The paper analyzes trading strategies in markets with high frictions.
problem Characterizing optimal trading strategies in markets with superlinear frictions.
method Characterizes superhedging prices, absence of arbitrage, and utility maximizing strategies under general frictions.
result Utility maximizing strategies exist even in markets with arbitrage, due to limitations on trading intensity.
Study random walks on groups with superlinear divergent geodesics.
problem Existence of superlinear divergent geodesics in groups.
method Developed theory of superlinear divergence and applied Gouëzel's pivoting technique.
result Established a central limit theorem for random walks on groups with superlinear divergent geodesics.
New quasi-Newton method guarantees global superlinear convergence.
problem Global convergence and superlinear convergence of quasi-Newton methods.
method Hybrid proximal extragradient method with online learning for Hessian approximation.
result First globally convergent quasi-Newton method with explicit superlinear convergence rate.
Ancient solutions on manifolds show positivity and constancy.
problem Qualitative properties of ancient solutions on Riemannian manifolds.
method Analysis of superlinear heat equations.
result Ancient solutions exhibit positivity and constancy.
Paper improves a method for fast global and local convergence in optimization.
problem Slow global convergence in optimization methods with noisy Hessian estimates.
method Stochastic Newton Proximal Extragradient method using HPE framework.
result Faster global linear rate and superlinear convergence in fewer iterations.
New averaging technique speeds up Newton method convergence.
problem Superlinear convergence of stochastic Newton methods with noisy Hessians.
method Hessian averaging to reduce noise and maintain superlinear convergence.
result Hessian averaging achieves superlinear convergence with a non-asymptotic rate.
New method achieves superlinear convergence rate with limited memory.
problem Achieving superlinear convergence rate in quasi-Newton methods with limited memory.
method Limited-memory Greedy BFGS (LG-BFGS) method with displacement aggregation and basis vector selection.
result Explicit non-asymptotic superlinear convergence rate demonstrated.
Predict road friction levels using connected vehicle data and weather parameters.
problem Predict road friction levels for connected vehicles.
method Proposes a framework using supervised machine learning (logistic regression, SVM, neural networks) to classify road friction levels.
result Neural networks model performs best across different prediction horizons and conditions.
Paper proposes new Langevin samplers for sampling from log-concave distributions with superlinear gradient growth.
problem Sampling from log-concave distributions with superlinear gradient growth.
method Proposes two novel discretizations of kinetic Langevin SDEs, showing contractivity and log-Sobolev inequality.
result Establishes non-asymptotic bounds in 2-Wasserstein distance between sampled distributions and target measures.
Generative model creates frictional surfaces from friction laws.
problem Designing frictional interfaces with prescribed behavior is challenging.
method Uses Variational Autoencoders (VAEs) to infer surface topographies from friction laws.
result Efficiently generates candidate topographies without contact simulations.
Improved stability for matrix recovery from rank-one measurements.
problem Phase retrieval problem of recovering rank-one positive semidefinite matrices.
method Developed a smoothing Newton method based on Bures-Wasserstein gradient descent.
result Superlinear convergence with rigorous guarantees and stable implementation.
Unified asymptotics for investment in markets with transaction costs and search frictions.
problem Investment in markets with transaction costs and search frictions.
method Power-utility maximization problem with proportional transaction costs and Poisson-triggered trades, analyzed using a novel asymptotic framework.
result Explicit asymptotics for the no-trade region and value function derived.
Market trade-routes can support infectious-disease transmission, impacting biological populations and even disrupting causal trade. Epidemiological models increasingly account for reductions in infectious contact, such as risk-aversion behaviour in response to pathogen outbreaks. However, market dynamics clearly differ…
Model analyzes trading frictions in cap-and-trade markets, showing how they interact to affect market effectiveness.
problem Analyzing how trading frictions impact cap-and-trade market effectiveness.
method Developed a dynamic stochastic model with multiple trading frictions, characterized access choices in closed form, and quantified using EU ETS data.
result Trading frictions interact to amplify or dampen market responses, and their combined effect is non-additive.
Novel signature approach for pricing and hedging path-dependent options with market frictions.
problem Pricing and hedging path-dependent options with market frictions.
method Signature approach, mean-quadratic variation criterion, non-standard infinite-dimensional Riccati equations, time-augmented signature, non-Markovian stochastic control problem.
result Effective hedging strategies in frictional markets with low-truncated signature approximations.
