Study shows pre-event L2 liquidity state predicts crypto futures liquidity better than event labels.
problem Understanding how crypto futures liquidity changes over time.
method Combining L2 order book data, trade-flow records, and macro-event windows to define discrete liquidity-state transitions and evaluate models.
result Pre-event L2 liquidity state predicts post-event liquidity regimes better than event labels, and order flow adds value only when layered on top of the state model.
The paper analyzes game theory in convertible contracts during liquidity events.
problem Optimizing payments in convertible contracts during liquidity events.
method Defined a general model for games, showed non-existence of pure strategy Nash equilibria, developed algorithms for computing equilibria.
result Optimum pure strategy Nash equilibria exist when all contracts are of the same type (SAFE).
Study adapts liquidity model to equity auctions, revealing accelerated event rates and reduced price impact.
problem Understanding and predicting price dynamics in equity auctions.
method Adapted latent/revealed order book framework to equity auctions, measuring order submissions, cancellations, and diffusion rates.
result Equity auctions exhibit accelerated event rates leading to reduced price impact and decreased volatility.
Empirical study on UEEs reveals liquidity's role and universal recovery patterns.
problem Understanding and stabilizing financial markets affected by UEEs.
method Comparative analysis of UEEs over different years in US stock market.
result Liquidity is dominant in UEEs emergence and recovery patterns are universal.
This paper optimizes liquidation strategies in DeFi protocols to prevent MEV attacks.
problem Predatory price manipulations and Maximal Extractable Value (MEV) attacks in DeFi protocols.
method Dynamic program modeling, Constant Product Market Maker (CPMM) transaction fees analysis.
result CPMM transaction fees make liquidation manipulations unprofitable for attackers.
Study finds no significant short-term impact on liquidity supply after protocol fees were reduced.
problem Liquidity provider welfare is affected by protocol fees, but the impact on liquidity supply is unclear.
method Used a matched-overlap event-study difference-in-differences design to estimate the liquidity-supply response to take-rate cuts.
result No significant short-term impact on active liquidity or local depth; no change in LP participation or composition.
This paper models financial contagion with endogenously determined market liquidity.
problem Financial contagion and its impact on market liquidity during price drops.
method Developed a joint clearing system for interbank payments, asset prices, and market liquidity, with endogenous market capacity.
result Endogenous market liquidity significantly affects system risk during financial contagion.
Study shows foreign institutional investment increases liquidity commonality in large Australian stocks.
problem Impact of foreign institutional investment on liquidity commonality in Australian stocks.
method Cross-sectional and time-series analysis of Australian equity market data.
result Foreign institutional investment contributes to increased exposure of large stocks to unexpected liquidity events.
We propose a framework to study the optimal liquidation strategy in a limit order book for large-tick stocks, with spread equal to one tick. All order book events (market orders, limit orders and cancellations) occur according to independent Poisson processes, with parameters depending on price move directions. Our goa…
RED-2400 is a public benchmark of trading events from a Solana exchange, labeled by algorithmic rejection.
problem Analyzing algorithmically-rejected trading events for insights into market dynamics.
method Public dataset of 6,660 algorithmically-rejected trading events, linked to post-rejection price and liquidity trajectories.
result First window of a planned series of datasets extending the time horizon and enabling regime-stratified analysis.
We study the relaxation dynamics of the bid-ask spread and of the midprice after a sudden, large variation of the spread, corresponding to a temporary crisis of liquidity in a double auction financial market. We find that the spread decays very slowly to its normal value as a consequence of the strategic limit order pl…
We introduce an event based framework of directional changes and overshoots to map continuous financial data into the so-called Intrinsic Network - a state based discretisation of intrinsically dissected time series. Defining a method for state contraction of Intrinsic Network, we show that it has a consistent hierarch…
Stablecoin liquidity was affected by the SVB collapse, with USDC's transparency leading to market reactions.
problem Impact of stablecoin transparency on liquidity during market turmoil.
method Adapted MCI measure to Uniswap, Difference-in-Differences analysis on MCI and TVL, measured liquidity concentration.
result USDC's transparency led to swift market reactions, while USDT's opacity provided a safety net.
Modeling high-frequency order book data with Hawkes-Markovian process.
problem Capturing the dynamics of high-frequency order book events.
method Hawkes process with Markovian baseline intensities, LASSO regularization, and Akaike Information Criteria.
result Effective modeling of order book dynamics with reduced parameter redundancy.
Study develops hybrid model to mitigate stablecoin liquidity risk.
problem Increasing integration of stablecoins introduces liquidity risk during market stress.
method Hybrid monetary architecture with 100% reserve backing and liquidity facilities.
result Demonstrates significant reduction in peg deviations and stress persistence.
New method detects market liquidity changes using order book data.
problem Detecting changes in market liquidity.
method Marked Hawkes processes and minimax quickest detection problem for doubly-stochastic Poisson process.
result Optimal stopping rule for detecting intensity changes in market liquidity.
