This project takes several common strategies for algorithmic stock trading and tests them on the cryptocurrency market. The three strategies used are moving average crossover, mean reversion, and pairs trading. Data was collected every five minutes for the top one hundred cryptocurrencies between October 5, 2017, and January 24, 2018. Due to the high volatility of the market, the data includes various market situations. Three noted situations are a rising market, falling market, and relatively stable market. The three strategies were modified to optimally follow each market situation. Modifications include adjusting parameters used in each strategy as well as mixing several strategies or dynamically changing between strategies. In each strategy and with each cryptocurrency, the benchmark against which the algorithm is tested is the market's performance, or what an investor would have after buying and holding. Returns are compared with the buying and holding strategy, and different scenarios are analyzed to determine the risk associated with buying and holding compared with an algorithmic strategy. Results will be taken with the market's actual trends and also with some alternate possible trends to test all market scenarios. A web interface will accompany the presentation, allowing users to test the strategies by entering their own parameters and instantly see the results.
Secret sharing has been study for many years and has had a number of real-word applications. There are several methods to construct the secret-sharing schemes. One of them is based on coding theory. In this work, we construct a secret-sharing scheme that realizes an access structure by using linear codes, in which any element of the access structure can reconstruct the secret key. We prove that our scheme is a multiprover zero-knowledge proof system in the random oracle model, which shows that a passive adversary gains no information about the secret key. Our scheme is also a leakage-resilient secret-sharing scheme (LRSS) in the bounded-leakage model, which remain provably secure even if the adversary learns a bounded amount of leakage information about their secret key. As an application, we propose a new group identification protocol (GID-scheme) from our LRSS. We prove that our GID-scheme is a leakage-resilient scheme. In our leakage-resilient GID-scheme, the verifier believes the validity of qualified group members and tolerates l bits of adversarial leakage in the distribution protocol, whereas for unqualified group members, the verifier cannot believe their valid identifications in the proof protocol.
Decentralized marketplace applications demand fast, cheap and easy-to-use cryptocurrency payment mechanisms to facilitate high transaction volumes. The standard solution for off-chain payments, state channels, are optimized for frequent transactions between two entities and impose prohibitive liquidity and capital requirements on payment senders for marketplace transactions. We propose PayPlace, a scalable off-chain protocol for payments between consumers and sellers. Using PayPlace, consumers establish a virtual unidirectional payment channel with an intermediary operator to pay for their transactions. Unlike state channels, however, the PayPlace operator can reference the custodial funds accrued off-chain in these channels to in-turn make tamper-proof off-chain payments to merchants, without locking up corresponding capital in channels with merchants. Our design ensures that new payments made to merchants are guaranteed to be safe once notarized and provably mitigates well-known drawbacks in previous constructions like the data availability attack and ensures that neither consumers nor merchants need to be online to ensure continued safety of their notarized funds. We show that the on-chain monetary and computational costs for PayPlace is O(1) in the number of payment transactions processed, and is near-constant in other parameters in most scenarios. PayPlace can hence scale the payment throughput for large-scale marketplaces at no marginal cost and is orders of magnitude cheaper than the state-of-art solution for non-pairwise off-chain payments, Zero Knowledge Rollups.
Benedict J. Drasch, Gilbert Fridgen, Tobias Manner-Romberg, Fenja M. Nolting · 5 authors
Abstract Multi-sided platforms are omnipresent in today’s digital world. However, establishing a platform includes challenges: The platform utility usually increases with the number of participants. At an early stage, potential participants expect the platform utility to be low and lack an incentive to join (i.e., “chicken and egg” problem). Blockchain-enabled utility tokens hold the promise to overcome this problem. They supposedly provide a suitable financial incentive for their owners to join the platform as soon as possible. In the first half of 2018, investors seemed to believe in the presumption and spent more than US$ 17.6 billion in token sales. To date, we know little about this financial incentive in the context of the token economy. For this purpose, we model the token value development and the associated incentives in a multi-sided blockchain-enabled platform. The resulting findings suggest that blockchain-enabled utility tokens can help to overcome the “chicken and egg” problem. However, these tokens lead to contradictory incentives for platform participants, and can even inhibit platform usage. The contribution of our work is twofold: First, we develop one of the first models for token value development. Second, our research contributes to a deeper understanding of the utility token’s financial incentive.
