I have previously categorized ’crypto’ – a catch-all for blockchain- and Web3-related innovation – as part of the Digital Revolution that started around the late 1960s to early 1970s with the invention of packet-switched networks, microprocessors, and other digital technologies that enabled the proliferation of personal computers and the Internet. I would like to expand on that by:
Providing a brief theoretical outline of the two main stages of technological revolutions;
Comparing the organizational and institutional shifts of the previous revolution (centered around oil, automobiles, and mass production) with those of the current one (centered around digital information and communications technology) as imagined during the dot-com era (late 1990s, early 2000s); and
Discussing how ’crypto’ as a techno-populist reform movement and innovation cluster is shaping global institutions and governance as the Digital Revolution matures.
Throughout the text, I will be using ’ICT’ as a shorthand for digital information and communications technology, and ’ICT Revolution’ as a shorthand for the Digital Revolution. From here on, quotation marks around the word ’crypto’ will be omitted, while still referring not just to cryptography, but to all blockchain- and Web3-related innovation. Readers familiar with Carlota Perez’s theory of techno-economic paradigm shifts may skip the first section.
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zkSync best preserves the properties that have made Ethereum successful thus far: decentralization, security, composability, capital efficiency, and instant withdrawals. At the same time, it minimizes the disruption faced by developers who are used to building contracts for the EVM. As a result, we believe zkSync is the L2 that paves the smoothest path to scaling DeFi, NFTs, and all other innovations happening on Ethereum. Before we get into specifics, it’s worth reflecting on how we got here. This discussion points to the conclusion that the challenge ahead is not only to scale, but to do so in a way that safeguards the core properties that got Ethereum this far.
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Yield is one of the most important primitives in financial markets. Alongside gains, it’s an expression of investment profits. But where gains stem from changes in the price of an asset – and are only realized when the asset is sold – yield is a measure of cash flows generated and distributed to the asset’s holder. While they are separate phenomena, yield informs the price of an asset and vice versa. Element is a protocol that allows developers and investors to harness the power of yield in their applications and strategies.
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The term ’institutional isomorphism’ refers to similarities in the structure and processes of independent organizations. In the past, the spread of information and the adoption of similar practices was slower and often limited to organizations within a single country or region. But in the newly emerging institutional field of blockchain networks and decentralized autonomous organizations (DAOs), which benefit from near-instant global communications via the Internet, isomorphism develops much faster.
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We are working to build permissionless, open tech. Most of the process is open, but the part that remains the most closed and shrouded in secrecy is the early-stage financing. While this is in-part regulatorily and social norms driven, the more sinister component is insiders can disproportionately tilt the scales in their favor while keeping the details hidden from public view. The more early-stage investors get away with edgy behavior, the more emboldened and empowered they become, to the point where this power becomes detrimental to the health of the space as a whole.
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We present a method for constructing Constant Function Market Makers (CFMMs) whose portfolio value functions matches a desired payoff. More specifically, we show that the space of concave, nonnegative, nondecreasing, 1-homogeneous payoff functions and the space of convex CFMMs are equivalent; in other words, every CFMM has a concave, nonnegative, nondecreasing, 1-homogeneous payoff function, and every payoff function with these properties has a corresponding convex CFMM. We demonstrate a simple method for recovering a CFMM trading function that produces this desired payoff. This method uses only basic tools from convex analysis and is intimately related to Fenchel conjugacy. We demonstrate our result by constructing trading functions corresponding to basic payoffs, as well as standard financial derivatives such as options and swaps.
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DeFi is not about rebuilding finance as we know it; it’s about building a better finance. History has shown that without appropriate rules, safeguards, and behavioral norms, financial markets become more prone to fraud, pro-cyclical excess, and crises. Occasionally, these crises take systemic proportions, threatening the stability of the economic system as a whole. A popular analogy for thinking about systemic risk in the financial sector is fire and building safety. While the analogy is far from perfect, perhaps there are lessons that today’s financial innovators can learn from the historical evolution of fire and building safety?
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Constant function market makers (CFMMs) such as Uniswap, Balancer, Curve, and mStable, among many others, make up some of the largest decentralized exchanges on Ethereum and other blockchains. Because all transactions are public in current implementations, a natural next question is if there exist similar decentralized exchanges which are privacy-preserving; i.e., if a transaction’s quantities are hidden from the public view, then an adversary cannot correctly reconstruct the traded quantities from other public information. In this note, we show that privacy is impossible with the usual implementations of CFMMs under most reasonable models of an adversary and provide some mitigating strategies.
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Radicle is a new kind of code collaboration network built entirely on open protocols. At the core of it there is a peer-to-peer code network built on Git. It allows developers to host and manage open source software projects on a decentralized network of nodes owned by their peers, instead of centralized platforms like GitHub owned by companies like Microsoft. This is especially important in today’s world, where the power to control information, including code, lies in the hands of the few.
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Constant Function Market Makers (CFMMs) are a family of automated market makers that enable censorship-resistant decentralized exchange on public blockchains. Arbitrage trades have been shown to align the prices reported by CFMMs with those of external markets. These trades impose costs on Liquidity Providers (LPs) who supply reserves to CFMMs. Trading fees have been proposed as a mechanism for compensating LPs for arbitrage losses. However, large fees reduce the accuracy of the prices reported by CFMMs and can cause reserves to deviate from desirable asset compositions. CFMM designers are therefore faced with the problem of how to optimally select fees to attract liquidity. We develop a framework for determining the value to LPs of supplying liquidity to a CFMM with fees when the underlying process follows a general diffusion. Our approach also allows one to select optimal fees for maximizing LP value.
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CFMMs and associated protocols, which were historically very small markets, now constitute the most liquid trading venues for a large number of crypto assets. But what does it mean for a CFMM to be the most liquid market? In this paper, we propose a basic definition of price sensitivity and liquidity. We show that this definition is tightly related to the curvature of a CFMM's trading function and can be used to explain a number of heuristic results. For example, we show that low-curvature markets are good for coins whose market value is approximately fixed and that high-curvature markets are better for liquidity providers when traders have an informational edge. Additionally, the results can also be used to model interacting markets and explain the rise of incentivized liquidity provision, also known as 'yield farming.'
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