Model uses Navier-Stokes equations to assess liquidity and systemic risk.
problem Traditional models fail to capture real market fluctuations and extreme events.
method Develops and validates a mathematical model based on Navier-Stokes equations, incorporating 13 macroeconomic and financial parameters.
result Model effectively describes liquidity dynamics, systemic risk, and extreme scenarios.
Study on liquidity providers' performance in decentralized exchanges.
problem Unclear profitability of liquidity providers in decentralized exchanges.
method Reconstructing LP PnL dynamics from on-chain events, introducing a new metric.
result Only about one out of six LPs avoids losses, suggesting open questions about LP participation motives.
The paper develops a new model for order book dynamics using Hawkes processes.
problem Capturing the dynamics of order flow and liquidity migration in financial markets.
method Develops a mesoscopic model using Hawkes processes to describe interactions between order arrivals, cancellations, and liquidity movement.
result Derives a diffusive limit for the order book dynamics, providing a unified framework for market microstructure.
We present an empirical study of the intertwined behaviour of members in a financial market. Exploiting a database where the broker that initiates an order book event can be identified, we decompose the correlation and response functions into contributions coming from different market participants and study how their b…
Agent-based model simulates market dynamics with real-time order matching.
problem Realistic simulation of market dynamics with realistic price impact.
method Agent-based model with asynchronous, event-time order matching.
result Realistic price impact curves and stylized facts presented.
The study identifies impactful news articles based on liquidity changes, improving asset return prediction.
problem Evaluating the sentiment of financial news articles for institutional investors.
method Liquidity-driven variables are used to identify impactful news articles, focusing on liquidity mode switches.
result The screened dataset leads to superior performance in short-term asset return prediction.
Study shows flash crashes in finance are self-organized criticality events.
problem Understanding and predicting anomalous price events in high-frequency finance.
method Investigated volume distributions during flash crashes and linked them to self-organized criticality.
result Volume distributions during flash crashes indicate a diverging second moment, suggesting self-organized criticality.
In our empirical study, we examine the price of liquid stocks after experiencing a large intraday price change using data from the NYSE and the NASDAQ. We find significant reversal for both intraday price decreases and increases. The results are stable against varying parameters. While on the NYSE the large widening of…
This paper develops a method to select a reference contract for multi-contract quoting to minimize execution risk.
problem Minimizing execution risk in multi-contract quoting sequences.
method Develops a diagnostic framework using order-flow Hawkes forecasts and CLF to select a stable reference contract.
result Event-history and LOB-state signals offer complementary views for reference-contract selection.
The profitability of CPMMs is significantly impacted by mint and burn fees.
problem Understanding the profitability of decentralized exchanges.
method Formalized liquidity providers' profitability conditions, studied the effect of mint and burn fees, and compiled a large data set from Uniswap V2 transactions.
result The profitability of liquidity provision is severely affected by mint and burn costs.
We present a new volatility model, simple to implement, that includes a leverage effect whose return-volatility correlation function fits to empirical observations. This model is able to capture both the "retarded effect" induced by the specific risk, and the "panic effect", which occurs whenever systematic risk become…
The study examines stock splits and their effects on companies, managers, and shareholders.
problem Misunderstandings and confounding factors around stock splits and their impacts.
method Selected database analysis of nine recent events, examining market impact, trading volume, and shareholder base.
result Stock splits enhance trading volume, increase shareholder base, and improve market liquidity.
We study the cause of large fluctuations in prices in the London Stock Exchange. This is done at the microscopic level of individual events, where an event is the placement or cancellation of an order to buy or sell. We show that price fluctuations caused by individual market orders are essentially independent of the v…
Deep learning for particle classification on large event images.
problem Training deep learning models on large, high-fidelity event images from MicroBooNE is challenging and time-consuming.
method Scaling training to multiple GPUs and architectures, using simulated MicroBooNE events.
result Demonstrated successful scaling of particle classification training to multiple GPUs and architectures.
Model shows liquidity stress crossover in market dynamics.
problem Identifying genuine market instabilities in agent-based models.
method Applied Bouchaud's phase-diagram method to a continuous-double-auction model.
result Emergent liquidity-stress crossover with specific tipping point parameters.
Uniform AMMs control loss in prediction markets.
problem Controlling loss in prediction markets.
method Loss-versus-rebalancing (LVR) framework and uniform AMMs.
result Uniform AMMs achieve proportional LVR to pool value.
Uniform AMMs control loss in prediction markets.
problem Controlling loss in prediction markets.
method Loss-versus-rebalancing (LVR) framework and uniform AMMs.
result Uniform AMMs achieve proportional LVR to pool value.
