Over the last decade, information technology has contributed significantly to the evolution of financial markets, without, however, revolutionising the way in which financial institutions interact with one another. This may be about to change, as some market players are now predicting that new database technologies, such as blockchain and other distributed ledger technologies (DLTs), could be the source of an imminent revolution. This paper analyses the main features of DLTs that could influence their potential adoption by financial institutions and discusses how the use of these technologies could affect the European post-trade market for securities. The original protocol underlying DLTs has its roots in the anarchic world of virtual currencies, which operate outside the conventional financial system. The public debate on DLTs has also been very much focused on the revolutionary potential of the technology. This paper concludes that, irrespective of the technology used and the market players involved, certain processes that feature in the post-trade market for securities will still need to be performed by institutions. DLTs could, however, stimulate a reorganisation of financial markets, which could in turn: (i) reduce reconciliation costs, (ii) streamline the post-trade value chain, and (iii) allow more efficient use to be made of collateral and regulatory capital. It should, nevertheless, be remembered that research into DLTs and their uses is at an early stage. The scope for financial institutions to adopt DLTs and their potential impact on mainstream financial markets are still unclear. This paper discusses three potential models of how market players could adopt DLTs for performing core post-trade functions. The DLT could be adopted either: (i) in clusters, (ii) collectively, or (iii) peer to peer. The evaluation of the three adoption models assumes that they are all equally compatible with the regulatory framework. It shows that, assuming this to be the case, they would each have different advantages and costs. JEL Classification: G21, G23, L15, O33
Sinclair Davidson, Primavera De Filippi, Jason Potts
Distributed ledger technology, invented for cryptocurrencies, is increasingly understood as a new general-purpose technology for a broad range of economic activities that rely on consensus of a database of transactions or records. However, blockchains are more than just a disruptive new ICT. Rather, they are a new institutional technology of governance that competes with other economic institutions of capitalism, namely firms, markets, networks, and even governments. We present this view of blockchains through a case study of Backfeed, an Ethereum-based platform for creating new types of commons-based collaborative economies.
Giuseppe Ateniese, Bernardo Magri, Daniele Venturi, Ewerton R. Andrade
We put forward a new framework that makes it possible to re-write or compress the content of any number of blocks in decentralized services exploiting the blockchain technology. As we argue, there are several reasons to prefer an editable blockchain, spanning from the necessity to remove inappropriate content and the possibility to support applications requiring re-writable storage, to "the right to be forgotten." Our approach generically leverages so-called chameleon hash functions (Krawczyk and Rabin, NDSS '00), which allow determining hash collisions efficiently, given a secret trapdoor information. We detail how to integrate a chameleon hash function in virtually any blockchain-based technology, for both cases where the power of redacting the blockchain content is in the hands of a single trusted entity and where such a capability is distributed among several distrustful parties (as is the case with Bitcoin). We also report on a proof-of-concept implementation of a redactable blockchain, building on top of Nakamoto's Bitcoin core. The prototype only requires minimal changes to the way current client software interprets the information stored in the blockchain and to the current blockchain, block, or transaction structures. Moreover, our experiments show that the overhead imposed by a redactable blockchain is small compared to the case of an immutable one.
The ‘blockchain’ is the core mechanism for the Bitcoin digital payment system. It embraces a set of inter-related technologies: the blockchain itself as a distributed record of digital events, the distributed consensus method to agree whether a new block is legitimate, automated smart contracts, and the data structure associated with each block. We propose a permanent distributed record of intellectual effort and associated reputational reward, based on the blockchain that instantiates and democratises educational reputation beyond the academic community. We are undertaking initial trials of a private blockchain or storing educational records, drawing also on our previous research into reputation management for educational systems.
We build on economic theory to discuss how blockchain technology can shape innovation and competition in digital platforms. We identify two key costs affected by the technology: the cost of verification and the cost of networking. The cost of verification relates to the ability to cheaply verify state, including information about past transactions and their attributes, and current ownership in a native digital asset. The cost of networking, instead, relates to the ability to bootstrap and operate a marketplace without assigning control to a centralized intermediary. This is achieved by combining the ability to cheaply verify state with economic incentives targeted at rewarding state transitions that are particularly valuable from a network perspective, such as the contribution of the resources needed to operate, scale, and secure a decentralized network. The resulting digital marketplaces allow participants to make joint investments in shared infrastructure and digital public utilities without assigning market power to a platform operator, and are characterized by increased competition, lower barriers to entry, and a lower privacy risk. Because of their decentralized nature, they also introduce new types of inefficiencies and governance challenges.
