Blockchain Papers

Andrew Hencic, Christian Gouriéroux

No abstract is available for this record.

Gerald P. Dwyer

No abstract is available for this record.

G. N. Vinogradova

The main subject of this thesis is a paradigm of instability and stabilization in coalition forming among countries as rational actors, presented through a Statistical Physics inspired model.This is an interdisciplinary work involving the fields of applied mathematics and sociophysics, as well as the political applications in the real cases from past and present. Applied to political,economic and social problems, the models can be used to analyze a wide variety of real cases -- international alliances, economic or business alliances, coalitions of political parties, socialnetworks, and organizational structures.In the first part of this thesis we present and analyze the coalition forming and the instability among rational actors coupled with pairwise static historical propensity bonds that have evolvedindependently. Such organization leads to discordant associations into coalitions and the instability as a consequence of decentralized maximization of the individual benefits gained fromjoining or leaving the coalitions. We define Natural Model of coalition forming and address the questions of instability and stabilization among actors possessing different levels of rationality. The framework presented here allows to analytically calculate the optimal and non-optimal stable configurations of actors' coalitions. We then investigate the coalition forming and the stabilization under the influence of externally-set opposing global alliances, which are represented in Global Alliance Model. The stabilization is produced through new cooperations based on the effect of polarization of several distinct interests shared by actors, which generates interest-based propensities and enables a planned coalition forming. We then investigate the effect of dissolution of a global alliancewhich, together with the competing alliance, has previously generated stable coalitions.A special section of the thesis is devoted to investigation and illustration of coalition forming in real historical cases. This part presents the analysis of unstable coalitions in Europe - cycling in the England-Spain-France conflicting triangle and creation of the Italian state, as well as of the remarkable historical cases of the Soviet global alliance collapse, of the recent internal conflict in Syria, and of the "paradoxical stability" in the Eurozone.In the second part of this thesis, we present a simulation of the coalition forming models. The simulation allows to follow graphically the coalition forming processes. We present the methodology used in the simulation, as well as its application in the illustration of coalition forming in the prototypes of real case systems. Given exact propensity values, which is fairly consideredto be the most difficult part of coalition forming modeling, the simulation tool can be used to predict optimal and non-optimal spontaneous stabilizations and globally motivated stabilities inreal cases.An independent part of the thesis is devoted to the subject of viability correction in dynamic network of actors. The model is a finite set of autonomous actors with states that evolveindependently and connected into a network via their connection operators, which evolve independently as well. The network is defined to be viable if a joint evolution satisfies the centralized scarcity constraints set by the environment. In order to restore the viability of these decentralized dynamics, we apply to the method of correction by viability multipliers used in Viability Theory, where the multipliers play the role of decentralizing prices. Standing apart from the main course of the thesis, the subject of viability correction in dynamic network of actors suggests an interesting theoretic dynamical generalization of coalition stabilization in our models inspired from Statistical Physics.

Dániel Kondor, István Csabai, János Szüle, Márton Pósfai · 5 authors

A main focus in economics research is understanding the time series of prices of goods and assets. While statistical models using only the properties of the time series itself have been successful in many aspects, we expect to gain a better understanding of the phenomena involved if we can model the underlying system of interacting agents. In this article, we consider the history of Bitcoin, a novel digital currency system, for which the complete list of transactions is available for analysis. Using this dataset, we reconstruct the transaction network between users and analyze changes in the structure of the subgraph induced by the most active users. Our approach is based on the unsupervised identification of important features of the time variation of the network. Applying the widely used method of Principal Component Analysis to the matrix constructed from snapshots of the network at different times, we are able to show how structural changes in the network accompany significant changes in the exchange price of bitcoins.

Daniel Wilson-Nunn, Héctor Zenil

We show that the behaviour of Bitcoin has interesting similarities to stock\nand precious metal markets, such as gold and silver. We report that whilst\nLitecoin, the second largest cryptocurrency, closely follows Bitcoin's\nbehaviour, it does not show all the reported properties of Bitcoin. Agreements\nbetween apparently disparate complexity measures have been found, and it is\nshown that statistical, information-theoretic, algorithmic and fractal measures\nhave different but interesting capabilities of clustering families of markets\nby type. The report is particularly interesting because of the range and novel\nuse of some measures of complexity to characterize price behaviour, because of\nthe IRS designation of Bitcoin as an investment property and not a currency,\nand the announcement of the Canadian government's own electronic currency\nMintChip.\n

Alessandro Caiani, Antoine Godin, Eugenio Caverzasi, Luca Riccetti · 8 authors

We present an agent based stock flow consistent macroeconomic model with heterogeneous agents interacting through a decentralized matching process across multiple markets with multiple assets. The model is consistent across both the micro and macroeconomic levels, by providing a detailed, comprehensive, and rigorous accounting of real and financial flows and stocks. We implement the model using a brand new Java programming platform, explicitly designed for AB-SFC models.