Son yıllarda, bloglar, tweet’ler, forumlar, e-postalar gibi Web 2.0 hizmetleri iletişim kanalı olarak yaygın bir şekilde kullanılmaktadır. Ayrıca sosyal medya; gerek bilgi paylaşımı gerekse istek, şikayet ve dilekler gibi görüşleri belirtmenin en kolay ve en güncel yolu olarak düşünülmektedir. Sosyal medyanın, birçok alana olduğu gibi Bitcoin fiyatlarına olan etkisi de son yıllarda tartışılmaktadır. Bitcoin yıllardır üzerinde durulan ve popülerliği her geçen gün artan bir yatırım aracıdır. Merkezi olmayan bir elektronik para birimi sistemi olan Bitcoin, çok sayıda kullanıcının ilgisini çeken, finansal sistemlerdeki köklü bir değişikliği ifade etmektedir. Bu çalışmada sosyal medyanın, özellikle Twitter kanalından elde edilen tweet’ler bazında, Bitcoin fiyatı ile etkileşimi ortaya konulmuştur. Bunun için 06.10.2018-19.05.2019 tarihleri arasında Twitter kullanıcıları tarafından atılan toplam 2.819.784 tweet üzerinden makine öğrenmesi yöntemlerinden sınıflandırma algoritmaları kullanılarak çeşitli analizler gerçekleştirilmiştir. Bulgular değerlendirildiğinde metin sınıflandırmada %90 ile en yüksek doğruluk oranına sahip olan Yapay Sinir Ağları kullanılmıştır. Ayrıca Bitcoin fiyatları ve sınıflandırılmış olumlu/olumsuz tweet oranları ile ikili korelasyon yapılmıştır. Elde edilen 0,681 korelasyon katsayısı ile pozitif yönde orta üstü kuvvetli ilişki tespit edilmiştir.
In recent years, smart contracts have suffered major exploits, cost- ing millions of dollars. Unlike traditional programs, smart contracts are deployed on a blockchain. As such, they cannot be modified once deployed. Though various tools have been proposed to detect vulnerable smart contracts, the majority fails to protect vulnera- ble contracts that have already been deployed on the blockchain. Only very few solutions have been proposed so far to tackle the issue of post-deployment. However, these solutions suffer from low precision and are not generic enough to prevent any type of attack. In this work, we introduce ÆGIS, a dynamic analysis tool that protects smart contracts from being exploited during runtime. Its capability of detecting new vulnerabilities can easily be extended through so-called attack patterns. These patterns are written in a domain-specific language that is tailored to the execution model of Ethereum smart contracts. The language enables the description of malicious control and data flows. In addition, we propose a novel mechanism to streamline and speed up the process of managing attack patterns. Patterns are voted upon and stored via a smart contract, thus leveraging the benefits of tamper-resistance and transparency provided by the blockchain. We compare ÆGIS to current state-of-the-art tools and demonstrate that our solution achieves higher precision in detecting attacks. Finally, we perform a large-scale analysis on the first 4.5 million blocks of the Ethereum blockchain, thereby confirming the occurrences of well reported and yet unreported attacks in the wild.
This work is about the mutual influence between two technologies: Databases and Blockchain. It addresses two questions: 1. How the database technology has influenced the development of blockchain technology?, and 2. How blockchain technology has influenced the introduction of new functionalities in some modern databases? For the first question, we explain how database technology contributes to blockchain technology by unlocking different features such as ACID (Atomicity, Consistency, Isolation, and Durability) transactional consistency, rich queries, real-time analytics, and low latency. We explain how the CAP (Consistency, Availability, Partition tolerance) theorem known for databases influenced the DCS (Decentralization, Consistency, Scalability) theorem for the blockchain systems. By using an analogous relaxation approach as it was used for the proof of the CAP theorem, we postulate a "DCS-satisfiability conjecture." For the second question, we review different databases that are designed specifically for blockchain and provide most of the blockchain functionality like immutability, privacy, censorship resistance, along with database features.
