Money is a technology for promoting economic prosperity. Over history money has become increasingly abstract, it used to be hardware, gold coins and the like, now it is mostly software, data structures located in banks. Here I propose the logical conclusion of the abstraction of money: to use as money the most general form of information - computer programs. The key advantage that using programs for money (program-money) adds to the technology of money is agency. Program-money is active and thereby can fully participate in economics as economic agents. I describe the three basic technologies required to implement program-money: computational languages/logics to unambiguously describe the actions and interactions of program-money; computational cryptography to ensure that only the correct actions and interactions are performed; and a distributed computational environment in which the money can execute. I demonstrate that most of the technology for program-money has already been developed. The adoption of program-money transfers responsibility from human economic agents to money itself and has great potential economic advantages over the current passive form of money. For example in
In the UK, the Bank of England and HM Treasury are exploring a potential UK retail CBDC, the digital pound, with one of their motivations being the potential role of the digital pound as an anchor for monetary and financial stability. In this paper, we explore three elements for anchoring money (singleness of money, official currency as the unit of account, and safety and soundness of financial institutions and payment systems) that maintain public trust and confidence in private UK retail digital money and the financial system. We also identify core capabilities (comprising on-demand interoperability across issuers and forms of private money, settlement finality in wholesale central bank money, and access to physical cash) and appropriate measures (comprising customer funds protection, robust regulation, effective supervision, safe innovation in money and payments, and the central bank as the lender of last resort) that together provide the foundations for the three elements for anchoring money. Our preliminary analysis concludes that anchoring private UK retail digital money is supported by these elements, capabilities and measures. Further work could include public-private colla
This research studies the relation between money and prices and its practical implications analyzing quarterly data from United States (1959-2022), Canada (1961-2022), United Kingdom (1986-2022), and Brazil (1996-2022). The historical, logical, and econometric consistency of the logical core of the two main theories of money is analyzed using objective bayesian and frequentist machine learning models, bayesian regularized artificial neural networks, and ensemble learning. It is concluded that money is not neutral at any time horizon and that, despite money is ultimately subordinated to prices, there is a reciprocal influence over time between money and prices which constitute a complex system. Non-neutrality is transmitted through aggregate demand and is based on the exchange value of money as a monetary unit.
St. Francis of Assisi (1181/82-1226) famously called money the devil's dung, and indeed money is often associated with greed, inequality, and corruption. Drawing on Nowak's five rules for the evolution of cooperation, we argue here that money promotes the formation of circuits of generalized reciprocity across human groups that are fundamental to social evolution. In an evolutionary tournament, we show that money exchange is an evolutionary stable strategy that promotes cooperation without relying on the cognitive demands of direct reciprocity or reputation mechanisms. However, we also find that excessive liquidity can be detrimental because it can distort the informational value of money as a signal of past cooperation, making defection more profitable. Our results suggest that, in addition to institutions that promoted trust and punishment, the emergence of institutions that regulated the money supply was key to maintaining generalized reciprocity within and across human groups.
Quantum money represents an innovative approach to currency by encoding economic value within the quantum states of physical systems, utilizing the principles of quantum mechanics to enhance security, integrity, and transferability. This perspective article explores the definition and properties of quantum money. We analyze the process of transferring quantum money via quantum teleportation, using terrestrial and satellite-based quantum networks. Furthermore, we consider the impact of quantum money on the modern banking system, particularly in money creation. Finally, we conduct an analysis to assess the strengths and weaknesses of quantum money, as well as opportunities and threats associated with this emerging concept.
As the largest blockchain platform that supports smart contracts, Ethereum has developed with an incredible speed. Yet due to the anonymity of blockchain, the popularity of Ethereum has fostered the emergence of various illegal activities and money laundering by converting ill-gotten funds to cash. In the traditional money laundering scenario, researchers have uncovered the prevalent traits of money laundering. However, since money laundering on Ethereum is an emerging means, little is known about money laundering on Ethereum. To fill the gap, in this paper, we conduct an in-depth study on Ethereum money laundering networks through the lens of a representative security event on \textit{Upbit Exchange} to explore whether money laundering on Ethereum has traditional traits. Specifically, we construct a money laundering network on Ethereum by crawling the transaction records of \textit{Upbit Hack}. Then, we present five questions based on the traditional traits of money laundering networks. By leveraging network analysis, we characterize the money laundering network on Ethereum and answer these questions. In the end, we summarize the findings of money laundering networks on Ethereum,
In the 1970s, Wiesner introduced the concept of quantum money, where quantum states generated according to specific rules function as currency. These states circulate among users with quantum resources through quantum channels or face-to-face interactions. Quantum mechanics grants quantum money physical-level unforgeability but also makes minting, storing, and circulating it significantly challenging. Currently, quantum computers capable of minting and preserving quantum money have not yet emerged, and existing quantum channels are not stable enough to support the efficient transmission of quantum states for quantum money, limiting its practicality. Semi-quantum money schemes support fully classical transactions and complete classical banks, reducing dependence on quantum resources and enhancing feasibility. To further minimize the system's reliance on quantum resources, we propose a cloud-based semi-quantum money (CSQM) scheme. This scheme relies only on semi-honest third-party quantum clouds, while the rest of the system remains entirely classical. We also discuss estimating the computational power required by the quantum cloud for the scheme and conduct a security analysis.