Steve Huckle, Rituparna Bhattacharya, Martin White, Natalia Beloff
This paper explores how the Internet of Things and blockchain technology can benefit shared economy applications. The focus of this research is understanding how blockchain can be exploited to create decentralised, shared economy applications that allow people to monetise, securely, their things to create more wealth. Shared economy applications such as Airbnb and Uber are well-known applications, but there are many other opportunities to share in the digital economy. With the recent interest in the Internet of Things and blockchain, the opportunity exists to create a myriad of sharing applications, e.g. peer-to-peer automatic payment mechanisms, foreign exchange platforms, digital rights management and cultural heritage to name but a few. While many types of shared economy scenarios are proliferating, few of them, so far, leverage the Internet of Things and blockchain as technologies to build distributed applications. This paper discusses how we might make use of the Internet of Things and blockchains to create secure shared economy distributed applications. Presented are examples of such distributed applications in the context of an Internet of Things architecture using blockchain technology.
Internet of Things (IoT) are being adopted for industrial and manufacturing applications such as manufacturing automation, remote machine diagnostics, prognostic health management of industrial machines and supply chain management. Cloud-Based Manufacturing is a recent on-demand model of manufacturing that is leveraging IoT technologies. While Cloud-Based Manufacturing enables on-demand access to manufacturing resources, a trusted intermediary is required for transactions between the users who wish to avail manufacturing services. We present a decentralized, peer-to-peer platform called BPIIoT for Industrial Internet of Things based on the Block chain technology. With the use of Blockchain technology, the BPIIoT platform enables peers in a decentralized, trustless, peer-to-peer network to interact with each other without the need for a trusted intermediary.
ABSTRACT: Motivated by the recent explosion of interest around Blockchains, we examine whether they make a good t for the Internet of Things (IoT) sector. Blockchains allow us to have a distributed peer-to-peer network where non-trusting members can interact with each other without a trusted intermediary, in a variable manner. We review how this mechanism works and also look into smart contracts scripts that reside on the Blockchain that allow for the automation of multi-step processes. We then move into the IoT domain, and describe how a Blockchain-IoT combination: 1) facilitates the sharing of services and resources leading to the creation of a marketplace of services between devices and 2) allows us to automate in a cryptographically variable manner several existing, time- consuming work owns. We also point out certain issues that should be considered before the deployment of a Blockchain network in an IoT setting: from transactional privacy to the expected value of the digitized assets traded on the network. Wherever applicable, we identify solutions and workarounds. Our conclusion is that the Blockchain-IoT combination is powerful and can cause sign cant transformations across several industries, paving the way for new business models and novel, distributed applications.
Issues of crypto currencies usage in international and domestic financial systems are considered in thearticle. Detailed review of crypto currency stages development in Ukraine and abroad was provided.Analysis of crypto currency nature was made. It was paid attention to the description of basic kinds ofcrypto currencies and specifications of their usage. Process of crypto currency implementation infinancial system of Ukraine was reviewed
Bitcoin, a decentralized cryptocurrency, has attracted a lot of attention from academia, financial service industry and enthusiasts. The trade-off between transaction confirmation throughput and centralization of hash power do not allow Bitcoin to perform at the same level as modern payment systems. Block Advertisement Protocol is proposed as a step to resolve this issue. The protocol allows block mining and block relaying to happen in parallel. The protocol dictates a miner to advertise the block it is going to mine allowing other miners to collect all the transactions in advance. When a block in mined, only header is relayed since most of data about the block is already known to all miners.
This study examines how decentralized finance protocols reshape consumer protection outcomes within blockchain financial markets amid growing global concerns regarding digital transaction security, governance transparency, and institutional regulatory adaptation. Using a balanced longitudinal panel dataset of 1,450 institutional year observations derived from BIS, IMF, OECD, and World Bank digital finance databases covering 2005 to 2014, the study applies fixed effects panel regression, moderation interaction modeling, clustered robust estimation, and multidimensional composite index construction to estimate the structural relationship between decentralized finance systems and consumer protection. The findings reveal that Smart Contract Infrastructure, Decentralized Financial Services, Blockchain Technology Integration, and DeFi Governance Structures exert positive and statistically significant effects on Consumer Protection, while the Digital Regulatory Environment significantly strengthens these relationships through regulatory clarity, cybersecurity readiness, legal enforcement, and digital literacy mechanisms. Interaction estimates further demonstrate that institutional readiness amplifies the protective capacity of decentralized financial ecosystems across heterogeneous digital markets. The study extends institutional governance and financial innovation theory by integrating technological infrastructure, decentralized governance, and adaptive regulatory conditioning into a unified explanatory framework. The findings provide policy relevant evidence for regulators, blockchain developers, and digital financial institutions seeking to strengthen consumer protection within technologically evolving financial ecosystems.