K. H. McIntyre, Kristine Harjes

Bitcoin is a decentralized, open-source cryptocurrency used to make private, peer-to-peer transactions anywhere across the world. Although the individuals involved are (mostly) anonymous, every Bitcoin transaction is a matter of public record; anyone can view every Bitcoin transaction ever made. Following the methodology developed by Evans and Lyons (2002), this paper adapts and estimates a FX microstructure model that emphases order flow, the difference between buyer- and seller-initiated trading volume, to the Bitcoin market Using a data set consisting of all major currency transactions occurring on the Mt. Gox exchange, our results are quite similar to prior microfinance research on traditional currencies insofar order flow is a significant determinant of Bitcoin spot rates.

Ferdinando M. Ametrano

In the history of money bitcoin represents an outstanding medium of exchange, independent from central authorities. Therefore, it has experienced impressive demand which, combined with inelastic supply, has led to huge price appreciation. Nonetheless, transaction volume has not been increasing accordingly. At the core of this conundrum is the very poor performance of bitcoin as unit of account: dramatic deflationary price instability makes bitcoin just impractical for commerce, but completely unserviceable for salaries, mortgages, and deferred payments in general. Ametrano (2014a) has championed as Hayek Money the proposal to engineer cryptocurrencies with fully automatic algorithmic non-discretionary elastic supply: the monetary rule of pegging to a price index would dynamically rebase the outstanding amount of money and achieve price stability. It is proposed here to implement Hayek Money as multiple coexisting units of account wrapped around the unmodified bitcoin (or any other cryptocurrency). Prices would be stable in terms of these rebased-bitcoin units of account: different coexisting cryptocurrencies all backed by the same bitcoins, each one with its own floating bitcoin-equivalent rebasing index. These cryptocurrencies would define a new monetary standard, with striking resemblance to the gold standard as improved by the compensated dollar proposed by Fisher (1913). In this Fisher Money scenario bitcoin would be digital crypto-gold and exchange rates would be floating, not fixed, being just the relative prices of the respective cryptocurrency price indexes.

Devavrat Shah, Kang Zhang

In this paper, we discuss the method of Bayesian regression and its efficacy for predicting price variation of Bitcoin, a recently popularized virtual, cryptographic currency. Bayesian regression refers to utilizing empirical data as proxy to perform Bayesian inference. We utilize Bayesian regression for the so-called "latent source model". The Bayesian regression for "latent source model" was introduced and discussed by Chen, Nikolov and Shah (2013) and Bresler, Chen and Shah (2014) for the purpose of binary classification. They established theoretical as well as empirical efficacy of the method for the setting of binary classification. In this paper, instead we utilize it for predicting real-valued quantity, the price of Bitcoin. Based on this price prediction method, we devise a simple strategy for trading Bitcoin. The strategy is able to nearly double the investment in less than 60 day period when run against real data trace.

David García, Claudio J. Tessone, Pavlin Mavrodiev, Nicolas Perony

What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid increase in exchange rates (price) followed by sharp decline; we hypothesise that these fluctuations are largely driven by the interplay between different social phenomena. We thus quantify four socio-economic signals about Bitcoin from large data sets: price on on-line exchanges, volume of word-of-mouth communication in on-line social media, volume of information search, and user base growth. By using vector autoregression, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin adopters. We also observe that spikes in information search, presumably linked to external events, precede drastic price declines. Understanding the interplay between the socio-economic signals we measured can lead to applications beyond cryptocurrencies to other phenomena which leave digital footprints, such as on-line social network usage.

