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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.

169,051 papers · 148 categories

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2.4%4.8%7.1%9.5% · May 199719922001200920182026
48 results for impact decay

Study shows slow decay of impact in equity markets after metaorders.

problem Understanding the decay of impact in equity markets after metaorders.
method Empirical study using a large dataset of metaorders executed by institutional investors.
result Impact decay follows a power-law function at short time scales and converges to a non-zero asymptotic value at long time scales.

In this paper, we use a database of around 400,000 metaorders issued by investors and electronically traded on European markets in 2010 in order to study market impact at different scales. At the intraday scale we confirm a square root temporary impact in the daily participation, and we shed light on a duration factor …

2014-11-30abs ↗pdf ↗

Estimates self- and cross-impact concavity and decay patterns in financial markets.

problem Understanding the impact of financial transactions on market dynamics.
method Nonparametric estimation of concave multi-asset propagator models using metaorders and order flow data.
result Concave self-impact with shifted power-law decay, significant gain from cross-impact, and improved predictive accuracy.

Using a proprietary dataset of meta-orders and prediction signals, and assuming a quasi-linear impact model, we deconvolve market impact from past correlated trades and a predictable return component to elicit the temporal dependence of the market impact of a single daily meta-order, over a ten day horizon in various e…

2014-07-12abs ↗pdf ↗

Sample variance decay is shown in deep ReLU networks, impacting training dynamics.

problem Sample variance decay in deep ReLU networks during training.
method Decomposed total variance into sample variance and network-averaged sum of sample mean and variance.
result Sample variance decays in later layers of deep ReLU networks, impacting training dynamics.

We suggest that the broad distribution of time scales in financial markets could be a crucial ingredient to reproduce realistic price dynamics in stylised Agent-Based Models. We propose a fractional reaction-diffusion model for the dynamics of latent liquidity in financial markets, where agents are very heterogeneous i…

2017-04-09abs ↗pdf ↗

Paper uses DDPG to learn optimal execution strategies in dynamic markets.

problem Learning non-Markovian optimal execution strategies in dynamic financial markets.
method Introduces a novel actor-critic algorithm based on DDPG for transient price impact modeling.
result Successfully approximates optimal execution strategy through numerical experiments.

This paper examines weight initialization for 1-Lipschitz networks to improve robustness against adversarial attacks.

problem Improving the robustness of deep neural networks against adversarial attacks.
method Examined weight parametrization of AOL and SLL networks, calculated weight variance bounds, and demonstrated weight decay.
result Weight initialization causes deep 1-Lipschitz networks to decay to zero, and weight variance does not affect output variance distribution.

We analyze a proprietary dataset of trades by a single asset manager, comparing their price impact with that of the trades of the rest of the market. In the context of a linear propagator model we find no significant difference between the two, suggesting that both the magnitude and time dependence of impact are univer…

2017-02-26abs ↗pdf ↗

We study the problem of what causes prices to change. We define the mechanical impact of a trading order as the change in future prices in the absence of any future changes in decision making, and its it informational impact as the remainder of the total impact once mechanical impact is removed. We introduce a method o…

2006-08-27abs ↗pdf ↗

We extend the "No-dynamic-arbitrage and market impact"-framework of Jim Gatheral [Quantitative Finance, 10(7): 749-759 (2010)] to the multi-dimensional case where trading in one asset has a cross-impact on the price of other assets. From the condition of absence of dynamical arbitrage we derive theoretical limits for t…

2016-12-22abs ↗pdf ↗

Study shows integrating OFI from multiple levels improves price impact explanation but not forecasting.

problem Explaining and forecasting price movements in equity markets using OFI.
method Systematic approach to combine OFIs from multiple levels into an integrated variable, testing multi-asset models with and without cross-impact terms.
result Lagged cross-asset OFIs improve future return forecasting but not contemporaneous price impact.

We present a thorough empirical analysis of market impact on the Bitcoin/USD exchange market using a complete dataset that allows us to reconstruct more than one million metaorders. We empirically confirm the "square-root law'' for market impact, which holds on four decades in spite of the quasi-absence of statistical …

2014-12-15abs ↗pdf ↗

Solves VWAP liquidation under transient market impact.

problem Optimal liquidation with VWAP benchmark in a transient market.
method Analyzes linear and transient market impact, considers risk-averse investors with CARA utility, finds explicit solutions in continuous and discrete time.
result Explicit solutions found, optimal VWAP includes both buy and sell trades even with convex decay kernel.

New framework explains market volatility and metaorder impact.

problem Reconciling contradictory observations in market microstructure.
method Introducing a new theoretical framework to describe metaorders with different signs, sizes, and durations.
result Price diffusion is ensured by long memory of cross-correlations between metaorders.

Study optimal liquidation strategies on Uniswap v2/v3 considering price impact.

problem Optimal liquidation of large positions on Uniswap v2/v3 under transient price impact.
method Dynamic programming and numerical approximation for Uniswap v3, closed-form solutions for v2.
result Obtained optimal strategies for both Uniswap v2 and v3, showing how liquidity profile influences them.