William Chien, Josenor de Jesus, Ben Taylor, Victor Dods · 7 authors
Purpose: As part of the FDA’s DSCSA Pilot Project Program, UCLA and its solution partner, LedgerDomain (collectively referred to as the team hereafter), focused on building a complete, working blockchain-based system, BRUINchain, which would meet all the key objectives of the Drug Supply Chain Security Act (DSCSA) for a dispenser operating solely on commercial off-the-shelf (COTS) technology. Methods: The BRUINchain system requirements include scanning the drug package for a correctly formatted 2D barcode, flagging expired product, verifying the product with the manufacturer, and quarantining suspect and illegitimate products at the last mile: pharmacist to patient, the most complex area of the drug supply chain. The authors demonstrate a successful implementation where product-tracing notifications are sent automatically to key stakeholders, resulting in enhanced timeliness and reduction in paperwork burden. At the core of this effort was a blockchain-based solution to track and trace changes in custody of drug. As an immutable, time-stamped, near-real-time (50-millisecond latency), auditable record of transactions, BRUINchain makes it possible for supply chain communities to arrive at a single version of the truth. BRUINchain was tested with real data on real caregivers administering life-saving medications to real patients at one of the busiest pharmacies in the United States. Results: In addition to communicating with the manufacturer directly for verification, BRUINchain also initiated suspect product notifications. During the study, a 100% success rate was observed across scanning, expiration detection, and counterfeit detection; and paperwork reduction from approximately 1 hour to less than a minute. The authors demonstrate a successful implementation where product-tracing notifications are sent automatically to key stakeholders, resulting in enhanced timeliness and reduction in paperwork burden. At the core of this effort was a blockchain-based solution to track and trace changes in custody of drug. As an immutable, time-stamped, near-real-time (50-millisecond latency), auditable record of transactions, BRUINchain makes it possible for supply chain communities to arrive at a single version of the truth. BRUINchain was tested with real data on real caregivers administering life-saving medications to real patients at one of the busiest pharmacies in the United States. Conclusions: By automatically interrogating the manufacturer’s relational database with our blockchain-based system, our results indicate a projected DSCSA compliance cost of 17 cents per unit, and potentially much more depending on regulatory interpretation and speed of verification. We project that this cost could be reduced with manufacturers’ adoption of a highly performant, fully automated end-to-end system based on digital ledger technology (DLT). In an examination of the interoperability of such a system, we elaborate on its capacity to enable verification in real time without a human in the loop, the key feature driving lower compliance cost. With 4.2 billion prescriptions being dispensed each year in the United States, DLT would not only reduce the projected per-unit cost to 13 cents per unit (saving $183 million in annual labor costs), but also serve as a major bulwark against bad or fraudulent transactions, reduce the need for safety stock, and enhance the detection and removal of potentially dangerous drugs from the drug supply chain to protect U.S. consumers.
Cases of introducing token economy in designs of ICT services are increasing. Users in the early stages of the service are expected to participate in and be active in the service by expecting future price increases in that cryptocurrency. However, the volatility of cryptocurrencies is always intense, and the large volatility may cause users to be more interested in price changes than service activities, which diminishes the incentives for the service activities. In this study, in order to dampen the volatility of cryptocurrencies at the initial stage of their service launch, we assume the case where the service providers make bids to suppress the price changes based on the funds obtained from ICO, and conduct analysis using simulations in artificial market. In order to reproduce the actual price movement in the artificial market, we built an agent model that has the same stylized facts as the price movement of newly listed cryptocurrencies. Then, we introduced a price stabilization agent, and obtained a parameter set that reduces price volatility while suppressing the change in the slope of a simple linear regression compared to the original state using an optimization method. As a result, by introducing the price stabilization agent, we found a parameter set that can reduce the standard division of percentage changes by about 14% from the original price movement, and keep the slope of the simple linear regression trend at a 3.5% change.