Study analyzes risk management in Aave and Compound lending protocols, finding v3 better than v2.
problem Risk management in decentralized lending protocols.
method Cross-version and cross-chain analysis using fixed effects model.
result v3 protocols have better risk management, with stronger impact on L2 blockchains.
Passive investing can incur hidden costs due to market timing inefficiencies.
problem Hidden costs in passive investing due to market timing inefficiencies.
method Analysis of passive investing strategies, including gradual share acquisition and post-announcement trading.
result Post-announcement trading can earn significant profits, often exceeding 1%.
This paper formalizes autodeleveraging as online learning, providing robustness results and algorithms for better performance.
problem Autodeleveraging as a mechanism to restore solvency in perpetual futures markets when liquidation and insurance buffers are insufficient.
method Formalizes autodeleveraging as online learning on a PNL-haircut domain, using an algorithm to recover solvency.
result The optimized algorithm achieves about 2.6% of an upper bound on regret, reducing overshoot to $3M.
Study shows multifractality emerging in decentralized cryptocurrency trading.
problem Understanding financial dynamics in decentralized cryptocurrency markets.
method Multifractal Detrended Fluctuation Analysis (MFDFA) on tick-by-tick transaction data.
result Multifractality is emerging in decentralized cryptocurrency trading, with larger fluctuations dominating.
Study finds anomalies in high-frequency S&P 500 price changes.
problem Anomalies in high-frequency S&P 500 price changes.
method Using NBBO event-time data, the study forms pairs of backward and forward price increments, standardizes them, and estimates expected responses on a fine grid of push magnitudes.
result Persistent structural shift in expected responses: near zero for short lags, pronounced tails for long lags, indicating correlation between larger historical pushes and nonzero responses.
Algorithmic trading systems on DEXs reject most candidate tokens, but the counterfactual outcome of rejected candidates is rarely measured.
problem Measuring the counterfactual outcome of rejected tokens in algorithmic trading systems on decentralized exchanges.
method Post-Rejection Follow-up Sampling (PRFS) introduces a methodology for collecting and analyzing the data needed to evaluate filter precision against actual market outcomes of rejected candidates.
result PRFS produces the data needed to evaluate filter precision against actual market outcomes of rejected candidates, not against synthetic backtest reconstructions.
A limit order book provides information on available limit order prices and their volumes. Based on these quantities, we give an empirical result on the relationship between the bid-ask liquidity balance and trade sign and we show that liquidity balance on best bid/best ask is quite informative for predicting the futur…
Hawkes processes have seen a number of applications in finance, due to their ability to capture event clustering behaviour typically observed in financial systems. Given a calibrated Hawkes process, of concern is the statistical fit to empirical data, particularly for the accurate quantification of self- and mutual-exc…
This study examines non-retail trading on Polymarket, revealing unique behavior patterns and structural limitations.
problem Lack of address-level quote-lifecycle data in Polymarket prediction markets.
method Empirical analysis of 13 million order-filled events using DBSCAN clustering on a six-feature fill-side vector.
result Non-retail behavior is uni-modal, contradicting previous archetypal hypotheses.
Study analyzes cryptocurrency pump-and-dump dynamics using minute-level data.
problem Identifying and quantifying insider trading in cryptocurrency markets.
method Algorithmic identification of insider volume spikes, conservative profit bounds calculation, social-media verification.
result Median returns above 100%, upper-quartile returns exceeding 2000% for insider profits.
The paper categorizes and analyzes various event-linked perpetual futures contracts.
problem Developing a risk-design framework for complex event-linked perpetual futures.
method Formal taxonomy of seven pure-form canonical variants, organized along four design axes.
result Detailed analysis of microstructure properties and limitations of various variants.
Credit Value Adjustment (CVA) is the difference between the value of the default-free and credit-risky derivative portfolio, which can be regarded as the cost of the credit hedge. Default probabilities are therefore needed, as input parameters to the valuation. When liquid CDS are available, then implied probabilities …
DeFi exploits lead to reduced CP spreads, contrary to contagion hypothesis.
problem Vulnerabilities in DeFi destabilize traditional short-term funding markets.
method Analysis of commercial paper spreads and regulatory segmentation.
result DeFi exploits lead to a 'Flight-to-Quality' pattern, narrowing rather than widening CP spreads.
Optimizes liquidity provision intervals for profitable AMM participation.
problem Financial losses from poor liquidity provision intervals and reallocation costs.
method Developed a tractable stochastic optimization problem.
result Computes optimal liquidity provision intervals for profitable liquidity concentration.
Study shows how crypto asset liquidity is affected by wash trading and proposes treatment to reduce liquidity diffusion.
problem Understanding and reducing crypto asset wash trading to improve liquidity.
method Proposed a two-component model for liquidity (jump and diffusion) and demonstrated the effectiveness of autoregressive models.
result Treatment on wash trading significantly reduces liquidity diffusion but not liquidity jump.