Market Makers Research Articles

Blockchain-Based Automated Market Makers for a Decentralized Stock Exchange

The advancements in communication speeds have enabled the centralized financial market to be faster and more complex than ever. The speed of the order execution has become exponentially faster when compared to the early days of electronic markets. Though the transaction speed has increased, the underlying architecture or models behind the markets have remained the same. These models come with their own disadvantages. The disadvantages are usually faced by non-institutional or small traders. The bigger players, such as financial institutions, have an advantage over smaller players because of factors such as information asymmetry and access to better infrastructure, which give them an advantage in terms of the speed of execution. This makes the centralized stock market an uneven playing field. This paper discusses the limitations of centralized financial markets, particularly the disadvantage faced by non-institutional or small traders due to information asymmetry and better infrastructure access by financial institutions. The authors propose the usage of blockchain technology and the data highway protocol to create a decentralized stock exchange that can potentially eliminate these disadvantages. The data highway protocol is used to generate new blocks with a flexible finality condition that allows for the consensus mechanism to configure security thresholds more freely. The proposed framework is compared with existing frameworks to confirm its effectiveness and identify areas that require improvement. The evaluation of the proposed approach showed that the improved highway protocol boosted the transaction rate compared to the other two mechanisms (PoS and PoW). Specifically, the transaction rate of the proposed model was found to be 2.2 times higher than that of PoS and 12 times higher than that of the PoW consensus model.

The Financial Origins of Non-Fundamental Risk

We formalize the idea that the financial sector can be a source of non-fundamental risk. Households' desire to hedge against price volatility can generate price volatility in equilibrium, even absent fundamental risk. Fearing that asset prices may fall, risk-averse households demand safe assets from leveraged intermediaries, whose issuance of safe assets exposes the economy to self-fulfilling fire sales. Policy can eliminate nonfundamental risk by (i) increasing the supply of publicly backed safe assets, through issuing government debt or bailing out intermediaries, or (ii) reducing the demand for safe assets, through social insurance or by acting as a market maker of last resort.

Do Automated Market Makers in DeFi Ecosystem Exhibit Time-Varying Connectedness during Stressed Events?

We investigate the connectedness of automated market makers (AMM) that play a pivotal role in liquidity and ease of operations in the decentralized exchange (DEX). By applying the TVP-VAR model, our findings show higher level of connectivity during periods of turmoil (such as Delta, Omicron variants of SARS-Covid, and the Russia Ukraine conflict). Furthermore, risk transmission/reception is found to be independent of the platform on which they typically run (Ethereum based AMMs were both emitters as well as receivers). Pancake (a Binance based AMM) and Perpetual Protocol (Ethereum based AMM) emerged as moderate to high receivers of risk transmission, whereas all of the other AMMs, including Ethereum, were found to be risk emitters at varying degrees. We argue that AMMs typically depend on the underlying smart contracts. If the contract is flexible, AMMs can vary (either receiver or emitter), otherwise AMMs behave in tandem.

Does the introduction of market maker improve market quality? Evidence from China's Sci-Tech innovation board

The design of the inherent mechanism of financial markets has always been an important issue in market microstructure. Based on the introduction of the market maker trading system on China's Sci-Tech Innovation Board (STAR Market), this study uses the staggered difference-in-differences method and selects data from STAR Market to test whether the introduction of the market maker system improves market quality. We find that introducing the market maker system improves market quality, with increased liquidity and decreased volatility in STAR Market stocks. Our study has great practical significance for constructing and developing capital market microstructure worldwide, especially in emerging markets.

