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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.

168,738 papers · 148 categories

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25507499 · May 202619922001200920172026
48 results for square-root law

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.

We apply an asymmetric version of Kirman's herding model to volatile financial markets. In the relation between returns and agent concentration we use the square root law proposed by Zhang. This can be derived by extending the idea of a critical mean field theory suggested by Plerou et al. We show that this model is eq…

2005-08-12abs ↗pdf ↗

Many independent studies on stocks and futures contracts have established that market impact is proportional to the square-root of the executed volume. Is market impact quantitatively similar for option markets as well? In order to answer this question, we have analyzed the impact of a large proprietary data set of opt…

2016-02-09abs ↗pdf ↗

This paper explains how predictable order flow can lead to Brownian motion in financial prices.

problem Why financial prices exhibit Brownian motion despite predictable order flow.
method Generalized Lillo-Mike-Farmer model to nonlinear price-impact dynamics, mapping to Lévy-walk model.
result Price dynamics remain diffusive under the square-root law, even with persistent order flow.

We confirm the square-root law of market impact on Apple Inc. using a large dataset.

problem Testing the square-root law of market impact on a single U.S. large-cap equity.
method Using a full market-by-order feed, we reconstruct metaorders and calibrate impact using the square-root formula.
result The square-root law is confirmed with a prefactor of 0.34, consistent with worldwide data.

The Volterra square-root process shows non-uniqueness of limiting distributions and regularity of its law.

problem Non-uniqueness of limiting distributions in the Volterra square-root process.
method Establishing existence of limiting distributions using integrability of the Volterra convolution kernel and exponential-affine transformation.
result The limiting distributions of the Volterra square-root process depend on the initial state and belong to weighted Besov spaces.

The notion of market impact is subtle and sometimes misinterpreted. Here we argue that impact should not be misconstrued as volatility. In particular, the so-called ``square-root impact law'', which states that impact grows as the square-root of traded volume, has nothing to do with price diffusion, i.e. that typical p…

2019-05-11abs ↗pdf ↗

Study confirms the square-root law in price impact across Tokyo stocks.

problem The debate on the strict universality of the square-root law in price impact.
method Comprehensive survey of all trading accounts on the Tokyo Stock Exchange over 8 years.
result The exponent δ is equal to 1/2 for all stocks within statistical errors.

Model identifies order splitting and liquidity replenishment as necessary for the square-root law of market impact.

problem Quantifying the square-root law of market impact and identifying its underlying mechanisms.
method Minimal limit-order-book model with heterogeneous interacting agents calibrated against real data. Counterfactual ablation to isolate mechanisms.
result Order splitting and liquidity replenishment are necessary for the square-root law of market impact.

The study confirms that market volatility can be explained by correlated metaorders impacting prices in a square-root fashion.

problem Explaining market volatility using metaorders and their impact.
method Generated synthetic market data and analyzed the correlation between order flow and returns.
result The square-root law of market impact is confirmed and can be measured from anonymized trade data.

The paper uncovers two key laws of market impact influenced by volume and participation rate.

problem Understanding the roles of volume and participation rate in market price response.
method Extending the no arbitrage approach to include sophisticated market participants, deriving price dynamics from order flow dynamics.
result Recovery of two square root laws governing market impact.

Unified theory explains market impact using a simplified supply-demand parameter.

problem Understanding the market impact of metaorders and excess volatility.
method Coarse-grained approach with a single parameter ρ to model supply-demand equilibrium and market impact.
result Establishes a connection between excess volatility and order-driven markets through the square-root law.

In a recent Nature paper, Gabaix et al. \cite{Gabaix03} presented a theory to explain the power law tail of price fluctuations. The main points of their theory are that volume fluctuations, which have a power law tail with exponent roughly -1.5, are modulated by the average market impact function, which describes the r…

2003-09-17abs ↗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 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.

A simple trading model based on pair pattern strategy space with holding periods is proposed. Power-law behaviors are observed for the return variance σ2σ^2, the price impact HH and the predictability KK for both models with linear and square root impact functions. The sum of the traders' wealth displays a positive v…

2008-01-23abs ↗pdf ↗

Volterra square-root process boundary behavior and martingale measures

problem Boundary behavior of the Volterra square-root process
method Comparison principles for Volterra integral equations and generalized Riemann-Liouville fractional equations
result Finiteness of negative pp-moments and atom at the boundary for rough kernels

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 ↗

In this paper, we assume that the permanent market impact of metaorders is linear and that the price is a martingale. Those two hypotheses enable us to derive the evolution of the price from the dynamics of the flow of market orders. For example, if the market order flow is assumed to follow a nearly unstable Hawkes pr…

2014-02-06abs ↗pdf ↗

Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Several models have been proposed for predicting technological improvement, but how well do these models perform? An early hypothesis made by Theodore Wright in 1936 is that cost decreases as a power law of cumul…

2012-07-05abs ↗pdf ↗

The paper examines the short-time implied volatility of additive processes and finds key parameters.

problem Characterizing the short-time implied volatility of equity markets.
method Examined pure jump exponential additive processes with power-law scaling parameters.
result The implied volatility is consistent with equity market characteristics if and only if β=1 and δ=-1/2.

