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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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103206309412 · Jun 202019922001200920172026
48 results for Latent Liquidity Theory

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.

Latent order book models have allowed for significant progress in our understanding of price formation in financial markets. In particular they are able to reproduce a number of stylized facts, such as the square-root impact law. An important question that is raised -- if one is to bring such models closer to real mark…

2018-08-29abs ↗pdf ↗

The IMH suggests market price fluctuations are driven by order flow, not fundamental values.

problem Reconciling IMH with microstructure literature on market dynamics.
method Reviewed empirical facts and applied Latent Liquidity Theory to predict price impact multiplier.
result The multiplier MM is of order unity, consistent with IMH, and depends on stock volatility and daily traded market cap fraction.

Model predicts trading strategies based on latent demand and price impact.

problem Predicting strategic trading behavior of investors with private targets.
method Equilibrium model of dynamic trading, learning, and pricing by strategic investors.
result Trading strategies are a combination of target following, liquidity provision, and front-running based on latent demand and price pressure.

The goal of this paper is to explore the relationship between momentum effects and liquidity in cryptocurrency markets. Portfolios based on momentum-liquidity bivariate sorts are formed and rebalanced on a varying number of cryptocurrencies through time. We find a strong momentum effect in the most liquid cryptocurrenc…

2019-04-01abs ↗pdf ↗

Study examines liquidation, leverage, and optimal margin requirements in Bitcoin futures markets.

problem Understanding and optimizing margin requirements in Bitcoin futures markets.
method Empirical analysis using generalized extreme value theory and BitMEX data.
result Margin requirements need to be significantly higher to reduce daily margin calls.

JIT liquidity providers can sometimes reduce overall market liquidity by crowding out passive LPs.

problem JIT liquidity providers can reduce overall market liquidity by crowding out passive LPs.
method Game-theoretic model with asymmetrically informed agents to analyze JIT liquidity provision in blockchain-based decentralized exchanges.
result JIT LPs only provide liquidity to uninformed orders and crowd out passive LPs when order volume is not sufficiently elastic to pool depth, potentially reducing overall market liquidity.

Machine learning predicts liquid water properties from cluster data.

problem Accuracy of bulk properties from machine-learned potentials is limited by training data.
method Local, atom-centred descriptors enable prediction of bulk properties from cluster data.
result Excellent agreement with experimental and theoretical counterparts of liquid water properties.

We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 minutes) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of …

2015-04-12abs ↗pdf ↗

We present an extended version of the recently proposed "LLOB" model for the dynamics of latent liquidity in financial markets. By allowing for finite cancellation and deposition rates within a continuous reaction-diffusion setup, we account for finite memory effects on the dynamics of the latent order book. We compute…

2017-10-10abs ↗pdf ↗

New neural networks with variable time constants for better time-series prediction.

problem Improving neural network performance in time-series prediction.
method Constructing networks of linear dynamical systems modulated by nonlinear gates, using numerical differential equation solvers.
result Liquid Time-Constant Networks (LTCs) yield superior performance on time-series prediction tasks.

We review the evidence that the erratic dynamics of markets is to a large extent of endogenous origin, i.e. determined by the trading activity itself and not due to the rational processing of exogenous news. In order to understand why and how prices move, the joint fluctuations of order flow and liquidity - and the way…

2010-09-15abs ↗pdf ↗

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.

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…

2017-01-05abs ↗pdf ↗

We formalize how markets aggregate via arbitrage and quantify liquidity loss.

problem How financial markets aggregate and the loss of liquidity.
method Characterize markets via utility functions, use thermodynamics analogy, derive limit order book representation, compute aggregation loss.
result Arbitrage-mediated aggregation leads to market-dynamical entropy quantifying liquidity loss.

Study on liquid-vapor interfaces in stable equilibrium without assuming prior regularity.

problem Understanding the conditions for a liquid-vapor interface to be in stable equilibrium without assuming prior regularity.
method Proposes a weakest set of mathematical assumptions using varifold regularity theory and identifies a suitable stability condition.
result The liquid-vapor interface is a smoothly embedded analytic surface in stable equilibrium.

Study of knotted defects in smectic liquid crystals using topological knot theory.

problem Understanding the topological structure of knotted defects in smectic liquid crystals.
method Investigation of screw and edge dislocations, focusing on their radial surface structure and knot fibration.
result Established a connection between smectic defects and knot theory, revealing the topological knotting of defects.

