We can define a Central Bank Digital Currency (CBDC) as a digital currency issued by a central bank to retail customers.

The main argument in this book is a simple one: that CBDCs offer no benefits to the public that cannot be better achieved using existing tools; at the same time, CBDCs entail substantial disadvantages and risks. These include the risks that CBDCs pose to the stability of the banking system, their inefficiency compared to private alternatives and especially the risks to civil liberties that come from giving the central bank an immensely powerful instrument of surveillance and control. In short, retail CBDCs would provide no tangible benefits and entail serious problems that could be avoided by not introducing a CBDC in the first place. The case for CBDCs should therefore be dismissed.

By contrast, privately issued digital currencies such as stablecoins should be encouraged as they offer potentially enormous benefits to the public.

Central Bank Digital Currencies (CBDCs) arose as a reaction by central banks to the threats posed to their currencies by cryptocurrencies. The process began with the development of digital currency, which required the prior development of strong cryptography. These developments led to the creation of Bitcoin in 2009, and its success then prompted the development of other so-called cryptocurrencies especially stablecoins. These in turn led to the idea of CBDCs, which were first proposed in 2013. The threat posed by Facebook’s proposed Libra cryptocurrency in 2019 then galvanised a subsequent ‘CBDC mania’ among central banks that is still going strong. However, this mania was misconceived and will prove to be embarrassing to its proponents when its underlying folly becomes obvious for all to see. It turns out that CBDCs have no distinctive useful functions and come with serious drawbacks as well.

The result is that there is no rational use for CBDCs, which should therefore be dismissed.

This chapter explores how traders’ performance may be influenced by the rationality levels of their peers in the market. Using a Behavioural Data Science approach, the study integrates experimental methods, machine learning and large-scale digital trace analysis to examine this relationship. Specifically, we analysed data from a cryptoasset exchange over a five-week period in late 2017 and early 2018, covering over 700,000 transactions across 17 trading pairs. We complemented this behavioural trace data with an online guessing game involving 2,622 active traders, of whom 273 participated. By combining survey results and trading histories, we applied clustering algorithms to identify seven distinct trader profiles, including ‘jokers’, ‘focal point traders’ and those operating at different levels of strategic reasoning (first, second and third order), as well as ‘professional’ and ‘Nash equilibrium’ traders. The findings suggest that traders engaging in higher-order reasoning generally achieve better financial outcomes, yet even experienced professionals are not immune to behavioural biases. The chapter highlights how Behavioural Data Science methods – linking experimental insight with real-world data and computational tools – can illuminate the cognitive patterns underlying economic decision-making in digital markets.

As business transactions and the global economy become increasingly digitalized, international investment disputes will deal with novel assets in new boundary-defiant contexts. Indeed, jurisdictional arguments and objections will likely require arbitral tribunals to confront with the uneasy task of delineating the ‘localization’ of investments in digital economy assets such as cryptocurrency, non-fungible tokens, and data-related investments. However, given that even more traditional assets have raised a variety of problems relating to territorial nexus and localization, the authors believe that the digital economy emphasizes what are essentially differences in degree rather than in kind. This chapter discusses the complexities that arise in considering the idiosyncrasies of investments in digital economy assets within a traditional territorially defined jurisdictional framework. First, the authors present some of those new digital economy assets and canvass several typical cross-border challenges inherent in international investment arbitration. Second, they question how traditional objections to jurisdiction ratione personae and jurisdiction ratione materiae might be employed when the investments in question relate to those digital developments. Third, the chapter raises questions about states’ jurisdiction to prescribe, and ponders the potential effects for purposes of jurisdiction of states asserting their authority to prescribe over investments or investors outside their territory.