Replicating market makers

Replicating market makers

A tale of two contracts: Examining the behavior of bid–ask spreads of corn futures in China

AbstractContracts that expire in January, May, and September attract the most trading activity for corn futures in China. Contracts that mature in other months are thinly traded, even when they are the closest to maturity. In this paper, we examine and compare the behavior and determinants of the bid–ask spreads (BASs) of active and inactive contracts using the best bid offer data set. We show that both the magnitude and volatility of BAS for inactive contracts exhibit U‐shaped patterns, whereas active contracts' BAS increase only near their expiration. Inactive contracts are also of low liquidity risk after introducing market makers. On the basis of the simultaneous equation model, we find that BAS responds negatively to volume and positively to volatility and order imbalance. The impacts are larger in inactive contracts. Moreover, introducing market makers to inactive contracts is conducive to attracting trading and lowering trading costs.

High frequency market making: The role of speed

We propose a model where a strategic high frequency market maker exploits his speed and informational advantages to place quotes that interact with the market orders of low frequency traders. We characterize the optimal market making policy and the equilibrium that results. The model has testable implications regarding the impact of speed on the provision of liquidity. We test these implications by taking advantage of a natural experiment on the NYSE American stock exchange, which implemented an intentional delay in 2017 then removed it in 2019. We find broad agreement between the empirical evidence and the implications of the model.

Ambiguous price formation

We study the price and liquidity of an asset in a model where market makers face ambiguity about the asset payoff. This ambiguity explains liquidity deteriorations and improvements in financial markets. We show that the ambiguity influences how market makers perceive adverse selection risk, and therefore, distorts market liquidity. The perceived adverse selection risk increases (resp. decreases) with the ambiguity when the market maker is sufficiently (resp. insufficiently) ambiguity averse. Our model also helps to understand how ambiguity and ambiguity aversion of market makers impact price and liquidity dynamics under various trading histories.

Primary Dealer Systems in the European Union

AbstractStates require money to function and therefore every government has to continuously raise new funds. On the financial markets, governments cannot be sure that auctions of their debt will be sufficiently attractive to financial investors, which is why they usually enter into cooperative agreements with selected banks. The best known and most widespread form of cooperation is the primary dealer system. A primary dealer is a bank that commits to purchasing a certain percentage of government debt at each auction and to intervene as a formalized market maker in the debt market if necessary. Most of the primary dealer systems involve the banks being financially neither remunerated nor compensated for their activities, and if there is some kind of financial compensation, it is on a low level. The article analyses European primary dealer systems and asks why banks are willing to participate in these systems. I will show that both domestic and foreign banks use their status as primary dealers to build long-term relationships with one or more European governments and to gain an advantage on the global stage. In Bourdieu’s terms, primary dealer banks use their financial capital to accumulate social and symbolic capital.

Heterogeneous agent-based modeling of endogenous boom-bust cycles in financial markets with adaptive expectations and dynamically switching fractions between contrarian and fundamental market entry strategies

Financial systems present nonlinear dynamics whilst in some conditions chaotic behaviours emerge, rendering the stability of these systems utterly volatile. In this novel study we investigate boom-bust cycles in stock markets with heterogeneous agent-based modeling, yet incorporating endogenously evolving fractions of market participants, particularly those switching between contrarian and fundamental strategies. The dynamical behavior of various market entry behaviours of market agents are studied via numerical simulations and analyses of phase portraits, bifurcation diagrams and Lyapunov exponents. If the system adjusts in a partial equilibrium of at least one positive Lyapunov exponent, we observe the emergence of chaotic dynamics. Overall, chaos emerges via endogenous boom-bust cycle dynamics, caused by time-varying fractions of switching strategies between contrarian versus fundamental trading strategies. Our results prove to be invaluable to different types of market participants, such as traders, arbitrageurs, investors, speculators and institutional market makers.

