entropy causality plane to study the temporal evolution of the price of these cryptocurrencies and their respective locations along this 2D map, bearing in mind after and during the Russia-Ukraine war. Moreover, we apply the permutation entropy and the Jensen-Shannon statistical complexity measure to rank these cryptocurrencies similarly to a complexity hierarchy. Our findings reflect that the Russian-Ukraine war affects the informational efficiency of cryptocurrency dynamics. Specifically, the cryptocurrencies notably showed a decrease in informational inefficiency (USD-coin, Binance-USD, BNB, Dogecoin, and XRP). At the same time, the cryptocurrencies with more expressiveness for the financial market, considering the volume traded and the capitalized market, were strongly impacted, presenting an increase in informational inefficiency (Tether, Cardano, Ethereum, and Bitcoin). It clarifies the potential of cryptocurrencies to mitigate exogenous shocks and their capability to use with portfolio selection, risk diversification and herding behaviour.
A cryptocurrency payment platform, allows users to transact in cryptocurrencies on a global scale inside a decentralized environment. Ethereumâs native token has been successfully migrated to the main net. The platformâs digital wallet, Ethereum Wallet, allows users to store and manage their digital assets across several platforms, including computers and mobile devices. Blockchain technology has emerged as a game-changer in aftermath of the success of Bitcoin and other cryptocurrencies. Instead of establishing a new blockchain from scratch as the number of current ones rises, decentralized application developers should focus on finding a solution that best suits their needs and the needs of their decentralized apps. The ownership and transferability of digital financial assets known as âcryptocurrenciesâ are guaranteed by decentralized cryptographic technology. The increasing market value and popularity of cryptocurrencies pose a variety of difficulties and concerns for global business and industrial economics. The planned studyâs main purpose is to validate the correctness of Etherium transactions on the blockchain. The accuracy of the suggested work was compared to that of earlier work in this study. The LSTM-based training strategy has been chosen for the planned study. The training and testing of the Etherium transaction were done with and without considerable record filtering. Both modelsâ accuracy was evaluated to ensure the dependability of the hybrid strategy, which combined an LSTM model with a specific filtering mechanism.
Orlando Telles Souza, JoĂŁo VinĂcius de França Carvalho
Purpose This study aims to analyze the efficient market hypothesis (EMH) of cryptocurrencies on multiple platforms by observing whether there is a discrepancy in the levels of efficiency between different exchanges. Additionally, EMH is tested in a multivariate way: whether the prices of the same cryptocurrencies traded on different exchanges are temporally related to each other. ADF and KPSS tests, whereas the vector autoregression model of order p â VAR(p) â for multivariate system. Findings Both Bitcoin and Ethereum show efficiency in the weak form on the main platforms in each market alone. However, when estimating a VAR(p) between prices among exchanges, there was evidence of Granger causality between cryptocurrencies in all exchanges, suggesting that EMH is not adequate due to cross information. Practical implications It is essential to assess the cryptocurrency market in a multivariate way, not only to favor its maturation process, but also to promote a broad understanding of its inherent risks. Thus, it will be possible to develop financial products that are actively managed in a more sophisticated cryptocurrency market. Social implications There is a possibility of performing arbitrage on different exchanges and market assets through cross-exchanges. Thus, emphasizing the need for regulation of exchanges in the digital asset market, as an eventual price manipulation on a single platform can impact others, which generates various distortions. Originality/value This study is the first to find evidence of cross-information for the same (and other) cryptocurrencies among different exchanges.