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on Market Microstructure |
| By: | \'Alvaro Cartea; Sebastian Jaimungal; Leandro S\'anchez-Betancourt |
| Abstract: | We study the perfect information Nash equilibrium between a broker and her clients -- an informed trader, and an uniformed trader. In our model, the broker trades in the lit exchange where trades have instantaneous and transient price impact with exponential resilience, while both clients trade with the broker. The informed trader and the broker maximise expected wealth subject to inventory penalties, while the uninformed trader is not strategic and sends the broker random buy and sell orders. We characterise the Nash equilibrium of the trading strategies with the solution to a coupled system of forward-backward stochastic differential equations (FBSDEs). We solve this system explicitly and study the effect of information in the trading strategies of the broker and the informed trader. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.10561 |
| By: | Robert McLaughlin; Nir Chemaya; Dingyue Liu; Dahlia Malkhi |
| Abstract: | Trading on decentralized exchanges via an Automated Market Maker (AMM) mechanism has been massively adopted, with a daily trading volume reaching $1B. This trading method has also received close attention from researchers, central banks, and financial firms, who have the potential to adopt it to traditional financial markets such as foreign exchanges and stock markets. A critical challenge of AMM-powered trading is that transaction order has high financial value, so a policy or method to order transactions in a "good" (optimal) manner is vital. We offer economic measures of both price stability (low volatility) and inequality that inform how a "social planner" should pick an optimal ordering. We show that there is a trade-off between achieving price stability and reducing inequality, and that policymakers must choose which to prioritize. In addition, picking the optimal order can often be costly, especially when performing an exhaustive search over trade orderings (permutations). As an alternative we provide a simple algorithm, Clever Look-ahead Volatility Reduction (CLVR). This algorithm constructs an ordering which approximately minimizes price volatility with a small computation cost. We also provide insight into the strategy changes that may occur if traders are subject to this sequencing algorithm. |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2408.02634 |
| By: | Robert Boyce; Martin Herdegen; Leandro S\'anchez-Betancourt |
| Abstract: | We study liquidity provision in the presence of exogenous competition. We consider a `reference market maker' who monitors her inventory and the aggregated inventory of the competing market makers. We assume that the competing market makers use a `rule of thumb' to determine their posted depths, depending linearly on their inventory. By contrast, the reference market maker optimises over her posted depths, and we assume that her fill probability depends on the difference between her posted depths and the competition's depths in an exponential way. For a linear-quadratic goal functional, we show that this model admits an approximate closed-form solution. We illustrate the features of our model and compare against alternative ways of solving the problem either via an Euler scheme or state-of-the-art reinforcement learning techniques. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.17393 |
| By: | Walter Hernandez Cruz; Jiahua Xu; Paolo Tasca; Carlo Campajola |
| Abstract: | Fiat-pegged stablecoins are by nature exposed to spillover effects during market turmoil in Traditional Finance (TradFi). We observe a difference in TradFi market shocks impact between various stablecoins, in particular, USD Coin (USDC) and Tether USDT (USDT), the former with a higher reporting frequency and transparency than the latter. We investigate this, using top USDC and USDT liquidity pools in Uniswap, by adapting the Marginal Cost of Immediacy (MCI) measure to Uniswap's Automated Market Maker, and then conducting Difference-in-Differences analysis on MCI and Total Value Locked (TVL) in USD, as well as measuring liquidity concentration across different providers. Results show that the Silicon Valley Bank (SVB) event reduced USDC's TVL dominance over USDT, increased USDT's liquidity cost relative to USDC, and liquidity provision remained concentrated with pool-specific trends. These findings reveal a flight-to-safety behavior and counterintuitive effects of stablecoin transparency: USDC's frequent and detailed disclosures led to swift market reactions, while USDT's opacity and less frequent reporting provided a safety net against immediate impacts. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.11716 |