The Overnight Drift

Abstract This paper documents that U.S. equity returns are large and positive during the opening hours of European markets. These returns are pervasive and highly economically and statistically significant. Consistent with models of inventory risk, we demonstrate a strong relationship with order imbalances at the close of the preceding U.S. trading day. Rationalizing unconditionally positive “overnight drift” returns, we uncover an asymmetric reaction to demand shocks: market sell-offs generate robust positive overnight reversals, while reversals following market rallies are much more modest. We argue that demand shock asymmetry can arise in inventory management models with time-varying market maker risk-bearing capacity. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Static replication of impermanent loss for concentrated liquidity provision in decentralised markets

This article analytically characterizes the impermanent loss of concentrated liquidity provision for automatic market makers in decentralised markets such as Uniswap. We propose two static replication formulas for the impermanent loss by a combination of European calls or puts with strike prices supported on the liquidity provision price interval. It facilitates liquidity providers to hedge impermanent loss by trading crypto options in more liquid centralised exchanges such as Deribit. Numerical examples illustrate the astonishing accuracy of the static replication.

Secret and Overt Information Acquisition in Financial Markets

Abstract We study the observability of investors’ information-acquisition activities in financial markets. Improving observability leads to two strategic effects on information acquisition: (1) the pricing effect, which arises from interactions between investors and the market maker and can encourage or discourage information acquisition, and (2) the competition effect, which concerns interactions among investors and always encourages information acquisition. We apply our theory to study voluntary and mandatory disclosures of corporate site visits. When the competition effect dominates, investors voluntarily disclose their visits. When the pricing effect dominates, mandatory disclosure is effective. Our analysis sheds novel light on Regulation Fair Disclosure. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

One for the money, two for the show? The number of designated market makers and liquidity

One for the money, two for the show? The number of designated market makers and liquidity

SoK: Decentralized Exchanges (DEX) with Automated Market Maker (AMM) Protocols

As an integral part of the decentralized finance (DeFi) ecosystem, decentralized exchanges (DEXs) with automated market maker (AMM) protocols have gained massive traction with the recently revived interest in blockchain and distributed ledger technology (DLT) in general. Instead of matching the buy and sell sides, automated market makers (AMMs) employ a peer-to-pool method and determine asset price algorithmically through a so-called conservation function. To facilitate the improvement and development of AMM-based decentralized exchanges (DEXs), we create the first systematization of knowledge in this area. We first establish a general AMM framework describing the economics and formalizing the system’s state-space representation. We then employ our framework to systematically compare the top AMM protocols’ mechanics, illustrating their conservation functions, as well as slippage and divergence loss functions. We further discuss security and privacy concerns, how they are enabled by AMM-based DEXs’ inherent properties, and explore mitigating solutions. Finally, we conduct a comprehensive literature review on related work covering both DeFi and conventional market microstructure.

Exchange-Traded Funds, Liquidity, and Centralized Risk Books: Moving Liquidity beyond the Portfolio

Since 1993, exchange-traded fund (ETF) product development has grown from broad-based equity benchmark indexes (i.e., S&P 500 Index) into a variety of asset classes and innovative, nontraditional index and active strategies. With this evolution, ETF issuers look to ensure that an ETF product lineup is supported by appropriate market participants. ETF capital market teams engage market participants (authorized participants and market makers) to understand each trading firm’s specific trading, hedging, and risk management processes. Based on the capabilities, the capital market groups select an appropriate lead market maker/designated liquidity provider. This selection process includes a market participant due diligence process. Given that ETF trading involves portfolios of underlying securities, capital markets teams look to engage with market participants using centralized risk books. Centralized risk books enable market participants to digest a variety of investment strategies into a well-diversified firm portfolio. Trading firms segregate centralized risk books across specific asset classes (US domestic equities, international equities, fixed income, commodities) as well as maintain oversight at a global level.