This study investigates how decentralized finance adoption reshaped banking intermediation structures across emerging digital economies during the foundational digital finance expansion period between 2005 and 2014 by evaluating the conditional role of financial technology environments in accelerating institutional financial transformation. Using a balanced panel dataset of 1,760 institutional year observations constructed from harmonized global digital finance repositories, the study applies fixed effects panel regression, interaction-based moderation estimation, heteroskedasticity robust clustered inference, and multidimensional composite index modeling to estimate the structural relationship between decentralized finance adoption and banking disintermediation. The findings reveal that decentralized finance adoption exerted a strong positive and statistically significant effect on banking disintermediation, with blockchain technology integration and digital financial accessibility producing the largest structural effects on non-bank financial participation and intermediary transaction displacement. The results further demonstrate that supportive financial technology environments amplified decentralized finance driven transformation through enhanced digital infrastructure readiness, cybersecurity preparedness, and institutional adaptability. Interaction estimates remained robust across alternative specifications, lagged estimations, and sensitivity diagnostics, confirming stable ecosystem conditioning effects across heterogeneous institutional environments. The study extends financial innovation and institutional transformation theories by integrating utilization, infrastructure, accessibility, and governance systems within a unified decentralized finance architecture. The findings provide globally relevant policy guidance for regulators and digital finance institutions seeking to balance financial innovation, inclusion, and banking system stability within emerging digital economies.
O artigo visa entender quais as possíveis respostas a serem dadas pelo Direito em relação à criação do bitcoin. O trabalho explica, propedeuticamente, e, através da análise da legislação comparada, a história da moeda, suas consequências econômicas, as mudanças paradigmáticas ocorridas e, por fim, reflete sobre as teses doutrinárias apontadas, por parte do mundo jurídico, como solução à criação da moeda. O objetivo geral do trabalho é analisar as consequências econômicas do novo sistema de pagamento, assim como explorar as possíveis hipóteses, para regulamentar as transações com a moeda criptográfica, que permanecem em uma área cinza, ainda não completamente atingida pelo Direito. A conclusão do trabalho é que o Estado deve incluir a moeda em suas regulamentações, inicialmente, lidando apenas com à evasão tributária, com a sua possível ligação com o mercado ilegal e com a licença, para trocar tais moedas e, posteriormente, regulamentar aspectos que requerem uma minúcia maior, como a proteção dos direitos dos consumidores.Palavras-chave: Bitcoin. Criptografia. Regulamentação.
Bitcoin is a relatively new and attractive asset. It is used for peer-to-peer transactions and is built upon an interesting system called the Blockchain which allows for fast and secure transactions between users. Although Bitcoin and its underlying infrastructure show a lot of potential for growth and innovation, many users of the so-called “cryptocurrency” are wary of holding it instead of other currencies such as the U.S. dollar because of the high volatility exhibited in the price of Bitcoin. The goal of this paper is to examine the use of theoretically priced put options, “protective puts”, to hedge against price decreases that Bitcoin may experience. The user of this protective put strategy is considered to be an investor with an optimistic view on the price of Bitcoin and wants to own some, but is uncomfortable with the potential for substantial losses due to price decreases. In implementing the protective put strategy, the price of Bitcoin that the investor owns has a floor at the strike price of the options purchased to hedge the risk of price decreases. If the price increases enough, then the options are sold, and those with the new strike price are bought to lock in a higher protected price for the investor. The investor’s goals are to reduce the risk of losses by owning Bitcoin while its price decreases and to lessen the volatility that his portfolio experiences at the expense of the cost of purchased options eating into potential profits. Upon analysis of both historical and simulated data, utilizing protective puts as a hedging mechanism against decreases in the price of Bitcoin has proven effective at reducing expected volatility and limiting losses. The use of the strategy, when analyzed across different simulated market environments, allows for the capture of price increases while stopping excessive losses. Proportional to an unhedged Bitcoin portfolio, the proposed approach reduces volatility more than it reduces expected percentage gains. Upon analysis, the expected profit is slightly less than 28% lower at around 8% hedged from 11% unhedged. However, the standard deviation of percentages of profits or losses is 53% lower, having decreased from 27.8% to about 13.1%. Bitcoin: A Brief Introduction History, Mechanics and Use of Bitcoin In October of 2008, a mysterious person or group known as Satoshi Nakamoto released a paper detailing a peer-to-peer electronic cash system that would come to be known as Bitcoin (The New York Times 2013). The software behind Bitcoin, called the Blockchain, was innovative because the code allowed transactions to be authenticated and processed without a central bank or government. For years, Bitcoin grew nearly unbeknownst to the mainstream public as it was used mostly to