Shahar Somin, Yaniv Altshuler, Goren Gordon, Alex Pentland · 5 authors
Global financial crises have led to the understanding that classical econometric models are limited in comprehending financial markets in extreme conditions, partially since they disregarded complex interactions within the system. Consequently, in recent years research efforts have been directed towards modeling the structure and dynamics of the underlying networks of financial ecosystems. However, difficulties in acquiring fine-grained empirical financial data, due to regulatory limitations, intellectual property and privacy control, still hinder the application of network analysis to financial markets. In this paper we study the trading of cryptocurrency tokens on top of the Ethereum Blockchain, which is the largest publicly available financial data source that has a granularity of individual trades and users, and which provides a rare opportunity to analyze and model financial behavior in an evolving market from its inception. This quickly developing economy is comprised of tens of thousands of different financial assets with an aggregated valuation of more than 500 Billion USD and typical daily volume of 30 Billion USD, and manifests highly volatile dynamics when viewed using classic market measures. However, by applying network theory methods we demonstrate clear structural properties and converging dynamics, indicating that this ecosystem functions as a single coherent financial market. These results suggest that a better understanding of traditional markets could become possible through the analysis of fine-grained, abundant and publicly available data of cryptomarkets.
Onno W. Purbo, Sriyanto Sriyanto, Suhendro Suhendro, RZ Abdul Aziz · 5 authors
In this paper, we report the benchmarking results of Hyperledger, a Distributed Ledger, which is the derivation Blockchain Technology. Method to evaluate Hyperledger in a limited infrastructure is developed. Themeasured infrastructure consists of 8 nodes with a load of up to 20000 transactions/second. Hyperledger consistently runs all evaluation, namely, for 20,000 transactions, the run time 74.30s, latency 73.40ms latency, and 257 tps. The benchmarking of Hyperledger shows better than a database system in a high workload scenario. We found that the maximum size data volume in one transaction on the Hyperledger network is around ten (10) times of MySQL. Also, the time spent on processing a single transaction in the blockchain network is 80-200 times faster than MySQL. This initial analysis can provide an overview for practitioners in making decisions about the adoption of blockchain technology in their IT systems.
The purpose of this work was to perform a network analysis on the rapidly\ngrowing bitcoin transaction network. Using a web-socket API, we collected data\non all transactions occurring during a six hour window. Sender and receiver\naddresses as well as the amount of bitcoin exchanged were record. Graphs were\ngenerated, using R and Gephi, in which nodes represent addresses and edges\nrepresent the exchange of bitcoin. The six hour data set was subsetted into a\none and two hour sampling snapshot of the network. We performed comparisons and\nanalysis on all subsets of the data in an effort to determine the minimum\nsampling length that represented the network as a whole. Our results suggest\nthat the six hour sampling was the minimum limit with respect to sampling time\nneeded to accurately characterize the bitcoin transaction network.Anonymity is\na desired feature of the blockchain and bitcoin network however, it limited us\nin our analysis and conclusions we drew from our results were mostly inferred.\nFuture work is needed and being done to gather more comprehensive data so that\nthe bitcoin transaction network can be better analyzed.\n
In recent years, smart contracts have suffered major exploits, costing\nmillions of dollars. Unlike traditional programs, smart contracts are deployed\non a blockchain. As such, they cannot be modified once deployed. Though various\ntools have been proposed to detect vulnerable smart contracts, the majority\nfails to protect vulnerable contracts that have already been deployed on the\nblockchain. Only very few solutions have been proposed so far to tackle the\nissue of post-deployment. However, these solutions suffer from low precision\nand are not generic enough to prevent any type of attack.\n In this work, we introduce {\\AE}GIS, a dynamic analysis tool that protects\nsmart contracts from being exploited during runtime. Its capability of\ndetecting new vulnerabilities can easily be extended through so-called attack\npatterns. These patterns are written in a domain-specific language that is\ntailored to the execution model of Ethereum smart contracts. The language\nenables the description of malicious control and data flows. In addition, we\npropose a novel mechanism to streamline and speed up the process of managing\nattack patterns. Patterns are voted upon and stored via a smart contract, thus\nleveraging the benefits of tamper-resistance and transparency provided by the\nblockchain. We compare {\\AE}GIS to current state-of-the-art tools and\ndemonstrate that our solution achieves higher precision in detecting attacks.\nFinally, we perform a large-scale analysis on the first 4.5 million blocks of\nthe Ethereum blockchain, thereby confirming the occurrences of well reported\nand yet unreported attacks in the wild.\n