We respond to the issues discussed by Farmer and Lillo (FL) related to our proposed approach to understanding the origin of power-law distributions in stock price fluctuations. First, we extend our previous analysis to 1000 US stocks and perform a new estimation of market impact that accounts for splitting of large ord…

2004-03-02abs ↗pdf ↗

Modeling stock returns and volatility using a bivariate gamma generalized Laplace law.

problem Analyzing stock returns and volatility using a new statistical model.
method Maximum likelihood estimation for a bivariate generalized Laplace distribution, simplifying to linear regression.
result Explicit estimators derived with nonstandard convergence rates for certain parameter configurations.

Unified model explains market dynamics, linking order flow, volatility, and impact.

problem Understanding the dynamics of order flow, market impact, and volatility in financial markets.
method Proposes a microstructural model using Hawkes processes to distinguish core orders and reaction flow, and analyzes their scaling limits.
result Estimates the persistence parameter H0H_0 and finds it consistent with market impact and volatility properties.

Study differential properties of matrix square roots in specific cases.

problem Understanding matrix square roots in semi-simple, symmetric, and orthogonal cases.
method Analysis of differential and metric structures of real square roots of matrices under specific conditions.
result Differential properties of matrix square roots in semi-simple, symmetric, and orthogonal cases.

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.

A new method simulates square-root processes efficiently.

problem Simulating square-root processes accurately and efficiently.
method Simulate the integrated square-root process instead of the square-root process itself.
result High precision with low number of time steps, and exact limiting Inverse Gaussian distributions.

We propose a minimal theory of non-linear price impact based on a linear (latent) order book approximation, inspired by diffusion-reaction models and general arguments. Our framework allows one to compute the average price trajectory in the presence of a meta-order, that consistently generalizes previously proposed pro…

2014-11-29abs ↗pdf ↗

This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of metaorders-large orders that are split into smaller pieces before being sent to the market on one of the main Asian markets. In line…

2019-02-13abs ↗pdf ↗

A new method solves large-scale sparse group square-root Lasso problems efficiently.

problem Large-scale linearly constrained sparse group square-root Lasso problems.
method Dual semismooth Newton based augmented Lagrangian method (ALM).
result The proposed method efficiently solves the problem with numerical experiments demonstrating its effectiveness.

We revisit the "epsilon-intelligence" model of Toth et al.(2011), that was proposed as a minimal framework to understand the square-root dependence of the impact of meta-orders on volume in financial markets. The basic idea is that most of the daily liquidity is "latent" and furthermore vanishes linearly around the cur…

2013-11-25abs ↗pdf ↗

Square-root natural-gradient improves variational inference convergence.

problem Challenges in establishing theoretical convergence guarantees for natural-gradient descent.
method Square-root parameterization for Gaussian covariance.
result Establishes novel convergence guarantees for natural-gradient Gaussian inference.

Polynomial networks converge to Gaussian processes at a rate of O(n^(-1/2)).

problem Understanding the convergence rate of polynomial networks to Gaussian processes.
method Examined one-hidden-layer neural networks with random weights, focusing on polynomial activations and their convergence rate in the 2-Wasserstein metric.
result The rate of convergence for polynomial networks to Gaussian processes is $O(n^{- rac{1}{2}})$.

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 ↗

This paper contains a phenomenological description of the whole U.S. forward rate curve (FRC), based on an data in the period 1990-1996. We find that the average FRC (measured from the spot rate) grows as the square-root of the maturity, with a prefactor which is comparable to the spot rate volatility. This suggests th…

1997-12-15abs ↗pdf ↗

Solves non-Abelian Rainich problem for SU(2) gauge fields.

problem Existence of local SU(2) Yang-Mills fields with prescribed stress-energy tensor.
method Canonically identifying tensors with Hermitian forms and defining internal square roots of stress-energy tensors.
result Existence of local SU(2) Yang-Mills field is equivalent to a single differential condition on internal square roots of stress-energy tensor.