facilitate black market transactions. In April 2013 a price surge in the value of Bitcoin caused the total value of all bitcoins to surpass one billion US dollars–this milestone triggered a media frenzy. Over the past 30 months, the value of a single Bitcoin has continued to be volatile, reaching a peak of over $1,242 US dollars before descending to the current price of around $430 per bitcoin (Coindesk 2015). During this period Bitcoin has been adopted as an accepted form of payment, and notable companies have implemented payments using it including Microsoft and Overstock.com (BitcoinValues 2015). Governments have demonstrated an interest in understanding and regulating Bitcoin. For example, former US Federal Reserve Chairman Ben Bernanke has said that Bitcoin “may hold long-term promise, particularly if the innovations to promote a faster, more secure, and more efficient payment system” (Tracy 2013). Bernanke highlights three key advantages that Bitcoin holds over traditional currencies. Bitcoin transactions theoretically are more secure, faster, and effectively free to facilitate. Not all governments have welcomed the rise of Bitcoin, China’s central bank has prohibited any financial institutions from handling bitcoin transactions (Wilhelm 2014). Bitcoin has attracted speculative investors who seek to capitalize on its volatility and perceived upside. As Bitcoin has become more established as a potential asset, companies have recently begun facilitating the development of Bitcoin options exchanges. Issues Holding Bitcoin Back from Major Adoption Despite the potential that Bitcoin has, many issues hold it back from large-scale adoption. Legality and security are the first two problems that potential investors run into when considering Bitcoin as an investment. These two issues are very gray at the moment, as some countries consider Bitcoin to be a currency while others consider it property and potential gains or losses are taxed differently. Many investors can buy Bitcoin online and hold it in a 3rd party wallet, but most do not have the deep understanding of computer science and cryptography that underlies Bitcoin. Additionally, news of stolen Bitcoin and unknowns about flaws or holes in storage mechanisms can also scare away buyers (Onies, Olayinka, Daniele). Despite these issues, Bitcoin has seen adoption because of its use in payments and also because of the potential that its Blockchain architecture holds for future development. Finally, should an optimistic or informed buyer decide to purchase bitcoins, they should expect the price of the cryptocurrency to be highly volatile. One bitcoin is one bitcoin; however, most people operate under a system where their base currency denomination is not in Bitcoin. The volatility shown in exchange rates is often due to news about acceptance or governmental regulation, in addition to market factors and broader adoption of the technology. The result of this volatility is that should an investor want to redeem his bitcoins for another currency, he may receive much more or much less than was originally spent to acquire them. Bitcoin as an Investment Because of the extraordinary potential that Bitcoin and the Blockchain have shown in recent years, there has been demand for the digital currency as an alternative investment. While reasons for owning it may differ, ranging from holding a different currency, the potential for capital appreciation or to be part of the future, the desire is there. However, there are few people willing to take on the risk of owning bitcoins when the price of the asset is so volatile concerning its exchange rate into US dollars. The Bitcoin market is still nascent and as such proper hedging methods have not been developed yet, requiring investors to accept the risk present in the market. Bitcoin adoption may be much higher in the future if people can have more control over the financial outcomes of their investment through hedging mechanisms (Prior 2015). Hedging a Historical Bitcoin Portfolio Methodology and Goals To test hedging the risk of a buy-and-hold Bitcoin portfolio, the decision was made to use the simple, yet often effective strategy of buying protective put options (CBOE). To evaluate how well the strategy would have worked, the last six months of daily price data for Bitcoin as a test sample. For the put options, European-style options were used, and the strike prices were set at $25.00 intervals. The expiry was placed to be at the end of the six-month period tested. Ten put options were bought (each covering 100 bitcoin) on the first day, as well as 1,000 bitcoins and progress of the hedge was tracked over the six-month period. The purchase of the put options is assumed to have been funded from a pool of cash which can be accessed for the cost of options and it is not tracked separately from the rest of the portfolio, although gain and loss from sales and purchases of puts are. To capture the upside of the investment in Bitcoin, if the price moved high enough to warrant the purchase of a put option at a higher strike price, it was done so. In doing this, the old put was sold to regain some of the cash spent on it because it is no longer required for the hedge. If the price of Bitcoin dropped below the strike price of the options, the price was locked-in at the strike price. The options were held until expiry since they are European-style and cannot be exercised beforehand. This allowed the price of Bitcoin to move until the expiry of the hedge and to possibly not require the use of the put by the time the option’s expiry date arrived. The goal of implementing such a hedging strategy is to reduce the volatility the Bitcoin portfolio experiences and to limit losses, while not sacrificing a majority of upside potential. Due to the high historical volatility of bitcoins, it was sought to