Our goal in this paper is to study the market impact in a market in which the order flow is autocorrelated. We build a model which explains qualitatively and quantitatively the empirical facts observed so far concerning market impact. We define different notions of market impact, and show how they lead to the different…

2012-12-19abs ↗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 ↗

We demonstrate that the lowest possible price change (tick-size) has a large impact on the structure of financial return distributions. It induces a microstructure as well as it can alter the tail behavior. On small return intervals, the tick-size can distort the calculation of correlations. This especially occurs on s…

2010-01-28abs ↗pdf ↗

Study proposes GRU-D networks for missing value handling in road surface friction prediction.

problem Missing values in road surface friction data affect prediction accuracy.
method Gated Recurrent Unit (GRU) network with decay mechanism.
result GRU-D networks outperform baseline models in road surface friction prediction.

Optimal portfolio choice with cross-impact propagators, solving complex equations.

problem Maximizing revenue-risk in a continuous-time portfolio choice problem with cross-impact.
method Formulated as a maximization problem, solved explicitly using operator resolvents and stochastic Fredholm equations.
result Sufficient conditions for the absence of price manipulation, providing financial insights.

Improved performance of factorized neural layers through spectral initialization and Frobenius decay.

problem Improving the performance of factorized neural layers in various deep learning contexts.
method Spectral initialization and Frobenius decay for initialization and regularization.
result Spectral initialization and Frobenius decay lead to improved performance across multiple deep learning settings.

Trading algorithms that execute large orders are susceptible to exploitation by order anticipation strategies. This paper studies the influence of order anticipation strategies in a multi-investor model of optimal execution under transient price impact. Existence and uniqueness of a Nash equilibrium is established unde…

2016-09-02abs ↗pdf ↗

In this paper we propose a copula contagion mixture model for correlated default times. The model includes the well known factor, copula, and contagion models as its special cases. The key advantage of such a model is that we can study the interaction of different models and their pricing impact. Specifically, we model…

2010-10-19abs ↗pdf ↗

This article provides a novel framework to evaluate limit order tactics that highlights expected fill price, adverse price selection cost, and opportunity cost. We formulate the problem of optimal execution of market orders with nonlinear market impact, power law decay kernel, and stochastic and deterministic liquidity…

2014-09-04abs ↗pdf ↗

Optimal trading strategy under market resistance and concave price impact model.

problem Optimal trading in a market with endogenous resistance and concave price impact.
method Modeling market resistance, deriving a stochastic Fredholm equation, proving existence and uniqueness, proposing an iterative scheme.
result Existence and uniqueness of optimal control under certain conditions, exponential convergence of iterative scheme.

The three-state agent-based 2D model of financial markets as proposed by Giulia Iori has been extended by introducing increasing trust in the correctly predicting agents, a more realistic consultation procedure as well as a formal validation mechanism. This paper shows that such a model correctly reproduces the three f…

2013-10-02abs ↗pdf ↗

We provide a microfoundation for linear price impact models in a stationary market.

problem Deriving linear price impact models in a stationary market with asymmetric information.
method Deriving linear price impact models as the equilibrium of an agent-based system.
result The model shows compatibility with universal price diffusion at small times and non-universal mean-reversion at larger times.

ICON-OCnet solves optimal execution problems with neural networks and few examples.

problem Optimal order execution in markets with unknown price impact.
method Transformer-based neural network architecture (ICON-OCnet) that learns price impact from few examples and applies it to optimal execution strategies.
result ICON-OCnet accurately infers price impact models and retrieves optimal execution strategies for various propagator kernels.

Two models predict similar high-frequency price dynamics but differ in low-frequency impact strength.

problem Understanding the relationship between market prices and fundamental information.
method Comparing a microfounded linear model with a data-driven model at high and low frequencies.
result Both models predict similar high-frequency price dynamics but differ in low-frequency impact strength.

Study finds price impact follows a 'double' square-root law, suggesting mechanical origin.

problem Understanding the origin of price impact in markets.
method Detailed dataset of Tokyo Stock Exchange orders, analyzing single and metaorders.
result Price impact follows a 'double' square-root law, indicating mechanical origin rather than information.

Study models market volatility with persistent and temporary impacts.

problem Microstructure of rough volatility models driven by Poisson measures.
method Existence and uniqueness of solutions for stochastic path-dependent Volterra equations.
result Volatility process converges to fractional Heston model with spikes.

Optimal trading is a recent field of research which was initiated by Almgren, Chriss, Bertsimas and Lo in the late 90's. Its main application is slicing large trading orders, in the interest of minimizing trading costs and potential perturbations of price dynamics due to liquidity shocks. The initial optimization frame…

2017-04-04abs ↗pdf ↗

Analyzes transaction costs for corporate bonds using a new analytical methodology.

problem Challenges in assessing the quality of corporate bond executions via Transaction Cost Analysis.
method Analyzes TRACE Enhanced dataset to estimate initiator, bid-ask spread, and mid-price dynamics; applies regularized regression models and transient impact models.
result Identifies price impact asymmetry between customer-buy and consumer-sell orders.