Advanced smart grid technologies enable energy prosumers to trade surplus energy from their distributed renewable energy sources with other peer prosumers through peer-to-peer (P2P) energy trading. In many previous works, P2P energy trading was facilitated by blockchain technology through blockchain’s distributive nature and capacity to run smart contracts. However, the feature that all the data and transactions on a blockchain are visible to all blockchain nodes may significantly threaten the privacy of the parties participating in P2P energy trading. There are many previous works that have attempted to mitigate this problem. However, all these works focused on the anonymity of participants but did not protect the data and transactions. To address this issue, we propose a P2P energy trading system on a blockchain where all bids are encrypted and peer matching is performed on the encrypted bids by a functional encryption-based smart contract. The system guarantees that the information encoded in the encrypted bids is protected, but the peer matching transactions are performed by the nodes in a publicly verifiable manner through smart contracts. We verify the feasibility of the proposed system by implementing a prototype composed of smart meters, a distribution system operator (DSO) server, and private Ethereum blockchain.
Robert G. Werner, Sebastian Lawrenz, Andreas Rausch
In recent years, cryptocurrencies have become more and more popular and the growing adoption has led to an increasing number of financial transactions being stored on the blockchain. Although cryptocurrencies have built a reputation as an anonymous means of payment, they are usually rather pseudonymous, transparent and everlasting logbooks about financial transactions, which are publicly available. Thus, analyzing a crypto address can reveal payment partners, money flows, behavior patterns and more. In this work, a program is presented, which provides an analysis of this kind and displays the results in a simple format. The technical properties of the blockchain that this analysis is based on are explained. This paper explains the possible impact of total transparency on the blockchain and our tool on our society.
While the digital layer of social interaction continues to evolve, the recently proclaimed hopes in the development of digital identity could be both naïf and dangerous. Rather than just asking ourselves how we could digitize existing features of identity management, and corresponding financial transactions on a community or state level, we submit that truly useful and innovative digital identities need to be accompanied by some significant rethinking of the essential basics behind the organization of the world. Once digital technologies leave the realm of purely on-line or deeply local projects, the confrontation with the world of citizenship’s biases and the random distribution of rights and duties precisely on the presumption of the lack of any choice and absolute pre-emption of any disagreement comes into a direct conflict with all the benefits Distributed Ledger Technology purports to enable. Some proponents of Distributed Ledger Technology-based identity systems envisage ‘cloud communities’ with truly ‘self-sovereign’ individuals picking and choosing which communities they belong to. We rather see a clear risk that when implemented at the global scale, digital identity systems could be deeply harmful, reinforcing and amplifying the most repugnant aspects of contemporary citizenship. In this contribution we present a categorization of existing digital identity systems from a governance perspective, and discuss it on basis of three corresponding case studies which allow us to infer opportunities and limitations of Distributed Ledger Technology based identity. Subsequently, we put our findings in the context of existing preconditions of citizenship law, and conclude with a suggestion of a combination of several tests which we propose to avoid the plunge into a neo-feudal ‘brave new world’. We would like to draw attention to the perspective that applying digital identity without rethinking the totalitarian assumptions behind the citizenship status will result in perfecting the current inequitable system, which is a move away from striving towards justice and a more dignified future of humanity. We see the danger that those might be provided with plenty of opportunities who already do not lack such under current governance structures, while less privileged individuals will witness their already weak position becoming increasingly worse.