No arbitrage found with market frictions for time-lagged asset returns.
problem Existence of time-lagged cross-correlations in financial returns.
method Introduced market frictions like minimal waiting time or transaction costs.
result No arbitrage possible with market frictions.
New algorithm samples from complex non-convex distributions.
problem Sampling from non-convex, non-smooth distributions with superlinear gradients.
method Subgradient Tamed Unadjusted Langevin Algorithm (SG-TULA)
result Non-asymptotic convergence bounds in Wasserstein-2 distance for SG-TULA.
Investment and insurance decisions are studied in a model with nonlinear portfolio frictions and background risk.
problem Investment and insurance decisions under a model with nonlinear portfolio frictions and background risk.
method Dynamic programming approach to find optimality conditions.
result Agent can choose to assume, partially assume, or purchase total insurance against adverse jumps in wealth.
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.
Study finds cryptoasset markets inefficient due to capital reallocation frictions.
problem Inefficiency in cryptoasset markets due to capital reallocation frictions.
method Examined investments with dominant and secondary risk factors, derived equilibrium restrictions, and tested empirically.
result Empirical results strongly reject necessary equilibrium restrictions, indicating market inefficiency.
Study pricing derivatives in nonlinear models with market frictions.
problem No-arbitrage pricing of derivatives in nonlinear market models with funding costs, credit risk, and trading frictions.
method Extend nonlinear pricing approach by incorporating funding costs, credit risk, and trading frictions.
result Developed a comprehensive framework for pricing derivatives in nonlinear market models.
We investigate the optimal strategy over a finite time horizon for a portfolio of stock and bond and a derivative in an multiplicative Markovian market model with transaction costs (friction). The optimization problem is solved by a Hamilton-Bellman-Jacobi equation, which by the verification theorem has well-behaved so…
A simple method to prevent forgetting in neural networks.
problem Catastrophic forgetting in neural networks.
method Weight friction, inspired by neurology and physics, modifies the gradient descent update rule.
result Weight friction enables continual learning with comparable performance and efficiency.
Repo dealers' market power affects bond prices by up to 2 percentage points.
problem Market power of repo dealers impacts bond prices and liquidity.
method Proprietary data on repo and reverse-repo trades analyzed.
result Market power of repo dealers accounts for 0.5-1.3 percentage points of bond yield deviation.
New methods optimize functions faster with less gradient accuracy needed.
problem Optimizing complex functions with limited gradient accuracy.
method Hessian averaging and adaptive gradient sampling methods.
result Improved convergence rates for various function types.
The paper optimizes forecasting for risk-adjusted decisions under trading frictions.
problem Optimizing forecasting accuracy for investment decisions in the presence of transaction costs.
method Develops a utility-weighted calibration criterion to minimize decision loss net of costs.
result Utility-weighted calibration reduces decision loss by over 30% and improves Sharpe ratio.
The paper models insurance market dynamics under uncertainty and financial frictions.
problem Modeling insurer behavior under uncertainty and financial frictions.
method Dynamic equilibrium model of insurance market with competitive insurers maximizing shareholder value.
result Investment can lead to lower insurance prices and negative loadings under certain conditions.
Study on friction forces for nonholonomic systems using affine connections.
problem Realizing nonholonomic constraints with strong friction forces.
method Affine connection approach, covariant derivatives, recursive procedure.
result Approximations of slip velocities and dynamics up to second order.
Bitcoin's monetary velocity is constrained by network friction, leading to significant utility contraction during shocks.
problem Bitcoin's monetary velocity is limited by network congestion, causing significant utility loss during economic shocks.
method Empirical analysis using Transaction Cost Index and threshold regression to identify structural breaks and velocity contraction.
result Network friction significantly reduces Bitcoin's monetary velocity, leading to a net utility contraction of -9.39% during shocks.
Study shows GPT's earnings forecasts are human-like but not always accurate.
problem Information friction in AI-generated financial analysis.
method Examined GPT's earnings forecasts following corporate earnings releases and proposed a diagnostic framework.
result GPT's narrative attention is consistent and human-like but not always associated with higher forecast accuracy.
Memory-constrained algorithms need superlinear memory for efficient convex optimization.
problem Efficiently minimizing convex functions with limited memory.
method Analyzing first-order algorithms with superlinear memory constraints.
result Superlinear memory is necessary for optimal performance in convex optimization.
New algorithm TUSLA improves learning of non-convex neural networks.
problem Optimizing non-convex loss functions in neural networks with superlinear gradient growth.
method Tamed Unadjusted Stochastic Langevin Algorithm (TUSLA) based on SGLD with taming technology.
result Finite-time guarantees for TUSLA to find approximate minimizers of empirical and population risks.