determine whether a hedging strategy involving protective put options will limit losses while still allowing for significant upside for the long-term investor who is optimistic about Bitcoin prices and adoption. Simulating Options Prices In order to price the options for the protective put strategy, the Black-Scholes equation was used (Black, Scholes 1973). In order to compute accurate prices for the puts, the following inputs were used: · Risk-free interest rate of 1.00% · Daily price of a bitcoin · Strike price in increments of $25.00 · Days remaining until option expiry · Dividend of zero · Historical volatility of Bitcoin prices, calculated to be 53.40% Put prices were calculated using these inputs by a Visual Basic for Applications (VBA) script inside an Excel sheet, as well as in a column-based format for consistency and compatibility with Palisade Corporation’s Excel add-in for simulation, @Risk. To calculate the volatility to use in the equation, the historical percentage of Bitcoin price changes over the six-month period the experiment was run on was used. To get the yearly volatility, the standard deviation of those values was multiplied by , because Bitcoin trades every day of the year. Assumptions Made During Model Development To streamline model development and simplify the analysis, some theoretical assumptions were made. One major assumption is that there are no transaction costs. Many Bitcoin exchanges charge a fee for placing trades, typically 0.25% of a transaction’s face value Coinbase. Additionally, Bitcoin options exchanges are not up and running yet, so transaction costs for options were omitted as well due to a lack of data and desire for simplicity in determining the efficacy of the protective put hedging strategy. Bitcoin, being considered an alternative currency, is purchased by exchanging another form of currency for it. In the historical scenario and simulations run, Bitcoin is bought with U.S. dollars; however, no currency exchange fees are incorporated, nor are bid or ask spreads. Some exchanges charge a final fee when Bitcoin is converted to another currency or withdrawn from the account. These costs were not built into the model since the premise of this work is based on an optimistic Bitcoin investor who has no desire to withdraw any form of currency from his accounts. Lastly, the options market for U.S. equities will sometimes exhibit mismatched prices or market making spreads. This model assumes that option prices will not be affected by these factors and that they will trade at their fair value as determined by the Black-Scholes equation with inputs specified above. There will be no market impact as liquidity is assumed to be infinite, and there will be no transaction costs per contract or order. Analysis of Historical Results Performance of Puts Over Six-Month Test Period Over the six-month test period evaluated, the protective put strategy worked well. The value of Bitcoin during the evaluation period was relatively volatile, which provided a good scenario for the procedure to be tested against. The price of a bitcoin over the six months chosen can be seen in Figure 1. The price path looks as though it follows a rough sine wave with a five-month wavelength and then spikes up during the sixth month. This study’s goals are to limit the downside of an investment in Bitcoin while retaining most of the upside and reducing the volatility of returns. Regarding accomplishing these, the protective puts worked as planned. During the six-month period, a few different trends seemed apparent based on the price path. During the upwards part of the wave in the price of a bitcoin, the portfolio increased in value, and the downward drag on value was the cost of upgrading puts to their next strike price. This impediment to the portfolio's value is to be expected, as a hedge can be defined as paying a price to reduce uncertainty. When the price went down below that of the strike price of the options owned, the lowest price for the portfolio was capped at the strike price of the options, multiplied by the number of bitcoin owned plus the cost of the options. In this section of time, the options did not expire, allowing the right to sell the bitcoins in the portfolio for a set price moving forward if the portfolio needed to be liquidated. The portfolio remained intact, and the price of bitcoin moved upwards again, allowing puts of an even higher price to be purchased and lock in a higher price for each bitcoin. On the last day, since the price of bitcoin was above the strike price of the puts owned, the puts expired worthless. The effects of the hedge can be seen in Figure 2, where the cost of the portfolio was locked in near the beginning, only increasing when puts were exchanged for others at a higher strike price. The value, however, increased over time and did not have the ability to fall much below the original cost of the portfolio in the worst case scenario of the price of Bitcoin falling through the strike price of the puts. In Figure 3, it can be seen that the volatility of the hedged portfolio is much lower, and the potential for loss was much lower. When compared to the unhedged portfolio’s profit and loss, it is clear that without hedging, selling any time from months three to five would have resulted in a loss, while the hedged portfolio would have allowed the capture of approximately a 20% gain. Reducing the volatility of the portfolio was another goal when using the protective put strategy. Using the historical volatility model to get the volatility for Bitcoin over the six-month period gave a 53.4% yearly volatility. Using the same metrics for the percent changes in the value of the portfolio comprised of Bitcoin and put options, the volatility resulted in a value of 39%. Evaluating solely the volatility of the 1,000 bitcoins owned in the portfolio gave the same result, offering a 39% yearly volatility. As such, the puts did effectively reduce portfolio volatility over the six-month period, while allowing the capture of upside and potentially limiting losses should the price of Bitcoin decreased over the time period examined. Simulation of Bitcoin Portfolio Using Random Walks Methodology To get a better idea of how the protective put strategy would work in different and potentially trending environments, simulated geometric random walks were used to analyze potential price paths of Bitcoin over a period of six months (Nau). 