Permissioned blockchains are becoming popular as data management systems in the enterprise setting. Compared to traditional distributed databases, blockchain platforms provide increased security guarantees but significantly lower performance. Further, these platforms are quite expensive to run for the low throughput they provide. The following are two ways to improve performance and reduce cost: (1) make the system utilize allocated resources efficiently; (2) allow rapid and dynamic scaling of allocated resources based on load. We explore both of these in this work. We first investigate the reasons for the poor performance and scalability of the dominant permissioned blockchain flavor called Execute-Order-Validate (EOV). We do this by studying the scaling characteristics of Hyperledger Fabric, a popular EOV platform, using vertical scaling and horizontal scaling. We find that the transaction throughput scales very poorly with these techniques. At least in the permissioned setting, the real bottleneck is transaction processing, not the consensus protocol. With vertical scaling, the allocated vCPUs go under-utilized. In contrast, with horizontal scaling, the allocated resources get wasted due to redundant work across nodes within an organization. To mitigate the above concerns, we first improve resource efficiency by (a) improving CPU utilization with a pipelined execution of validation & commit phases; (b) avoiding redundant work across nodes by introducing a new type of peer node called sparse peer that selectively commits transactions. We further propose a technique that enables the rapid scaling of resources. Our implementation - SmartFabric, built on top of Hyperledger Fabric demonstrates 3x higher throughput, 12-26x faster scale-up time, and provides Fabric's throughput at 50% to 87% lower cost.
While technology is playing an increasingly important role in courtrooms around the world, Chinese courts are adopting and experimenting with deep technologies at a much faster pace and on a greater scale than their counterparts in most other countries. In recent years, Chinese courts have seen major developments in online dispute resolution platforms, specialized Internet courts, and the wide use of AI tools across case management, dispute resolution and adjudication processes in personal injury claims. Other novel technologies such as distributed ledgers, blockchain and smart contracts solutions are currently being developed and rolled out in several local and specialised courts. The Chinese leadership has established a policy framework of “Smart Courts” with the aims of enhancing judicial efficiency, transparency, and effectiveness. This article provides an overview of how Chinese courts have swiftly embraced the adoption of new technologies under this framework over the past few years, with consideration of how Smart Courts may handle personal injury claims.
Social enterprises (SEs) have been active for some decades and have been regulated by law in several countries. Their operation showed ability to complement the provision of welfare services, especially social services, by the public sector and private enterprises, and to innovate in the introduction of new services, organizational and managerial models. In some cases, SEs succeeded in producing and innovating in an autonomous way, without depending on public financial support and procurement agreements. This paper starts from the state of the art in the study of SEs to propose different avenues through which they can be able to expand supply of welfare services and contribute to the decentralization of welfare systems. It traces these specific abilities to SEs’ peculiar institutional structure, especially their non-profit nature, the pursuit of public benefit and social missions, and multi-stakeholder governance. This last feature is considered the most remarkable emerging characteristic in the evolution of this organizational form. The paper then proceeds to focus on price discrimination as specific governance mechanism of the relations of production and exchange, involving different stakeholders and allowing SEs to widen their supply of services, achieve financial sustainability and contribute to the decentralization of the welfare system.