SPAC data shows premium investors get better terms, non-premium get quid pro quo deals.
problem Agency problems and informational frictions in securities issuance.
method Analysis of SPAC data to identify premium and non-premium investors.
result Non-premium investors engage in quid pro quo relationships with issuers and intermediaries.
We study superreplication of European contingent claims in discrete time in a large trader model with market indifference prices recently proposed by Bank and Kramkov. We introduce a suitable notion of efficient friction in this framework, adopting a terminology introduced by Kabanov, Rasonyi, and Stricker in the conte…
We study long-term growth-optimal strategies on a simple market with linear proportional transaction costs. We show that several problems of this sort can be solved in closed form, and explicit the non-analytic dependance of optimal strategies and expected frictional losses of the friction parameter. We present one der…
New algorithms improve sampling from complex distributions.
problem Sampling from complex probability distributions efficiently.
method Regime-switching Langevin dynamics and Monte Carlo algorithms.
result Convergence guarantees and iteration complexities provided.
Investment strategy optimized in markets with transaction costs and search delays.
problem Maximizing wealth in an illiquid market with transaction costs and search frictions.
method Characterized no-trade region and provided asymptotic expansions of value function for small transaction costs.
result The effects of transaction costs are more pronounced in illiquid markets.
Model explains capital allocation and wealth distribution dynamics in a frictional economy.
problem Understanding capital allocation and wealth distribution dynamics in a frictional economy.
method Mean-field game approach to model interactions between expert and household groups.
result Experts accumulate capital during booms and quickly reverse behavior in busts, even without macro-shocks.
Robust HVA adjusts deep hedging policies for market frictions and transaction costs.
problem Ensuring deep hedging policies are financially feasible under market frictions and transaction costs.
method Applying a robust hedging valuation adjustment (HVA) post-training to evaluate and adjust policies for funding and margin add-ons.
result A single HVA computation provides a consistent reserve for funding and margin, improving financial feasibility of deep hedging policies.
New friction model for geometric locomotion systems.
problem Modeling asymmetric friction in locomotion systems.
method Introducing asymmetric friction into geometric locomotion models using Finsler metrics.
result Generalized motility map for systems with asymmetric friction.
Emulator speeds up landslide run-out modeling sensitivity analysis.
problem Computational challenges in assessing landslide run-out model sensitivity.
method Gaussian process emulation integrated into r.avaflow.
result Strong interactions detected between friction coefficients and release volume.
New method improves smoothness of minimizing currents near singular points.
problem Improving smoothness of minimizing currents near singular points.
method New method to estimate the full singular set of the foliation by minimizers and proof of superlinear decay of closeness.
result Generic smoothness of minimizers improved to n−9−εn for n≥11. Novel approach to high frequency trading microstructure.
problem Understanding high frequency trading and its impact on market dynamics.
method Introducing a new concept of informed traders and rigorous limit order book analysis.
result Market frictions misrepresent wealth by 50% and alter trading strategies.
Deep Hedging removes drift for cleaner option pricing.
problem Finding equivalent martingale measures in markets with frictions.
method Learning minimal near-martingale measures using deep learning.
result Clean hedges for exotic payoffs robust to estimation error.
Extends sublinear expectations to random sets, identifying extremal and constructing methods.
problem Extending sublinear expectations to random sets.
method Identifying extremal expectations and presenting general construction methods.
result Identification of extremal sublinear and superlinear expectations.
The paper derives the QGS equations using stochastic central extensions.
problem Deriving the viscous quasi-geostrophic equations on the torus.
method Central extensions of Lie groups and Lie algebras, stochastic Lagrangian formulation, and Euler-Poincaré reduction.
result Stochastic perturbations to the central extension lead to solutions of the QGS equations.
Model explains asset price dynamics, defaults, and market crashes via non-linear dynamics.
problem Understanding asset price dynamics, defaults, and market crashes in financial markets.
method Proposes a non-equilibrium model incorporating market frictions and feedback mechanisms.
result The QED model produces non-linear dynamics, broken scale invariance, and corporate defaults.
The paper proves superhedging duality with transaction costs and frictions.
problem Superhedging under proportional transaction costs and model uncertainty.
method Quasi-sure setup with solvency cones, removing restrictive assumptions.
result Duality proved under more natural conditions of No Strict Arbitrage.