A New Era of Automated Market-Makers (AMM) powered by Non-Fungible Tokens- A Review

The most well-known cryptocurrency, Bitcoin, is one of many that are sweeping the globe. Along with them, fungible tokens traded on numerous centralised or decentralised exchanges are different from non-fungible tokens traded on NFT marketplaces. The majority of NFTs are currently digital, and in the future, producers may innovate in this area to allow for more innovative user experiences. The blockchain and its NFTs can provide fantastic chances for artists and content producers to profit from their work. The NFT Marketplace intends to be at the centre of all these fantastic use cases for NFTs by giving users a platform to produce and exchange non-fungible tokens. NFTs offer a wide range of application cases. Automated Market Makers, which are essentially decentralised markets for crypto-tokens and offer users three core operations—depositing crypto tokens in exchange for AMM shares, performing a dual operation in which shares are obtained in exchange for base tokens, and exchanging two tokens for one another—are some of the main applications of DeFi. This conceptual research discusses AMMs that are already in existence on the Ethereum blockchain and their developments, including the AMM that is now being created on the Tezos blockchain. The goal of this study is to present a thorough understanding of blockchain technology and all of its practical uses, including voting, trading NFTs, etc. It then focuses on how NFTs are traded on various platforms before aiming for improved NFT trading marketplaces, namely Automated Market Makers on various blockchains like Ethereum and Tezos.

VIX to S&P 500 Correlation Over the Weekend: Are Market Makers Using S&P 500 Weekend Returns to Price VIX on Monday Morning?

This paper studied the correlation between the S&P 500 ETF (SPY) weekend returns and the VIX changes. Two distinct patterns are found: (1) VIX is dropping intraday and rising overnight; (2) a negative SPY weekend return correlates with VIX weekend change. We found the negative correlation is statistically significant (P=0.000). This proves that option market makers are using SPY Friday overnight returns to adjust the implied volatility the next morning. This may lead to a profitable options model that sells high IV options closing on Friday and buys them back next Monday, especially before the earnings announcement.

Dampening effect and market efficiency

The way informed traders use their privileged information affects the properties of asset prices. This paper analyzes the differences in market efficiency between the two most widely adopted informed trading paradigms (Grossman-Stiglitz-style and Kyle-style) in a unified three-period framework. The aggregate risk—the product of fundamental risk, liquidity trading risk, and traders’ risk aversion coefficient—uniquely determines three measures of market efficiencies, including price informativeness, return autocorrelations, and the unconditional expected utilities of uninformed market makers. In the Kyle-style model, a self-reinforcing dampening effect arises from informed traders’ trading on fundamental information and non-fundamental information about their prior positions, leading to less efficient markets, contrarian trading by informed traders, and a return reversal between the two trading periods. Our study proposes to estimate price informativeness using information from short-term return reversals.

Is There Any Pattern Regarding the Vulnerability of Smart Contracts in the Food Supply Chain to a Stressed Event? A Quantile Connectedness Investigation

Blockchain can support the food supply chain in several aspects. Particularly, food traceability and trading across pre-existing contracts can make the supply chain fast, error-free, and support in detecting potential fraud. A proper algorithm, keeping in mind specific geographic, demographic, and additional essential parameters, would let the automated market maker (AMM) supply ample liquidity to pre-determined orders. AMMs are usually run by a set of sequential algorithms called a ‘smart contract’ (SM). Appropriate use of SM reduces food waste, contamination, extra or no delivery in due course, and, possibly most significantly, increases traceability. However, SM has definite vulnerabilities, making it less adaptable at times. We are investigating whether they are genuinely vulnerable during stressful periods or not. We considered seven SM platforms, namely, Fabric, Ethereum (ETH), Waves, NEM (XEM), Tezos (XTZ), Algorand (ALGO), and Stellar (XLM), as the proxies for food supply-chain-based smart contracts from 29 August 2021 to 5 October 2022. This period coincides with three stressed events: Delta (Covid II), Omicron (Covid III), and the Russian invasion of Ukraine. We found strong traces of risk transmission, comovement, and interdependence of SM return among the diversified SMs; however, the SMs focused on the food supply chain ended up as net receivers of shocks at both of the extreme tails. All these SMs share a stronger connection in both positive shocks (bullish) and negative shocks (bearish).