Finansal piyasaların ilgi noktasını oluşturan kripto para birimlerinden bitcoin’in para birimi olarak yayılması ve kullanılmasından sonra herkesin aklında, bitcoin’in bir yatırım aracı olarak ya da hedge enstrümanı olarak değerlendirilip değerlendirilemeyeceği sorusu yer almaya başlamıştır. Çalışmada kripto para birimlerinden en çok işlem hacmine sahip olan bitcoin’in alternatif yatırım araçları arasında uzun dönemli ilişkilerini ortaya koymak için istatistiki analiz yapılmış ve bununla ilgili bulgular tartışılmıştır. Birçok kripto para olmasına karşın Bitcoin’in her açısından önde gelmesi nedeniyle, bitcoin ile alternatif yatırım araçları arasında bir eş bütünleşmenin olup olmadığı ARDL testi ile ortaya koyulmaya çalışılmıştır. Çalışmada Bitcoin ile alternatif yatırım araçları arasında geniş kapsamda ele alan salt bir çalışma görülmediğinden dolayı bu çalışmanın yapılmasına karar verilmiştir.
Although societies are becoming increasingly secularized, religion continues to play an important role worldwide. However, few studies have focused on how religion affects the entrepreneurial emergence novel markets. To address this gap, I examine the impact of Islam, as a decentralized belief system, on entrepreneurship in the context of developing Islamic investment fund markets across countries. I focus on religious diversity within Islam as an instance of intrainstitutional complexity and analyze a country-level panel dataset of Islamic investment funds in addition to complementary qualitative data. Intriguingly, I find that religious diversity within Islam plays a paradoxical role: it promotes the entrepreneurial supply of Islamic investment funds in a country, but it also reduces the investor demand for these funds. This complex effect is moderated by interinstitutional forces: the market logic positively moderates the effect on supply dynamics, whereas the state logic negatively moderates the effect on supply and positively that on demand. This study contributes to the research on religion and market emergence, institutional complexity, and Islamic finance.
Stephen Dipple, Abhishek Choudhary, James Flamino, Bolesław K. Szymański · 5 authors
Abstract The growing interconnectivity of socio-economic systems requires one to treat multiple relevant social and economic variables simultaneously as parts of a strongly interacting complex system. Here, we analyze and exploit correlations between the price fluctuations of selected cryptocurrencies and social media activities, and develop a predictive framework using noise-correlated stochastic differential equations. We employ the standard Geometric Brownian Motion to model cryptocurrency rates, while for social media activities and trading volume of cryptocurrencies we use the Geometric Ornstein-Uhlenbeck process. In our model, correlations between the different stochastic variables are introduced through the noise in the respective stochastic differential equation. Using a Maximum Likelihood Estimation on historical data of the corresponding cryptocurrencies and social media activities we estimate parameters, and using the observed correlations, forecast selected time series. We successfully analyze and predict cryptocurrency related social media and the cryptocurrency market itself with a reasonable degree of accuracy. In particular, we show that our method has impressive accuracy in predicting whether a cryptocurrency market will increase or decrease a day in the future, a significant result with regards to investing and trading cryptocurrencies.
Jéssica Paule-Vianez, Camilo Prado Román, Raúl Gómez-Martínez
Purpose The goal of this work is to determine whether Bitcoin behaves as a safe-haven asset. In order to do so, the influence of Economic Policy Uncertainty (EPU) on Bitcoin returns and volatility was studied. Design/methodology/approach It is evaluated whether, when compared with the evolution of EPU, Bitcoin's returns and volatility show behaviours typical of safe havens or rather, those of conventional speculative assets. When faced with an increase in EPU, safe havens – such as gold – can be expected to increase their returns and volatility, while conventional speculative assets will increase their volatility and reduce their returns. This study uses simple linear regression and quantile regression models on a daily data sample from 19 July 2010 to 11 April 2019, to analyse the influence of EPU on the returns and volatility of Bitcoin and gold. Findings Bitcoin's returns and volatility increase during more uncertain times, just like gold, showing that Bitcoin acts not only as a means of exchange but also shows characteristics of investment assets, specifically of safe havens. These findings provide useful information to investors by allowing Bitcoin to be considered as a tool to protect savings in times of economic uncertainty and to diversify portfolios. Originality/value This study complements and expands current research by aiming to answer the question of whether Bitcoin is a simple speculative asset or a safe haven. The most significant contribution is to show that Bitcoin is not a mere speculative asset but behaves like a safe haven.