10,000 simulations were run for each random walk scenario and the portfolio and Bitcoin profits and losses in dollars and percentages were analyzed as outputs, as well as portfolio and Bitcoin volatility. Initially, a positive drift was used in the random walk, indicating a general uptrend in the simulated price of Bitcoin. To validate the strategy in multiple types of markets, random walks with negative and null drift were also used. Random Walk with Positive Drift In order to simulate the price of Bitcoin, a geometric random walk with positive drift was initially used. Upon analysis of the natural logarithm of historical price changes represented by , there was a positive drift of value 0.0032 based on the average daily price change percentage with volatility incorporated. Stated symbolically, , where is the drift value calculated and is the standard deviation of the daily changes, of value 0.02808. It is worth noting that the drift may be different based on different windows of time. The ones digits in the formula used represent the size of the time step for each day, as the equation progresses to price from daily. The random walk with positive drift is represented by the equation below, where represents a random perturbation chosen from the standard normal distribution. Unsurprisingly, with the positive drift, the simulated price of a bitcoin trended up, resulting in a mean ending portfolio value of $433,000 given a beginning investment of $228,230 (the cost of 1,000 bitcoin at the starting date of the historical scenario). After incorporating the cost of buying and selling options to hedge the simulated positions, the average profit was 34.2% over the simulated term of six months (Figure 4). Over the same period and using the same inputs, the percentage of profit on the unhedged portfolio was 77% (Figure 5). Comparing the profit and loss percentages to those achieved by the unhedged portfolio, the unhedged portfolio has a much greater return. This return is not surprising since the positive drift term in the random walk equation should result in favorable increases in Bitcoin’s price over the duration of the simulation, making a hedge less necessary in hindsight. A comparison of the standard deviations of the scenarios also reveals the effects of hedging. The standard deviation of the profit and loss percentage for the unhedged portfolio is 69% while the protective puts decreased that same profit and loss standard deviation to 34% for the hedged portfolio. It is clear that the protective put strategy allows an investor to invest with less risk by reducing standard deviations of simulated profit and loss percentages, but the strategy also sacrifices potential return, likely due to the high price of the options due to volatility. Random Walk with Zero Drift While the six-month period analyzed had shown the price of Bitcoin to exhibit an upward trend, this may not be the case in the future. For this reason, random walks of null and negative drift were analyzed as well in order build a better image of what may happen using the protective put strategy in environments of less favorable price paths. The equation used for the random walk with zero drift is: Simulating the random walks using a drift value of zero provided results representative of approximately an equal number of winning and losing price progressions. The average expected profit for the portfolio comprised of put options and bitcoins was slightly less than 1%, with a standard deviation of 16.7%. Examining the chart (Figure 6), it is clear that the protective put strategy had an effect on the outcomes, there are spikes in the histogram of outcomes representing the price floors that the put options created. This shows that the options did indeed limit the losses that could have been experienced in downward trends. The effect of the options can also be seen in the confidence interval. The hedged portfolio had a 90% chance of ending with an expected profit or loss between -19.3% and 33.4%, while the same confidence interval for the unhedged portfolio expected between a -49.8% and 72.8% profit or loss. The unhedged portfolio has a much smoother distribution of outcomes (Figure 7), representing the outcomes of wherever the price of Bitcoin ended during each simulation. The expected loss for the unhedged simulations was approximately zero percent, but with a much higher standard deviation of 39.12%. When comparing the unhedged portfolio to the hedged portfolio, the puts managed to reduce expected losses to about a maximum of 19.3%, while the unhedged portfolio had a 4.9% chance of losing more than half of the initial investment. Expected gains also decreased by over 50%, however this was an expected consequence of the hedging strategy’s option costs. Random Walk with Negative Drift After evaluating random walks with positive and zero drift, for completeness a random walk with negative drift was simulated. For the drift value, -0.0032 was used, since this is the negative counterpart to the positive value used in the random walk with positive drift. When the expected profit is negative, as is the case when the drift implies a downward trend in the simulated price of Bitcoin over time, the benefit of a protective put strategy