Study shows HFT improves market liquidity indicators.
problem Impact of high-frequency trading on market liquidity.
method Agent-based simulations comparing HFT and non-HFT markets.
result All liquidity indicators improved in markets with HFTs.
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48 results for “liquidity indicators”
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.
Project forecasts liquidity withdrawal using machine learning models.
problem Predicting liquidity withdrawal at individual stock levels.
method Tested a framework using machine learning models (AR, HAR, XGBoost) on Nasdaq MBO data.
result Introduced the Liquidity Withdrawal Index (LWI) for measuring liquidity removal.
The Impact of Designated Market Makers on Market Liquidity and Competition: A Simulation Approachq-fin.TR
This study examines how DMMs affect market liquidity and competition.
problem The impact of DMMs on market liquidity and competition.
method Agent-based simulations to explore the effects of varying competition levels and incentive structures among DMMs.
result Optimal competition among DMMs maximizes liquidity benefits without negatively impacting price discovery.
Predicting the intraday stock jumps is a significant but challenging problem in finance. Due to the instantaneity and imperceptibility characteristics of intraday stock jumps, relevant studies on their predictability remain limited. This paper proposes a data-driven approach to predict intraday stock jumps using the in…
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.
Paper develops a risk scoring framework for tokenized RWA markets.
problem Tokenized assets may not reflect true risk due to illiquidity and concentration.
method Develops a risk scoring framework based on observable indicators.
result Assets with limited transfer activity and concentrated ownership have high empirical risk.
The study finds a liquidity premium in stock returns, but only after correcting for microstructure noise.
problem The positive association between expected idiosyncratic volatility and expected stock returns.
method Developed a novel method to eliminate microstructure influences from stock returns and estimate idiosyncratic volatility.
result The liquidity premium in value-weighted portfolios is driven by liquidity in the prior month after correcting for microstructure noise.
This letter investigates the dynamic relationship between market efficiency, liquidity, and multifractality of Bitcoin. We find that before 2013 liquidity is low and the Hurst exponent is less than 0.5, indicating that the Bitcoin time series is anti-persistent. After 2013, as liquidity increased, the Hurst exponent ro…
L'effet de levier de trésorerieq-fin.GN
The effect of leverage on liquidity is a tool for analysing the level of liquidity for a given production process. It measures the sensitivity of the level of liquidity that results from changes in the volume of production and unit operating margin. A commercial activity is liquid at the moment when all costs are cover…
Paper introduces a method to assess liquidity risk in meme tokens using entity-linked address analysis.
problem High market volatility and vulnerability to manipulation in meme tokens.
method Multi-dimensional approach integrating fund flow analysis, behavioral similarity, and anomalous transaction detection.
result Significant disparities between apparent and actual liquidity in meme token markets.
PEARL uses AI to replicate private equity performance with liquid assets.
problem Lack of access to private equity due to high costs and complexity.
method Combines AI with liquid assets, incorporating asymmetry for better performance.
result Model outperforms liquid proxies and aligns with private equity benchmarks.
We investigate the correlation properties of transaction data from the New York Stock Exchange. The trading activity f(t) of each stock displays a crossover from weaker to stronger correlations at time scales 60-390 minutes. In both regimes, the Hurst exponent H depends logarithmically on the liquidity of the stock, me…
This study examines whether tokenized assets improve liquidity and finds significant differences across categories.
problem Improving liquidity for real-world assets through tokenization.
method Examined tokenized real-world assets using Ethereum-based data, measuring liquidity through turnover, active addresses, and active-month indicator.
result Gold-backed tokens show more persistent on-chain activity than Treasury and private-credit-related products, but asset value alone does not reliably predict liquidity.
Slippage-at-Risk (SaR): A Forward-Looking Liquidity Risk Framework for Perpetual Futures Exchangesq-fin.RM
A new framework assesses liquidity risk in perpetual futures exchanges.
problem Measuring and predicting liquidation execution risk in perpetual futures markets.
method Slippage-at-Risk (SaR) framework, comprising three metrics: cross-sectional slippage quantile, expected slippage, and aggregate dollar-denominated tail slippage.
result SaR provides a forward-looking assessment of liquidation execution risk, predictive of systemic stress.
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.
We investigate whether fractal markets hypothesis and its focus on liquidity and invest- ment horizons give reasonable predictions about dynamics of the financial markets during the turbulences such as the Global Financial Crisis of late 2000s. Compared to the mainstream efficient markets hypothesis, fractal markets hy…
The paper examines how insurers manage risks and liquidity in a dynamic market.
problem Model uncertainty in insurance pricing and competitive equilibrium.
method Analyzes insurers' robustness preferences and optimization strategies for underwriting and liquidity management.
result Robust insurance pricing leads to higher premiums and equity valuations compared to a benchmark.
