Study analyzes impact of concentrated liquidity on trading fees and provider returns.
problem Impact of concentrated liquidity on trading fees and provider returns.
method Comparison of average liquidity provider returns before and after concentrated liquidity introduction; quantification of fundamental strategies performance.
result Concentrated liquidity strategies outperform in certain trading pairs and market conditions.
Uniswap V3 requires more decisions from liquidity providers, making it complex and risky.
problem Complexity and risk in liquidity provision on Uniswap V3.
method Developed a theoretical model and analyzed real data.
result Liquidity provision on Uniswap V3 is highly complex and risky.
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.
FLAIR measures LP competitiveness in AMMs, improving LP performance evaluations.
problem LP returns are affected by both market risk and competitive strategies.
method Introduces FLAIR metric to quantify LP competitiveness and assesses its impact on LP returns.
result FLAIR captures dynamic behavior of LPs and differentiates between active provisioning strategies.
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 paper extends liquidity returns in geometric mean markets to time-varying weights.
problem Understanding returns and no-arbitrage prices in geometric mean markets with time-varying weights.
method Extending known results for constant-weight G3Ms to the general case of G3Ms with time-varying and potentially stochastic weights.
result LP shares can replicate the payoffs of financial derivatives and various trading strategies.
Optimal fees for CFMMs prevent liquidity pools from competing to the bottom.
problem Maximizing liquidity provider returns in CFMMs with multiple pools.
method Theoretical and numerical analysis of Nash equilibria for optimal fees.
result Pure Nash equilibria of optimal fees exist for CFMMs using Uniswap's trade function.
This paper studies liquidity providers in decentralized exchanges.
problem Understanding how liquidity providers behave in DEXes.
method Analyzed operations on Uniswap, measured investment strategy, returns, and risks.
result Liquidity providers benefit from transaction fees and determine their strategy based on market changes.
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.
Optimal design of automated market makers for decentralized exchanges.
problem Maximizing utility for liquidity providers in decentralized exchanges.
method Modeling a risk-averse liquidity provider's optimal strategy and the optimal design of automated market makers.
result The optimal unit trading fee increases with asset volatility.
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.
The study uses equity order flow to forecast stock returns and resolves the liquidity premium puzzle.
problem The liquidity premium and its relation to investment horizons.
method Directly estimated Kyle's price-impact coefficient λ from daily equity order flow data.
result Signed order flow predicts stock returns, with volume volatility predicting lower returns.
Study analyzes factors affecting profits in crypto liquidity provision.
problem Liquidity providers lack guidance for developing profitable strategies.
method Developed a measurement model based on impermanent loss to analyze key parameters.
result Uncovered influences of key parameters on LPs' profits.
We develop an optimal currency hedging strategy for fund managers who own foreign assets to choose the hedge tenors that maximize their FX carry returns within a liquidity risk constraint. The strategy assumes that the offshore assets are fully hedged with FX forwards. The chosen liquidity risk metric is Cash Flow at R…
Market liquidity plays a vital role in the field of market micro-structure, because it is the vigor of the financial market. This paper uses a variable called convexity to measure the potential liquidity provided by order-book. Based on the high-frequency data of each stock included in the SSE (Shanghai Stock Exchange)…
Novel method reconstructs liquidity data for CLMMs, optimizing dynamic liquidity strategies.
problem Challenges in evaluating and optimizing CLMMs due to lack of historical liquidity data.
method Reconstructs historical liquidity states from swap transaction data using machine learning.
result Identifies outperformance of dynamic liquidity strategies over uniform allocation benchmarks.
Optimizes hedge ratio for delta-neutral liquidity positions in AMMs.
problem Balancing price exposure and liquidation risk in borrowing-funded delta-neutral positions.
method Model token prices as correlated geometric Brownian motions, derive optimal hedge ratio maximizing risk-adjusted return subject to liquidation probability constraint.
result Optimal hedge ratio h** = min(h*, h_bar(alpha)) lies between 50% and 70% for typical DeFi lending conditions.
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.
We review different approaches for measuring the impact of liquidity on CDS prices. We start with reduced form models incorporating liquidity as an additional discount rate. We review Chen, Fabozzi and Sverdlove (2008) and Buhler and Trapp (2006, 2008), adopting different assumptions on how liquidity rates enter the CD…
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.
This paper studies the risk-adjusted optimal timing to liquidate an option at the prevailing market price. In addition to maximizing the expected discounted return from option sale, we incorporate a path-dependent risk penalty based on shortfall or quadratic variation of the option price up to the liquidation time. We …
This paper compares token and equity financing for startups.
problem Understanding differences in return rates between token and equity financing.
method Developed a three-period model to analyze liquidity and return differences.
result Entrepreneurs can achieve higher payoffs by issuing tokens, especially for risk-averse investors with liquidity needs.
This paper presents several models addressing optimal portfolio choice, optimal portfolio liquidation, and optimal portfolio transition issues, in which the expected returns of risky assets are unknown. Our approach is based on a coupling between Bayesian learning and dynamic programming techniques that leads to partia…
Backtesting framework for CLMMs on Uniswap V3 reduces reward estimation error.
problem Estimating rewards for CLMMs in Uniswap V3 liquidity pools.
method Parametric model for liquidity distribution, historical data analysis.
result Error in reward estimation less than 1% for each pool.