became most apparent due to limiting losses consistently. The equation used for the random walk with negative drift is as follows: The hedged distribution of profit and loss percentages has some peaks likely representing different strike prices that the options prevented the portfolio from falling under (Figure 8). The mean of the distribution is -11.2%, which is likely attributable to the price of Bitcoin falling to the strike price of the option fairly quickly, but the portfolio was prohibited from dropping any further. The standard deviation of the hedged strategy’s results was a mere 7.4%. Because of these factors, the most lost was 19.3%. There was a 90% chance of earning anywhere from the minimum to 3.4%, although the strategy tended to lose approximately either 19%, 14% or 7% due to the strike prices. Also included in the losses are any increases in the simulated price path resulting in a higher strike price before the options were driven into effect. The unhedged distribution suffered significant losses in the negative drift scenario. Given the bias of the simulated price to trend down, the expected loss was 43.97%, with a standard deviation of 21.98% (Figure 9). In the simulated scenario, there was a 90% probability of losing between 3.9% and 71.9%, with the highest simulated loss being 85.64% although it could theoretically be 100%. When compared to the summary statistics of the hedged portfolio, it is clear that hedging is expected to reduce volatility and expected loss significantly in a situation of negative drift. Combined P&L of Random Walk Scenarios To verify the usefulness of the protective put hedging strategy in reducing expected losses and volatility over different price paths, a simulation was conducted with all three previous random walks. 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In this Note, I will argue that Bitcoin should be categorized and regulated as a commodity. This treatment would be consistent with the economic behavior of Bitcoin’s users and would provide a clearer regulatory path for Bitcoin’s future. Additionally, categorizing Bitcoin as a commodity would provide increased clarity to existing regulatory efforts. Part I of this Note will briefly discuss the basic technological underpinnings of the Bitcoin system. Part II will quickly survey the current regulatory landscape around Bitcoin. Part III will examine Bitcoin’s identity crisis and explain why Bitcoin should not be categorized as a currency or a security—the two other categories vying for Bitcoin’s inclusion. Part IV will explain why Bitcoin is a commodity, and Part V will examine the legal advantages of treating Bitcoin as a commodity. Finally, Part VI will examine how treating Bitcoin as a commodity can provide needed consumer protection regulation in the Bitcoin economy.
<strong>Advanced manufacturing is the use of innovative technology to im prove products or processes. Now-a- days POKA YOKE�S made by new technologies are used for mi stake proofing to achieve � ZERO DEFECT �. Poka Yoke focuses on eliminating the defects of hum an origination by reducing the opportunity for defects. Naturally human beings are not mistake proofed,therefore we can�t eliminate all the mistakes done by human beings. But organization can avoid these mistakes from r eaching to the customer,which is known as a defect in this case. Japanese manufacturing engineer Shig eo Shingo develops the quality assurance technique Poka Yoke. The aim of Poka Yoke is to eliminate de fects in a product by preventing or correcting mistakes as early as possible. A Poka Yoke is d one by using a method that uses sensor or other devices for catching errors that may pass by human beings or operators. Shigeo Shingo defines Poka Yoke as:Poka � �Inadvertent Mistake That Anyone Can Make� [2] and Yoke � �To Prevent or Proof� [1]. Poka -Yoke performs two key operations of ZDQ (Zero D efect Quality) i.e. identifying the defect immediately (Point of Origin Inspection) & quick feedback fo r corrective action. Poka-yoke detects an error,gives a warning,and can shuts down the process. This paper describes the solution on customer complaint of fa ilure of brake in the car due to wrong machining in the TMC (Tandem Master Cylinder). The root ca use is detected by using systematic 8-D method. To overcome this problem we have made a Poka Yoke us ing laser sensor.</strong> <strong>https://www.ijiert.org/paper-details?paper_id=140489</strong>
M. Albrecht, Pooya Farshim, Shuai Han, Dennis Hofheinz · 6 authors
Abstract We provide constructions of multilinear groups equipped with natural hard problems from indistinguishability obfuscation, homomorphic encryption, and NIZKs. This complements known results on the constructions of indistinguishability obfuscators from multilinear maps in the reverse direction. We provide two distinct, but closely related constructions and show that multilinear analogues of the $${\text {DDH}} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>DDH</mml:mtext></mml:math> assumption hold for them. Our first construction is symmetric and comes with a $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>κ</mml:mi></mml:math> -linear map $$\mathbf{e }: {{\mathbb {G}}}^\kappa \longrightarrow {\mathbb {G}}_T$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>e</mml:mi><mml:mo>:</mml:mo><mml:msup><mml:mrow><mml:mi>G</mml:mi></mml:mrow><mml:mi>κ</mml:mi></mml:msup><mml:mo>⟶</mml:mo><mml:msub><mml:mi>G</mml:mi><mml:mi>T</mml:mi></mml:msub></mml:mrow></mml:math> for prime-order groups $${\mathbb {G}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>G</mml:mi></mml:math> and $${\mathbb {G}}_T$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>G</mml:mi><mml:mi>T</mml:mi></mml:msub></mml:math> . To establish the hardness of the $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>κ</mml:mi></mml:math> -linear $${\text {DDH}} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>DDH</mml:mtext></mml:math> problem, we rely on the existence of a base group for which the $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>κ</mml:mi></mml:math> -strong $${\text {DDH}} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>DDH</mml:mtext></mml:math> assumption holds. Our second construction is for the asymmetric setting, where $$\mathbf{e }: {\mathbb {G}}_1 \times \cdots \times {\mathbb {G}}_{\kappa } \longrightarrow {\mathbb {G}}_T$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>e</mml:mi><mml:mo>:</mml:mo><mml:msub><mml:mi>G</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>×</mml:mo><mml:mo>⋯</mml:mo><mml:mo>×</mml:mo><mml:msub><mml:mi>G</mml:mi><mml:mi>κ</mml:mi></mml:msub><mml:mo>⟶</mml:mo><mml:msub><mml:mi>G</mml:mi><mml:mi>T</mml:mi></mml:msub></mml:mrow></mml:math> for a collection of $$\kappa +1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>κ</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math> prime-order groups $${\mathbb {G}}_i$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>G</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:math> and $${\mathbb {G}}_T$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>G</mml:mi><mml:mi>T</mml:mi></mml:msub></mml:math> , and relies only on the 1-strong $${\text {DDH}} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>DDH</mml:mtext></mml:math> assumption in its base group. In both constructions, the linearity $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>κ</mml:mi></mml:math> can be set to any arbitrary but a priori fixed polynomial value in the security parameter. We rely on a number of powerful tools in our constructions: probabilistic indistinguishability obfuscation, dual-mode NIZK proof systems (with perfect soundness, witness-indistinguishability, and zero knowledge), and additively homomorphic encryption for the group $$\mathbb {Z}_N^{+}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msubsup><mml:mi>Z</mml:mi><mml:mi>N</mml:mi><mml:mo>+</mml:mo></mml:msubsup></mml:math> . At a high level, we enable “bootstrapping” multilinear assumptions from their simpler counterparts in standard cryptographic groups and show the equivalence of PIO and multilinear maps under the existence of the aforementioned primitives.
Peer-to-peer networks are often large, collaborative networks where peers can join openly. The essence of a collaborative, distributed system is that every node performs tasks for other nodes. The peers often help in singular interactions and without direct reciprocity. Malicious peers can abuse and freeride the public goods. The network without countermeasures can fall into a tragedy of the commons where no one helps another and everyone takes advantage of the generosity of peers. Only when the reputation of a peer is publicly available at scale and peers trust this reputation can the network escape the problems of freeriding and attain high utility for all participants. This thesis focuses on designing and implementing the first step of a tamper proof reputation system within Tribler. Tribler is a peer-to-peer BitTorrent system developed at the Delft University of Technology. This first step, made by this thesis, is to create MultiChain, a proof-of-concept bookkeeping system. MultiChain tracks the upload and download amounts of peers to eliminate freeriding. Multi-Chain is cryptographically protected and validated. The bookkeeping system has to be scalable to be publicly available and be able to process enough transactions. The system has to work in an asynchronous network. A new design of a distributed data structure that can be used as a ledger is introduced by this thesis. This first step with MultiChain is already more resilient to tampering than previous work, like BarterCast. BarterCast has no security measures against tampering records. The design of MultiChain is to have a chain of blocks for every peer as a ledger. Peers are participants of a peer-to-peer network. A block contains a transaction between two peers. This block is shared and added to both chains. This makes both chains of the peers intertwined and entangled at a shared block. The proposed design abandons the typical global, full ledger. The protocol of creating these blocks between peers is described. The problems faced by MultiChain in an asynchronous network are explained. The thesis proposes how the design can overcome these problems by only allowing atomic operations to be performed on the chain and to introduce unfinished blocks in the chain. The implementation of the design is tested and experimented with within this thesis to validate it to work correctly. Furthermore, a number of weak points are discussed. These weak points have to be addressed in the future to create a tamper proof reputation system.
This paper examines Bitcoin from a legal and regulatory perspective, answering several important questions. \n \nWe begin by explaining what Bitcoin is, and why it matters. We describe problems with Bitcoin as a method of implementing a cryptocurrency. This introduction to cryptocurrencies allows us eventually to ask the inevitable question: is it legal? What are the regulatory responses to the currency? Can it be regulated? \n \nWe make clear why virtual currencies are of interest, how self-regulation has failed, and what useful lessons can be learned. Finally, we produce useful and semi-permanent findings into the usefulness of virtual currencies in general, blockchains as a means of mining currency, and the profundity of Bitcoin as compared with the development of block chain technologies. We conclude that though Bitcoin may be the equivalent of Second Life a decade later, so blockchains may be the equivalent of Web 2.0 social networks, a truly transformative social technology.