While classical money can be copied, it is impossible to copy quantum money in principle, with only the bank that issues it knowing how to generate it, meaning only the bank can make exact copies. Not all reliable banks, such as central banks, will issue quantum money, so there is the possibility that untrustworthy banks are distributing fake or multiple copies of the same quantum money without the users' knowledge. As such, we propose a quantum patchwork money scheme in which banks cannot distribute exact copies to users. This scheme involves multiple banks providing public-key quantum money as shards and generating quantum patchwork money by combining them. The banks can use the quantum patchwork money without completely trusting the other banks. In addition, nonbank users can use safely the quantum patchwork money without trusting any banks potentially focused on self-interest by adding a protocol for monitoring the distribution of copies.
Recently, in order to explore the mechanism behind wealth or income distribution, several models have been proposed by applying principles of statistical mechanics. These models share some characteristics, such as consisting of a group of individual agents, a pile of money and a specific trading rule. Whatever the trading rule is, the most noteworthy fact is that money is always transferred from one agent to another in the transferring process. So we call them money transfer models. Besides explaining income and wealth distributions, money transfer models can also be applied to other disciplines. In this paper we summarize these areas as statistical distribution, economic mobility, transfer rate and money creation. First, money distribution (or income distribution) can be exhibited by recording the money stock (flow). Second, the economic mobility can be shown by tracing the change in wealth or income over time for each agent. Third, the transfer rate of money and its determinants can be analyzed by tracing the transferring process of each one unit of money. Finally, money creation process can also be investigated by permitting agents go into debts. Some future extensions to these
The proposed framework introduces a novel multidimensional representation of money using tensor analysis, enabling a more granular examination of economic interactions and capital flow. By treating money as a multidimensional entity, this approach allows for detailed tracking and modeling of sectoral, temporal, and agent-based dynamics. This enhanced perspective facilitates the design of adaptive economic policies that can effectively respond to evolving macroeconomic conditions, ensuring resilience and inclusivity in financial systems. Furthermore, the tensor-based modeling framework bridges traditional economic analyses with advanced computational techniques, offering a robust foundation for algorithmic governance and data-driven decision-making in complex economies.
Cryptocurrencies are considered relevant assets and they are currently used as an investment or to carry out transactions. However, specific characteristics commonly associated with the cryptocurrencies such as irreversibility, immutability, decentralized architecture, absence of control authority, mobility, and pseudo-anonymity make them appealing for money laundering activities. Thus, the collection and characterization of current cryptocurrency-based methods used for money laundering are paramount to understanding the circulation flows of physical and digital money and preventing this illegal activity. In this paper, a collection of cryptocurrency transaction methods is presented and distributed through the money laundering life cycle. Each method is analyzed and classified according to the phase of money laundering it corresponds to. The result of this article may in the future help design efficient strategies to prevent illegal money laundering activities.
This review is about the convenience, the benefits, as well as the destructive capacities of money. It deals with various aspects of money creation, with its value, and its appropriation. All sorts of money tend to get corrupted by eventually creating too much of them. In the long run, this renders money worthless and deprives people holding it. This misuse of money creation is inevitable and should come as no surprise. Abusive money creation comes in various forms. In the present fiat money system "suspended in free thought" and sustained merely by our belief in and our conditioning to it, money is conveniently created out of "thin air" by excessive government spending and speculative credit creation. Alas, any too tight money supply could ruin an economy by inviting all sorts of unfriendly takeovers, including wars or competition. Therefore the ambivalence of money as benefactor and destroyer should be accepted as destiny.
Given a stream of money transactions between accounts in a bank, how can we accurately detect money laundering agent accounts and suspected behaviors in real-time? Money laundering agents try to hide the origin of illegally obtained money by dispersive multiple small transactions and evade detection by smart strategies. Therefore, it is challenging to accurately catch such fraudsters in an unsupervised manner. Existing approaches do not consider the characteristics of those agent accounts and are not suitable to the streaming settings. Therefore, we propose MonLAD and MonLAD-W to detect money laundering agent accounts in a transaction stream by keeping track of their residuals and other features; we devise AnoScore algorithm to find anomalies based on the robust measure of statistical deviation. Experimental results show that MonLAD outperforms the state-of-the-art baselines on real-world data and finds various suspicious behavior patterns of money laundering. Additionally, several detected suspected accounts have been manually-verified as agents in real money laundering scenario.