Jermain Kaminski

This paper analyzes correlations and causalities between Bitcoin market indicators and Twitter posts containing emotional signals on Bitcoin. Within a timeframe of 104 days (November 23rd 2013 - March 7th 2014), about 160,000 Twitter posts containing "bitcoin" and a positive, negative or uncertainty related term were collected and further analyzed. For instance, the terms "happy", "love", "fun", "good", "bad", "sad" and "unhappy" represent positive and negative emotional signals, while "hope", "fear" and "worry" are considered as indicators of uncertainty. The static (daily) Pearson correlation results show a significant positive correlation between emotional tweets and the close price, trading volume and intraday price spread of Bitcoin. However, a dynamic Granger causality analysis does not confirm a statistically significant effect of emotional Tweets on Bitcoin market values. To the contrary, the analyzed data shows that a higher Bitcoin trading volume Granger causes more signals of uncertainty within a 24 to 72-hour timeframe. This result leads to the interpretation that emotional sentiments rather mirror the market than that they make it predictable. Finally, the conclusion of this paper is that the microblogging platform Twitter is Bitcoin's virtual trading floor, emotionally reflecting its trading dynamics.

Luisanna Cocco, Giulio Concas, Michele Marchesi

This paper presents an agent-based artificial cryptocurrency market in which heterogeneous agents buy or sell cryptocurrencies, in particular Bitcoins. In this market, there are two typologies of agents, Random Traders and Chartists, which interact with each other by trading Bitcoins. Each agent is initially endowed with a finite amount of crypto and/or fiat cash and issues buy and sell orders, according to her strategy and resources. The number of Bitcoins increases over time with a rate proportional to the real one, even if the mining process is not explicitly modelled. The model proposed is able to reproduce some of the real statistical properties of the price absolute returns observed in the Bitcoin real market. In particular, it is able to reproduce the autocorrelation of the absolute returns, and their cumulative distribution function. The simulator has been implemented using object-oriented technology, and could be considered a valid starting point to study and analyse the cryptocurrency market and its future evolutions.

Ladislav Krištoufek

The Bitcoin has emerged as a fascinating phenomenon in the Financial markets. Without any central authority issuing the currency, the Bitcoin has been associated with controversy ever since its popularity, accompanied by increased public interest, reached high levels. Here, we contribute to the discussion by examining the potential drivers of Bitcoin prices, ranging from fundamental sources to speculative and technical ones, and we further study the potential influence of the Chinese market. The evolution of relationships is examined in both time and frequency domains utilizing the continuous wavelets framework, so that we not only comment on the development of the interconnections in time but also distinguish between short-term and long-term connections. We find that the Bitcoin forms a unique asset possessing properties of both a standard financial asset and a speculative one.

Nicolas T. Courtois

In this paper we revisit some major orthodoxies which lie at the heart of the bitcoin crypto currency and its numerous clones. In particular we look at The Longest Chain Rule, the monetary supply policies and the exact mechanisms which implement them. We claim that these built-in properties are not as brilliant as they are sometimes claimed. A closer examination reveals that they are closer to being... engineering mistakes which other crypto currencies have copied rather blindly. More precisely we show that the capacity of current crypto currencies to resist double spending attacks is poor and most current crypto currencies are highly vulnerable. Satoshi did not implement a timestamp for bitcoin transactions and the bitcoin software does not attempt to monitor double spending events. As a result major attacks involving hundreds of millions of dollars can occur and would not even be recorded. Hundreds of millions have been invested to pay for ASIC hashing infrastructure yet insufficient attention was paid to network neutrality and to insure that the protection layer it promises is effective and cannot be abused. In this paper we develop a theory of Programmed Self-Destruction of crypto currencies. We observe that most crypto currencies have mandated abrupt and sudden transitions. These affect their hash rate and therefore their protection against double spending attacks which we do not limit the to the notion of 51% attacks which is highly misleading. In addition we show that smaller bitcoin competitors are substantially more vulnerable. In addition to small hash rate, many bitcoin competitors mandate incredibly important adjustments in miner reward. We exhibit examples of 'alt-coins' which validate our theory and for which the process of programmed decline and rapid self-destruction has clearly already started.

José Eduardo Gómez-González, Julián Andrés Parra-Polanía

In the present paper we remark that the absence of an intrinsic or fundamental value represents a problem for the stability of the bitcoin’s price as an asset. In addition, we consider some …nancial stability concerns that derive from the hypothesis that the bitcoin will survive as an asset subject to high speculation.

Marshall Van Alstyne

Evaluating the evolving controversial digital currency.