In order to reduce signalling, traders may resort to limiting access to dark venues and imposing limits on minimum fill sizes they are willing to trade. However, doing this also restricts the liquidity available to the trader since an ever increasing quantity of orders are traded by algos in clips. An alternative is to…
In this research, we develop a trading strategy for the discrete-time optimal liquidation problem of large order trading with different market microstructures in an illiquid market. In this framework, the flow of orders can be viewed as a point process with stochastic intensity. We model the price impact as a linear fu…
A framework for simulating systemic risk and its application to the South African banking sectorq-fin.RM
We present a network-based framework for simulating systemic risk that considers shock propagation in banking systems. In particular, the framework allows the modeller to reflect a top-down framework where a shock to one bank in the system affects the solvency and liquidity position of other banks, through systemic mar…
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 …
Systemic liquidity risk, defined by the IMF as "the risk of simultaneous liquidity difficulties at multiple financial institutions", is a key topic in macroprudential policy and financial stress analysis. Specialized models to simulate funding liquidity risk and contagion are available but they require not only banks' …
RL-Exec uses reinforcement learning to optimize BTC-USD liquidation, outperforming traditional methods.
problem Optimizing liquidation strategies on BTC-USD limit-order books with transient impact and latency.
method PPO agent trained on historical BTC-USD limit-order book replays, incorporating impact resilience and fees.
result RL-Exec significantly outperforms TWAP and a VWAP-like baseline on BTC-USD liquidation, with performance improving with longer execution horizons.
In this paper, we provide non-parametric statistical tools to test stationarity of microstructure noise in general hidden Ito semimartingales, and discuss how to measure liquidity risk using high frequency financial data. In particular, we investigate the impact of non-stationary microstructure noise on some volatility…
Method identifies causal interactions between time series using extreme eigenvalue variability.
problem Detecting causal interactions between time series.
method Largest eigenvalue of lagged correlation matrices, measuring causal interactions through variability.
result The method outperforms traditional Granger causality tests in detecting structural changes.
The paper proposes a new model for financial order books without assuming prices or quantities.
problem Understanding the geometry of financial order books without assuming prices or quantities.
method Modeling financial order books as an inflationary relational system without metric, temporal, or price coordinates. Observable quantities arise through spectral embeddings of the graph Laplacian.
result Projected supply and demand are constrained to gamma-like functional forms, which can be observed as integrated-gamma cumulative profiles in high-frequency data.
LSTM model predicts stock prices with high accuracy in stable sectors but struggles with volatile ones.
problem Predicting stock prices in emerging markets with limited data.
method Developed and evaluated an LSTM network on historical OHLCV data and technical indicators.
result Strong predictive performance () for stable sectors, but challenges for volatile ones.
Study assesses impact of CBDC on financial stability in dual-currency economy.
problem Impact of CBDC on financial stability in dual-currency economy (Romania).
method Integrated analytical framework combining econometrics, machine learning, and behavioural modelling. CBDC adoption probabilities estimated using XGBoost and logistic regression models. Liquidity stress simulations and VAR, MSVAR, SVAR models capture macro-financial transmission.
result CBDC uptake would be moderate, primarily driven by digital readiness and trust in the central bank.
This study compares three volatility metrics for Bitcoin, highlighting high expected volatility.
problem Understanding Bitcoin's volatility in financial markets.
method Historical volatility, forecasted volatility (GARCH models), and implied volatility (from options market).
result High expected volatility across all methodologies, especially implied volatility.
Market Efficiency in Foreign Exchange Marketsphysics.soc-ph
We investigate the relative market efficiency in financial market data, using the approximate entropy(ApEn) method for a quantification of randomness in time series. We used the global foreign exchange market indices for 17 countries during two periods from 1984 to 1998 and from 1999 to 2004 in order to study the effic…
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.
Regulators require financial institutions to estimate counterparty default risks from liquid CDS quotes for the valuation and risk management of OTC derivatives. However, the vast majority of counterparties do not have liquid CDS quotes and need proxy CDS rates. Existing methods cannot account for counterparty-specific…
Investing with Cryptocurrencies -- evaluating their potential for portfolio allocation strategiesq-fin.PM
Investing in cryptocurrencies can improve portfolio risk-return profile, especially with diversification strategies.
problem Investing in cryptocurrencies and evaluating their potential for portfolio allocation strategies.
method Investigated different types of investors, various portfolio construction rules, and incorporated liquidity constraints.
result Cryptocurrencies can improve the risk-return profile of portfolios, especially with diversification strategies.
Automated Market Makers: A Stochastic Optimization Approach for Profitable Liquidity Concentrationq-fin.TR
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.
Agents learn to outperform in trading by using past and current prices.
problem Optimal trading performance beyond theoretical limits.
method Two-agent Almgren-Chriss liquidation game, schedule-learning, DDQN architectures.
result Agents with access to past and current prices achieve supra-competitive outcomes.
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.
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…
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.
Liquidity Stress Testing in Asset Management -- Part 3. Managing the Asset-Liability Liquidity Riskq-fin.RM
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.
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.
Optimal early liquidation strategy reduces financial losses during crises.
problem Substantial losses from simultaneous asset liquidation at depressed prices.
method Developed a worst-case approach for optimal early liquidation, considering uncertainty of other banks' decisions.
result Proposed robust optimal strategy maximizes liquid assets' value at clearing, even with uncertainty.
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.