Chapter 3 dives deep into the beating heart of cryptocurrency, the paradoxical technology that has made early adherents billions, while adding nothing of real value to society. By any measure, crypto has failed at its stated goal: creating a better financial system. Looking to Bitcoin, we show how the core innovation – a distributed encrypted database – makes a terrible payment system, with slow, expensive, uncorrectable transactions. But crypto enthusiasts ignore more than a decade of failure, doubling down on grandiose claims about solving everything from financial inclusion to corporate governance while ignoring the far easier, low-tech solutions to these very real needs. We include an interview with an early supporter of the massive crypto currency Ethereum, who came to see how crypto became “just a tool for the wealthy to become wealthier” rather than fulfilling its promise of financial inclusion for the world’s 1.7 billion unbanked people.

This chapter examines cases where cryptocurrency has been used by terrorist actors. At the same time, the chapter also examines the important role played by the private sector in ensuring that virtual assets are not misused. The chapter also takes a peek at the role of government regulation in the industry and where the private sector has concerns regarding an overly interventionist approach that could stifle a new technology.

The leading early twentieth-century US proponents of a transformation in the social organization of money were – albeit far from unproblematically – collectivist and communitarian in ideological orientation, whereas those that succeeded them tended toward libertarian, individualistic, and free-market positions. This chapter offers the first examination of American literature’s connections to this latter wave of alternative currency campaigns, ranging from 1970s calls for privatized monies to contemporary cryptocurrency. It first introduces the foundational articulation of the right-libertarian approach to monetary reform, by the Austrian economist Friedrich Hayek, and connects these ideas to a classic of US avant-garde fiction as well as a landmark of the American libertarian literary canon. It then explores how two of the most renowned economically-themed American novels of recent decades – Lionel Shriver’s The Mandibles (2016) and Neal Stephenson’s Cryptonomicon (1999) – put a libertarian understanding of monetary innovation into dialogue with complex questions of trust, value, technology, nation, and identity. It concludes by reading an important recent addition to the tradition of American weird fiction – Michael Cisco’s Animal Money (2015) – as suggesting alternatives both to the too-narrow conceptions of the collective and to the privileging of the individual that have characterized visions of monetary transformation past and present.

This chapter covers the potential use of quantum algorithms for cryptanalysis, that is, the breaking and weakening of cryptosystems. We discuss Shor’s algorithm for factoring and discrete logarithm, which render widely used public-key cryptosystems vulnerable to attack, given access to a sufficiently large-scale quantum computer. We present resource estimates from the literature for running Shor’s algorithm, and we discuss the outlook for postquantum cryptography, which aims to replace existing cryptosystems while being resistant to quantum attack. We also cover quantum approaches for weakening the security of cryptosystems based on Grover’s search algorithm.

In the light of the growing interest in crypto-assets and the quest for their institutionalisation, we examine the role that they can play as investable assets useful in standard portfolio problems when asset returns are predictable. In particular, we study whether a mix of macroeconomic factors and crypto-specific predictors can be combined to produce accurate and economically valuable pooled forecasts. With reference to Bitcoin data, we uncover that crypto returns are predictable out-of-sample. Moreover, when this crypto-asset is made available to a mean-variance optimising investor, it generates large risk-adjusted realised performance gains irrespective of the assumed risk aversion. The results on the predictability of cryptocurrencies are robust to a generalisation to Litecoin and Ripple, although on a shorter 2015–2020 sample. However, results turn mixed and come to depend on the assumed risk aversion, when we investigate the power of forecast combinations to generate economic value from the entire pool of cryptocurrencies.

There has been progress made in the adoption of digital assets by institutional investors. Large institutions including Fidelity, BlackRock, and several investment banks have started providing products and services to satisfy the needs of their clients. Hedge funds and venture capital funds are also investing in digital assets. Global exchanges have introduced investable products based on cryptocurrency derivatives. The number of ways one can invest in digital assets is expected to grow with the introduction of new products. Digital assets are still very new and carry considerable risk. It is prudent of regulators to cautiously approach regulation. At the same time, the markets are looking for clarity from financial regulators. If and when there is more regulatory clarity, the pace of adoption is likely to pick up.