Many-body dynamical models in which Boltzmann statistics can be derived directly from the underlying dynamical laws without invoking the fundamental postulates of statistical mechanics are scarce. Interestingly, one such model is found in econophysics and in chemistry classrooms: the money game, in which players exchange money randomly in a process that resembles elastic intermolecular collisions in a gas, giving rise to the Boltzmann distribution of money owned by each player. Although this model offers a pedagogical example that demonstrates the origins of Boltzmann statistics, such demonstrations usually rely on computer simulations - a proof of the exponential steady-state distribution in this model has only become available in recent years. Here, we study this random money/energy exchange model, and its extensions, using a simple mean-field-type approach that examines the properties of the one-dimensional random walk performed by one of its participants. We give a simple derivation of the Boltzmann steady-state distribution in this model. Breaking the time-reversal symmetry of the game by modifying its rules results in non-Boltzmann steady-state statistics. In particular, intr
Quantum money allows a bank to mint quantum money states that can later be verified and cannot be forged. Usually, this requires a quantum communication infrastructure to transfer quantum states between the user and the bank. Gavinsky (CCC 2012) introduced the notion of classically verifiable quantum money, which allows verification through classical communication. In this work we introduce the notion of classical minting, and combine it with classical verification to introduce semi-quantum money. Semi-quantum money is the first type of quantum money to allow transactions with completely classical communication and an entirely classical bank. This work features constructions for both a public memory-dependent semi-quantum money scheme and a private memoryless semi-quantum money scheme. The public construction is based on the works of Zhandry and Coladangelo, and the private construction is based on the notion of Noisy Trapdoor Claw Free Functions (NTCF) introduced by Brakerski et al. (FOCS 2018). In terms of technique, our main contribution is a perfect parallel repetition theorem for NTCF.
The standard criterion of rationality in economics is the maximization of a utility function that is stable across multiple observations of an agent's choice behavior. In this paper, we discuss two notions of the money pump that characterize two corresponding notions of utility-maximization. We explain the senses in which the amount of money that can be pumped from a consumer is a useful measure of the consumer's departure from utility-maximization.
An innovative method is proposed to construct a quantile dependence system for inflation and money growth. By considering all quantiles and leveraging a novel notion of quantile sensitivity, the method allows the assessment of changes in the entire distribution of a variable of interest in response to a perturbation in another variable's quantile. The construction of this relationship is demonstrated through a system of linear quantile regressions. Then, the proposed framework is exploited to examine the distributional effects of money growth on the distributions of inflation and its disaggregate measures in the United States and the Euro area. The empirical analysis uncovers significant impacts of the upper quantile of the money growth distribution on the distribution of inflation and its disaggregate measures. Conversely, the lower and median quantiles of the money growth distribution are found to have a negligible influence. Finally, this distributional impact exhibits variation over time in both the United States and the Euro area.
A money transfer involves a buyer and a seller. A buyer buys goods or services from a seller. The money the buyer decreases is the same as that the seller increases. At each time step, a pair of socially connected agents are selected and transact in agreed money. We evolve the Deffuant model to a money exchange system and study circumstances under which asymptotic stability holds, or equal wealth can be achieved.
Money transfer is an abstraction that realizes the core of cryptocurrencies. It has been shown that, contrary to common belief, money transfer in the presence of Byzantine faults can be implemented in asynchronous networks and does not require consensus. Nonetheless, existing implementations of money transfer still require a quadratic message complexity per payment, making attempts to scale hard. In common blockchains, such as Bitcoin and Ethereum, this cost is mitigated by payment channels implemented as a second layer on top of the blockchain allowing to make many off-chain payments between two users who share a channel. Such channels only require on-chain transactions for channel opening and closing, while the intermediate payments are done off-chain with constant message complexity. But payment channels in-use today require synchrony, therefore they are inadequate for asynchronous money transfer systems. In this paper, we provide a series of possibility and impossibility results for payment channels in asynchronous money transfer systems. We first prove a quadratic lower bound on the message complexity of on-chain transfers. Then, we explore two types of payment channels, unidi
In this paper, we reveal the depreciation mechanism of representative money (banknotes) from the perspective of logistics warehousing costs. Although it has long been the dream of economists to stabilize the buying power of the monetary units, the goal we have honest money always broken since the central bank depreciate the currency without limit. From the point of view of modern logistics, the key functions of money are the store of value and low logistics (circulation and warehouse) cost. Although commodity money (such as gold and silver) has the advantages of a wealth store, its disadvantage is the high logistics cost. In comparison to commodity money, credit currency and digital currency cannot protect wealth from loss over a long period while their logistics costs are negligible. We proved that there is not such honest money from the perspective of logistics costs, which is both the store of value like precious metal and without logistics costs in circulation like digital currency. The reason hidden in the back of the depreciation of banknotes is the black hole of storage charge of the anchor overtime after digitizing commodity money. Accordingly, it is not difficult to infer