Stefan Bornholdt, Kim Sneppen

Bitcoins have emerged as a possible competitor to usual currencies, but other\ncrypto-currencies have likewise appeared as competitors to the Bitcoin\ncurrency. The expanding market of crypto-currencies now involves capital\nequivalent to $10^{10}$ US Dollars, providing academia with an unusual\nopportunity to study the emergence of value. Here we show that the Bitcoin\ncurrency in itself is not special, but may rather be understood as the\ncontemporary dominating crypto-currency that may well be replaced by other\ncurrencies. We suggest that perception of value in a social system is generated\nby a voter-like dynamics, where fashions form and disperse even in the case\nwhere information is only exchanged on a pairwise basis between agents.\n

Bernhard Rengs, Manuel Scholz-Wäckerle

We present a highly stylized agent-based computational model (ABM) of an artificial economic and monetary union. Contrary to other current macroeconomic ABMs, it focuses on the relations/consequences of credit-financed, high-leveraged economies, conspicuous consumption within and across borders and a monetary and economic union of individual countries. The model includes a number of boundedly rational agents of the following types: a central bank, states & governments, banks, firms and households. In summary, it enables simulations of interacting political economies within a monetary union, entailing complex interactions and interdependencies between centralized governments/central banks and decentralized markets for goods (regular and status), labor, loans as well as bonds from the bottom up. Through its modular structure, we are able to apply dynamic comparative institutional analysis by investigating medium and long-run economic effects.

Frederik The

No abstract is available for this record.

Nicolás Della Penna, P M Krafft

We study herding behavior of traders in a cryptocurrency exchange

Nicolas Wesner

This paper uses simple monetary economic theory in order to extract implied BTC interest rates from exchange rates, interest rates and monetary supply data. Uncovered interest rate parity permits to derive a theoretical risk free BTC interest rate that is supposed to apply in a no arbitrage environment with rational expectations. Application to BTC/US$ exchange rates, Libor and Money supply US M2 data on the period September 2010 to January 2014 provides estimates, which illustrate what a risk free BTC interest rate could look like.

W L Brown

Bitcoins have the potential to fundamentally change the way value is transferred globally. Their rapid adoption over the past four years has led many to consider the possible results of such a technology. To be a viable currency, however, it is imperative that the market for trading Bitcoins is efficient. By examining the changes in availability of predictable outsized returns and market liquidity over time, this paper examines historical Bitcoin market efficiency and establishes correlations between market liquidity, price predictability, and return data. The results provide insight into the turbulent nature of Bitcoin market efficiency over the past years, but cannot definitively measure the magnitude of the change due to the limitations in efficiency analysis. The most meaningful result of this study, however, is the statistically significant short-horizon price predictability that existed over the duration of the study, which has implications for Bitcoin market efficiency as well as for continued research in short-horizon Bitcoin price forecasting models.

Ole Christian Andreas Valstad, Kristian Vagstad

Alloreactivity after transplantation is associated with profound immune suppression, and consequent opportunistic infection results in high morbidity and mortality. This immune suppression is most profound during GVHD after bone marrow transplantation where an inflammatory cytokine storm dominates. Contrary to current dogma, which avers that this is a T-cell defect, we demonstrate that the impairment lies within conventional dendritic cells (cDCs). Significantly, exogenous antigens can only be presented by the CD8(-) cDC subset after bone marrow transplantation, and inflammation during GVHD specifically renders the MHC class II presentation pathway in this population incompetent. In contrast, both classic and cross-presentation within MHC class I remain largely intact. Importantly, this defect in antigen processing can be partially reversed by TNF inhibition or the adoptive transfer of donor cDCs generated in the absence of inflammation.

Hammad Siddiqi, Siddiqi, Hammad

I argue that the bitcoins market is an example of a complex system without a stable equilibrium. The users of bitcoins fall into two broad categories: 1) Capital gain seekers: who have no functional use for the currency apart from an expectation of capital gains; 2) Functional users: who use the currency to save on transaction costs as it provides a less costly medium of exchange over traditional fiat currencies. I assume thateach category consists of mean-variance optimizers, and specify simple evolutionary dynamics for each category. I identify two simple routes to chaos in the bitcoins market. If only capital gain seekers are present, then one route to chaos is via the logistic map. If both categories of users matter then a possible route to chaos is via the delay logistic-Hénon map. A policy recommendation follows: in order to pre-empt chaos in the bitcoins market, currency exchanges should be allowed to convert bitcoins into dollars and vice versa if and only if there is an associated transaction involving buying and selling of goods or services or if the bitcoins are freshly mined.Such a regulation pre-empts chaos by reducing the impact of capital gain seekers on the virtual currency’s value.