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).

Cryptocurrencies are examined through the asset flow equations and experimental asset markets. Since tangible value of a typical cryptocurrency is non-existent, the theory suggests that price will gravitate toward liquidity value, i.e., the total amount of cash available for purchase of the asset divided by the number …

2018-02-27abs ↗pdf ↗

The study extends SPT to account for real-world transaction costs, improving portfolio performance.

problem Real-world transaction costs affect portfolio performance, especially during market stress.
method Developed a continuous-time model with stochastic transaction costs and derived lower bounds for cost-adjusted wealth.
result Functionally generated portfolios can still achieve relative arbitrage after accounting for transaction costs.

This paper analyzes and compares different Automated Market Maker mechanisms.

problem Impermanent loss in Constant Function Market Makers.
method Mean-Variance analysis of liquidity providers' profit and loss, comparison of different mechanisms.
result Optimized oracle-based mechanisms outperform Constant Function Market Makers.

Sunshine trading theory predicts lower execution costs and liquidity provision through explicit preannouncements, but evidence is scarce in traditional markets.

problem Adverse selection on liquidity provision
method Reconstructing metaorders and comparing them with visible TWAP executions
result Visible TWAPs face lower execution costs and leave a smaller permanent price impact compared to hidden metaorders.

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.

The study introduces new liquidity measures and models for assets with extreme liquidity.

problem Modeling assets with extreme liquidity, especially in crypto markets.
method Developed innovative liquidity premium measures, liquidity-adjusted return and volatility models, and used ARMA-GARCH/EGARCH models.
result The liquidity-adjusted models outperform traditional models in predicting asset performance at extreme liquidity.

The paper models market dynamics using a limit order book system to explain slippage and inefficiency.

problem Inefficiency in matching markets due to structural liquidity constraints and slippage.
method Introduces a market microstructure framework with a latent preference state matrix and a dynamic discrete choice execution model.
result Persistent slippage and regional invariance of preference orderings are explained by liquidity thresholds.

A liquidity measure based on consideration and price range is proposed. Initially defined for daily data, Liquidity Index (LIX) can also be estimated via intraday data by using a time scaling mechanism. The link between LIX and the liquidity measure based on weighted average bid-ask spread is established. Using this li…

2014-12-16abs ↗pdf ↗

Using a large database of 8 million institutional trades executed in the U.S. equity market, we establish a clear crossover between a linear market impact regime and a square-root regime as a function of the volume of the order. Our empirical results are remarkably well explained by a recently proposed dynamical theory…

2018-11-13abs ↗pdf ↗

The study identifies features making cross-impact relevant in explaining price variance of US assets.

problem Understanding the relevance of cross-impact in explaining price variance of US assets.
method Using tick-by-tick data spanning 5 years for 500 US assets, the study investigates the features making cross-impact relevant.
result Price formation is endogenous within highly liquid assets, influencing less liquid correlated products with a constrained impact velocity.

Research proposes a model to estimate transaction costs and assess asset liquidity risk.

problem Lack of standardized models for asset liquidity risk in asset management.
method Develops a market impact model and a two-regime model based on power-law property.
result Defines liquidity measures and applies model to stocks and bonds.

Improved ARMA-GARCH model for illiquid assets like cryptocurrencies.

problem Inadequate modeling of illiquid assets, especially cryptocurrencies, with traditional ARMA-GARCH models.
method Introducing liquidity-adjusted liquidity jump and diffusion metrics into ARMA-GARCH framework.
result The liquidity-adjusted model improves model fit and volatility sensitivity for cryptocurrencies.

Optimizes liquidity provision in decentralized exchanges with utility indifference market makers.

problem Impermanent loss in decentralized exchanges without transaction fees.
method Mathematical formulation of liquidity provision, focusing on utility indifference market makers.
result No-arbitrage conditions and optimal arbitrage strategies are established.

Third part of a study on liquidity risk in asset management, focusing on managing the asset-liability liquidity risk.

problem Managing the asset-liability liquidity risk in asset management.
method Develops a methodological and practical framework for liquidity stress testing programs.
result Proposes measurement, management, and monitoring tools for controlling the liquidity gap.