Research
On-device research index

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.

168,742 papers · 148 categories

Trend · papers per month

10213141 · May 202619922001200920172026
48 results for liquidity fluctuations

New framework detects crypto wash trading using liquidity measures.

problem Detecting and monitoring wash trading in crypto assets.
method Developed a new framework to detect wash trading through real-time liquidity fluctuation measures.
result Joint elevation in liquidity jump and diffusion indicates wash trading in crypto assets.

We introduce a microscopic model for the dynamics of the order book to study how the lack of liquidity influences price fluctuations. We use the average density of the stored orders (granularity gg) as a proxy for liquidity. This leads to a Price Impact Surface which depends on both volume ωω and gg. The dependence …

2009-02-24abs ↗pdf ↗

In this manuscript we analyse the leading statistical properties of fluctuations of (log) 3-month US Treasury bill quotation in the secondary market, namely: probability density function, autocorrelation, absolute values autocorrelation, and absolute values persistency. We verify that this financial instrument, in spit…

2007-06-08abs ↗pdf ↗

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 ↗

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.

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…

2003-12-30abs ↗pdf ↗

Model explains yield curve dynamics using order flow shocks.

problem Understanding the yield curve's fluctuations and their relation to order flows.
method Relates exogenous shocks to order flow surprises, creating a microstructural model that incorporates price and order flow dynamics.
result The model explains yield curve dynamics with fewer parameters and generates liquidity-dependent correlations.

Develops a new model to better estimate cryptocurrency and stock volatility.

problem Misrepresentation of volatility and co-movement in traditional models.
method Introduces liquidity-sensitive multivariate volatility framework with novel liquidity measures.
result Liquidity-adjusted models yield more stable and interpretable risk structures.

Study on order book dynamics with uniform catastrophes, explaining volatility and trends.

problem Understanding volatility and trends in financial markets with different types of liquidity.
method Stochastic models and population processes with uniform catastrophes.
result Law of large numbers, central limit theorem, and large deviations proved for the model.

Proposes a new model to measure trade impact and information content in fluctuating markets.

problem Measuring price impact and information content of trades in a time-varying market setting.
method Non-linear observation-driven model for dynamically estimating market impact and information content.
result Market impact shows intraday patterns with large fluctuations, some of which are exogenous.

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.

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 ↗

The paper examines how cheaper and faster chains affect Uniswap v3 liquidity and profitability.

problem Impact of cheaper and faster chains on Uniswap v3 liquidity and profitability.
method Comparative analysis of Uniswap v3 activity on different chains with varying gas prices and block times.
result Liquidity providers are more capital efficient and receive higher fee returns on cheaper and faster chains.

For the London Stock Exchange we demonstrate that the signs of orders obey a long-memory process. The autocorrelation function decays roughly as τατ^{-α} with α0.6α\approx 0.6, corresponding to a Hurst exponent H0.7H \approx 0.7. This implies that the signs of future orders are quite predictable from the signs of past orde…

2003-11-04abs ↗pdf ↗

The intraday pattern, long memory, and multifractal nature of the intertrade durations, which are defined as the waiting times between two consecutive transactions, are investigated based upon the limit order book data and order flows of 23 liquid Chinese stocks listed on the Shenzhen Stock Exchange in 2003. An inverse…

2008-06-15abs ↗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.

Optimizes liquidity withdrawal timing for AMM LPs to balance fees and impermanent loss.

problem Balancing fees and impermanent loss in automated market makers.
method Stochastic control problem with endogenous stopping time, numerical solutions via Euler scheme and Longstaff-Schwartz method.
result Optimal exit strategy depends on volatility, fees, and market dynamics.

Optimal trading strategies in fluctuating financial markets are analyzed using complex mathematical models.

problem Optimal execution of trades in markets with fluctuating liquidity and order book depth.
method Continuous-time limit order book model with càdlàg semimartingale strategies, quadratic BSDEs.
result Characterization of minimal execution costs and existence of optimal strategies.

Construct intrinsic Langevin dynamics for rigid inclusions on curved surfaces.

problem Stochastic dynamics of rigid inclusions on curved surfaces.
method Cartan's method of moving frames, Hamiltonian equations, intrinsic Langevin equations, Fokker-Planck equation.
result Extracted overdamped equations for accurate simulations of diffusion processes.

Study proposes optimal risk-aware interest rates for crypto lending protocols.

problem Determining optimal interest rates for decentralized lending protocols to maximize profit and minimize risk.
method Agent-based model, Riccati-type ODEs for linear behaviors, Monte-Carlo estimator and deep learning for nonlinear behaviors.
result Calibrated model shows superior risk-adjusted performance compared to industry-standard interest rate models.

The statistical properties of the return intervals τqτ_q between successive 1-min volatilities of 30 liquid Chinese stocks exceeding a certain threshold qq are carefully studied. The Kolmogorov-Smirnov (KS) test shows that 12 stocks exhibit scaling behaviors in the distributions of τqτ_q for different thresholds qq. …

2008-07-11abs ↗pdf ↗

The paper models natural gas futures prices and volatility, using Monte Carlo and reinforcement learning.

problem Hedging and selecting delivery strategies in natural gas markets.
method Dynamical model for futures prices, least-square Monte Carlo simulation, reinforcement learning.
result Calibrated futures price quotes and implied volatility smiles for different delivery periods.

Study on heavy tails in closing auction returns, explaining imbalance through limit order submission.

problem Understanding heavy tails in closing auction return distributions.
method Used the stochastic call auction model of Derksen et al. (2020a) to derive and verify a relation between tail exponents.
result Large closing price fluctuations are not caused by large market orders, but by imbalance in limit orders.

In order to understand the origin of stock price jumps, we cross-correlate high-frequency time series of stock returns with different news feeds. We find that neither idiosyncratic news nor market wide news can explain the frequency and amplitude of price jumps. We find that the volatility patterns around jumps and aro…

2008-03-12abs ↗pdf ↗

In this article we revisit the classic problem of tatonnement in price formation from a microstructure point of view, reviewing a recent body of theoretical and empirical work explaining how fluctuations in supply and demand are slowly incorporated into prices. Because revealed market liquidity is extremely low, large …

2008-09-04abs ↗pdf ↗

We study an agent-based stock market model with heterogeneous agents and friction. Our model is based on that of Foellmer-Schweizer(1993): The process of a stock price in a discrete-time framework is determined by temporary equilibria via agents' excess demand functions, and the diffusion approximation approach is appl…

2013-01-28abs ↗pdf ↗

We develop a behavioral model for liquidity and volatility based on empirical regularities in trading order flow in the London Stock Exchange. This can be viewed as a very simple agent based model in which all components of the model are validated against real data. Our empirical studies of order flow uncover several i…

2007-09-03abs ↗pdf ↗

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.

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 ↗

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.