Bid-ask spread is taken as an important measure of the financial market liquidity. In this article, we study the dynamics of the spread return and the spread volatility of four liquid stocks in the Chinese stock market, including the memory effect and the multifractal nature. By investigating the autocorrelation functi…
Study finds Indian mutual funds adjust cash holdings based on inflows, impacting stock purchases.
problem Active liquidity management by mutual funds in India.
method Examined cash holdings and stock purchases of Indian equity mutual funds.
result Funds with active liquidity choices outperform, highlighting the importance of this strategy.
Using recent advances in the econometrics literature, we disentangle from high frequency observations on the transaction prices of a large sample of NYSE stocks a fundamental component and a microstructure noise component. We then relate these statistical measurements of market microstructure noise to observable charac…
Interpool solves interoperability issues by minting, exchanging, and burning tokens within a single liquidity pool.
problem Lack of proper interoperability in blockchain use cases.
method Interpool operates as a standalone liquidity pool that mints, exchanges, and burns tokens, optimizing the order of transactions in the mempool.
result Interpool transforms front-running issues into a solution that ensures ultimate liquidity through a burning procedure, enabling trustless design.
This paper explores leverage staking with stETH, revealing high returns but also significant risks.
problem Leverage staking introduces risks through intensified selling pressure and cascading liquidations.
method Formal framework for leverage staking, stress tests under extreme conditions of stETH devaluation.
result Leverage staking amplifies risks, leading to intensified selling pressure and price declines.
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.
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.
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.
Study factors affecting liquidity on decentralized exchanges, introducing new metrics.
problem Understanding and predicting liquidity on decentralized exchanges (DEXs).
method Analyzes platform, blockchain, token pair, and liquidity pool factors; introduces new metrics.
result Identifies how various factors affect liquidity through concentration and total value locked.
Study shows how macroeconomic news affects intraday price and order flow dynamics.
problem Understanding how macroeconomic news impacts intraday price and order flow dynamics.
method Structural VAR model identified through heteroskedasticity, estimated at one-second frequency for each 15-minute interval.
result Macroeconomic news announcements reshape price-flow dynamics, with significant impacts on price and flow impacts at the one-second horizon.
Study examines new financial metrics and their implications for trading and risk management.
problem Liquidity and price dynamics in financial markets.
method High-frequency trading data, ARMA(1,1)-GARCH(1,1) model, normal inverse Gaussian distribution, option pricing model, Rachev ratio.
result New financial metrics (TMOBBAS, GMP) have heavy-tailed distributions and significant deviations from normality.
The distribution of returns in financial time series exhibits heavy tails. In empirical studies, it has been found that gaps between the orders in the order book lead to large price shifts and thereby to these heavy tails. We set up an agent based model to study this issue and, in particular, how the gaps in the order …
New formula identifies and quantifies costs for automated market makers.
problem Adverse selection costs faced by liquidity providers in automated market makers.
method Derives a Black-Scholes-like formula for AMMs and identifies loss-versus-rebalancing cost.
result Closed-form expressions for LVR applicable to all automated market makers.
When trading incurs proportional costs, leverage can scale an asset's return only up to a maximum multiple, which is sensitive to its volatility and liquidity. In a model with one safe and one risky asset, with constant investment opportunities and proportional costs, we find strategies that maximize long term returns …
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.
Study news networks to predict stock returns.
problem Predicting cross-sectional stock returns using news networks.
method Constructed time-varying directed networks of S&P500 stocks from 1 million news articles, identified stock tickers using an algorithm, and tested for comovement and reversal effects.
result News network attention proxy, network degree, predicts monthly stock returns robustly.
The total duration of drawdowns is shown to provide a moment-free, unbiased, efficient and robust estimator of Sharpe ratios both for Gaussian and heavy-tailed price returns. We then use this quantity to infer an analytic expression of the bias of moment-based Sharpe ratio estimators as a function of the return distrib…
Study finds it hard to establish common factor pricing in corporate bonds.
problem Difficulty in establishing common factor pricing in corporate bonds.
method Portfolio- and bond-level analyses using multifactor models.
result Common factor pricing in corporate bonds is not significantly explanatory.
Study optimizes Bitcoin futures hedging to reduce liquidation risk.
problem Optimizing hedging strategies to minimize liquidation risk in Bitcoin futures.
method Derived a semi-closed form optimal hedging strategy considering spot and futures extreme returns, loss aversion, leverage, and collateral management.
result Optimal strategy reduces both hedged portfolio variance and liquidation probability.
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.
It is customary that when security prices fully reflect all available information, the markets for those securities are said to be efficient. And if markets are inefficient, investors can use available information ignored by the market to earn abnormally high returns on their investments. In this context this paper tri…
Study on Kyle's model with stochastic liquidity impacts asset volatility.
problem Impact of stochastic volatility of noise trading on asset volatility.
method Construct equilibrium for continuous-time Kyle's model with stochastic liquidity.
result In equilibrium, Kyle's Lambda and its inverse are submartingales.
We present a large-scale study of commonality in liquidity and resilience across assets in an ultra high-frequency (millisecond-timestamped) Limit Order Book (LOB) dataset from a pan-European electronic equity trading facility. We first show that extant work in quantifying liquidity commonality through the degree of ex…
Motivated by the literature on investment flows and optimal trading, we examine intraday predictability in the cross-section of stock returns. We find a striking pattern of return continuation at half-hour intervals that are exact multiples of a trading day, and this effect lasts for at least 40 trading days. Volume, o…