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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.

169,181 papers · 148 categories

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63126189252 · Jun 202019922001200920182026
48 results for one-sided quadratic cost

Quantization-aware phase retrieval algorithm improves signal reconstruction accuracy.

problem Reconstructing signals from quantized phase measurements.
method Developed a rank-1 projection algorithm with consistency criterion using one-sided quadratic cost.
result The algorithm achieves higher reconstruction accuracy and is closer to the Cramér-Rao lower bound.

New methods improve online matrix optimization with reduced computational cost.

problem Online matrix optimization with operator norm constraints.
method Gradient-based prediction scheme with smoothed potentials for nuclear norm.
result Adaptive matrix optimizers match Shampoo's regret up to a constant factor.

Research shows quadratic growth in derivative maxima for certain interval diffeos with parabolic fixed points.

problem Analyzing the growth of derivative maxima for C2C^2 interval diffeomorphisms with parabolic fixed points.
method Examining C2C^2 diffeomorphisms with only parabolic fixed points, focusing on tangency and repelling behavior.
result Maximal growth of derivative maxima is exactly quadratic for diffeomorphisms with a non-quadratic tangency to identity at a repelling fixed point.

The study examines portfolio optimization with quadratic transaction costs, complicating the optimization process.

problem Portfolio optimization with quadratic transaction costs is more challenging than with linear costs.
method Introduced numerical algorithms to solve the optimization problem with quadratic transaction costs.
result Quadratic transaction costs significantly impact the expected returns of optimized portfolios.

Optimal liquidation strategy for a risk-averse investor in a one-sided limit order book driven by a Levy process.

problem Balancing market risk and execution cost for a large share liquidation.
method Modeling the price process as a Levy process and solving a singular two-dimensional optimisation problem.
result Explicit expression for the optimal intervention boundary.

The paper solves a utility-based hedging problem with quadratic costs.

problem Optimal trading strategy for hedging European contingent claims with quadratic transaction costs.
method Duality theory applied to exponential utility maximization problem.
result Explicit computation of optimal trading strategy for quadratic payoffs.

We define a notion of Hempel distance for one-sided Heegaard splittings and show that the existence of alternate surfaces restricts distance for one-sided splittings in a manner similar to Hartshorn's and Scharlemann-Tomova's results for two-sided splittings. We also show that every geometrically compressible one-sided…

2011-12-02abs ↗pdf ↗

Study how transaction costs impact stock returns and holdings in equilibrium.

problem Impact of quadratic transaction costs on equilibrium stock returns and holdings.
method Developed a continuous-time risk-sharing model with FBSDEs to characterize equilibrium stock holdings and trading rates.
result Equilibrium stock holdings and trading rates are uniquely determined by FBSDEs, and equilibrium return by a system of coupled FBSDEs.

We reconsider the problem of optimal trading in the presence of linear and quadratic costs, for arbitrary linear costs but in the limit where quadratic costs are small. Using matched asymptotic expansion techniques, we find that the trading speed vanishes inside a band that is narrower than in the absence of quadratic …

2015-11-23abs ↗pdf ↗

When a Dehn filled link manifold contains a geometrically incompressible one-sided surface, it is shown there is a unique boundary incompressible position that the surface can take in the link space. The proof uses a version of the sweep-out technique from two-sided Heegaard splitting theory. When applied to one-sided …

2008-07-30abs ↗pdf ↗

In this paper we prove an extrinsic one-sided curvature estimate for disks embedded in R3\mathbb{R}^3 with constant mean curvature which is independent of the value of the constant mean curvature. We apply this extrinsic one-sided curvature estimate in [24] to prove to prove a weak chord arc type result for these disks…

2014-08-22abs ↗pdf ↗

The paper develops an expansion for optimizing portfolios with small quadratic transaction costs.

problem Optimizing portfolios with small, instantaneous, quadratic transaction costs.
method Develops an asymptotic expansion for the Hamilton-Jacobi-Bellman equation.
result Derives explicit formulae for the first two terms of the expansion.

Using basic properties of one-sided Heegaard splittings, a direct proof that geometrically compressible one-sided splittings of RP^3 are stabilised is given. The argument is modelled on that used by Waldhausen to show that two-sided splittings of S^3 are standard.

2005-09-01abs ↗pdf ↗

Proposes a new framework for invariant quadratic P&L predictions in option books.

problem Inconsistent second-order P&L predictions across different factor parameterizations.
method Local, model-agnostic framework using covariant Hessian defined by an affine connection.
result Coordinate-invariant quadratic P&L predictions that match desk targets.

The paper extends a variance gamma model to quadratic functions, reducing arbitrage and computational costs.

problem Creating an arbitrage-free interpolation for option pricing models.
method Generalizing the local variance gamma model to a piecewise quadratic local variance function.
result The quadratic model results in an arbitrage-free interpolation of class C3, reducing knots and computational cost.

OMGD algorithm optimizes online convex optimization with switching costs and delayed gradients.

problem Optimizing online convex optimization with switching costs and delayed gradients.
method Proposed an online multiple gradient descent (OMGD) algorithm for quadratic and linear switching costs.
result OMGD achieves optimal dynamic regret in the limited information setting.

Optimal contracts are found for agents with quadratic effort costs.

problem Finding optimal contracts in principal-agent problems with quadratic effort costs.
method Modeling the problem using Hamilton-Jacobi-Bellman (HJB) equations and proving the existence of classical solutions.
result Existence of optimal contracts for agents with quadratic effort costs is proven.

Study cost-driven state representation learning for control from partial observations.

problem Learning state representation for control from partial and high-dimensional observations.
method Cost-driven state representation learning via predicting cumulative costs.
result Established finite-sample guarantees for near-optimal representation and controller.

We study minimal graphic functions on complete Riemannian manifolds $\Si$ with non-negative Ricci curvature, Euclidean volume growth and quadratic curvature decay. We derive global bounds for the gradients for minimal graphic functions of linear growth only on one side. Then we can obtain a Liouville type theorem with …

2013-10-08abs ↗pdf ↗

Model liquidity premia using a risk-sharing economy with quadratic costs.

problem Understanding the cross-section of liquidity premia earned by assets with different trading costs.
method Developed a risk-sharing economy model with quadratic transaction costs, leading to matrix-valued Riccati equations for equilibrium.
result Calibrated model to time series data, revealing liquidity premia across assets with varying trading costs.

Adam-type optimizers show one-sided convergence in GAN training, not reaching critical points.

problem Theoretical understanding of Adam-type optimizers in non-convex non-concave min-max optimization.
method Empirical and theoretical analysis of Adam-type algorithms' convergence in GAN training.
result Adam-type algorithms converge to one-sided first order stationary points under the one-sided MVI condition.

RL and DTSOC for final quadratic hedging performance studied.

problem Optimal hedging of European call options with and without transaction costs.
method Reinforcement Learning and Deep Trajectory-based Stochastic Optimal Control.
result RL and DTSOC perform similarly to variance-optimal hedging in various market models.

Study analyzes market equilibrium returns with price impact and transaction costs.

problem Modeling equilibrium returns in markets with strategic order placement and transaction costs.
method Analyzes frictionless and transaction-cost markets, characterizes Nash equilibrium via FBSDEs.
result Equilibrium returns are affected by transaction costs, especially with noise traders.

Various structural properties are developed for non-orientable surfaces in link spaces. The Möbius band tree is described to represent genus growth of one-sided surfaces in solid tori. The structure of the Tree allows various insights into the change of genus under boundary slope, which are not possible using the exist…

2011-01-13abs ↗pdf ↗

Non-bilinear observations make optimal control harder, showing non-convex costs and non-affine optimal controllers.

problem Optimal control from bilinear observations in linear systems is challenging.
method Analytical and numerical methods to study the non-convex cost-to-go and non-affine optimal controllers.
result The Separation Principle does not hold for bilinear observations, leading to non-convex costs and non-affine optimal controllers.

Study on regularity of optimal transport maps on convex domains with quadratic cost.

problem Regularity of optimal transport maps between convex domains with quadratic cost.
method Analysis of CαC^α-densities and C1,αC^{1, α} boundary conditions, monotonicity formula for optimal transport maps.
result Proves C1,1εC^{1, 1-\varepsilon}-regularity for nondegenerate CαC^α-densities and C2,αC^{2, α}-regularity for C1,αC^{1, α} boundary.

A new method for selective classification trades off accuracy for coverage.

problem Selective classification allows a classifier to abstain from predicting some instances.
method Optimizes a collection of class-wise decoupled one-sided empirical risks.
result The method achieves near-optimal coverage in high target accuracy regimes.

Study risk-sharing equilibria with general transaction costs, proving mean-reversion of returns.

problem Analyzing risk-sharing equilibria with general convex transaction costs.
method Infinite-horizon model with linear state dynamics, solved numerically using deep learning.
result Equilibrium returns mean-revert around frictionless counterparts, with different dynamics for quadratic and proportional costs.

Study one-sided matrix completion with two observations per row.

problem Recover right singular vectors of a low-rank matrix XX with few observations.
method Impute missing values of XTXX^TX and analyze recovery guarantees.
result Provable recovery of XTXX^TX with Ω(r2dlogd)Ω(r^2 d \log d) rows, outperforming standard methods.

Study learns state representations from observations for control, proving guarantees.

problem Learning state representations from high-dimensional observations for control.
method Cost-driven approach, learning latent state model to predict costs.
result Proves finite-sample guarantees for near-optimal state representation and controller.

Investigates VaR behavior for sums of one-sided random variables, showing impossibilities and conditions for super-additivity.

problem Investigates the behavior of Value-at-Risk (VaR) for sums of one-sided random variables.
method Analyzes the extremal aggregation behavior of VaR, introduces structural conditions for super-additivity.
result Characterizes when VaR is fully super-additive and provides unified framework for various dependence structures.