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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.

168,695 papers · 148 categories

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48 results for transient values

Study non-rectangular robust MDPs for average-reward, finding optimal policies and transient values.

problem Non-rectangular robust Markov decision processes under average-reward criterion.
method Proves history-dependent policies are robust-optimal, introduces transient-value framework, constructs epoch-based policy.
result Existence and properties of robust optimal policies, transient value bounds.

Study solves utility maximization in a transient price impact market.

problem Utility maximization in a market with transient price impact.
method Developed a discrete-time model and removed market depth and resilience process restrictions.
result Solved the utility maximization problem without convexity of attainable portfolio values.

We study a multiplicative transient price impact model for an illiquid financial market, where trading causes price impact which is multiplicative in relation to the current price, transient over time with finite rate of resilience, and non-linear in the order size. We construct explicit solutions for the optimal contr…

2015-01-08abs ↗pdf ↗

We discuss an "extrinsic" property of knots in a 3-subspace of the 3-sphere S3S^3 to characterize how the subspace is embedded in S3S^3. Specifically, we show that every knot in a subspace of the 3-sphere is transient if and only if the exterior of the subspace is a disjoint union of handlebodies, i.e. regular neighbor…

2015-02-17abs ↗pdf ↗

Detects anomalies in astronomical time series data.

problem Identifying new and interesting transients in large astronomical surveys.
method Two novel methods: a probabilistic neural network and a Bayesian parametric model.
result Neural networks are less suitable for anomaly detection in time series data compared to parametric models.

New method decomposes Markov chain rewards into persistent and transient components.

problem Ambiguity in classical evaluation methods for Markov chains with reducible and periodic states.
method Minimal exact quotient by the real peripheral invariant subspace, decomposing rewards into persistent and transient components.
result Exact comparison with classical methods shows that the new decomposition reallocates the same information, making persistent modes explicit.

Study examines the training process of an unsupervised learning model for detecting gravitational-wave transient noise.

problem Transient noise in gravitational-wave detector data causes instability and signal overlap.
method Unsupervised deep learning with variational autoencoder and invariant information clustering applied to the Gravity Spy dataset.
result Training process of the unsupervised learning architecture is examined and reported.

We present RAPID (Real-time Automated Photometric IDentification), a novel time-series classification tool capable of automatically identifying transients from within a day of the initial alert, to the full lifetime of a light curve. Using a deep recurrent neural network with Gated Recurrent Units (GRUs), we present th…

2019-03-29abs ↗pdf ↗

Novel method uses information theory to measure causal influences during transient neural events.

problem Characterizing network interactions during transient neural events.
method Structural Causal Models, Information Theory, Transfer Entropy, Dynamic Causal Strength, Relative Dynamic Causal Strength.
result Introduced a novel measure, relative Dynamic Causal Strength, with theoretical and empirical support.

Unsupervised learning classifies transient noise in gravitational wave detectors.

problem Transient noise interferes with gravitational wave signals, causing instability.
method Combines variational autoencoder and invariant information clustering.
result Consistent classification with Gravity Spy project labels.

Game theory models how agents trade in a risky asset considering price impact and a common signal.

problem Modeling how financial agents liquidate assets in a risky market with price impact and a common signal.
method Formulated and solved a multi-player stochastic differential game and mean field game.
result Equilibrium strategies reveal how agents adjust the predictive trading signal to price impact.

Optimal trading strategy adapts to signals in markets with price impact.

problem Optimal liquidation in markets with linear price impact and predictive signals.
method Formulated as a stochastic control problem, solved using probabilistic and convex analytic techniques.
result Explicit solution for optimal trading strategy in terms of SDEs.

Over the last decade, both the neural network and kernel adaptive filter have successfully been used for nonlinear signal processing. However, they suffer from high computational cost caused by their complex/growing network structures. In this paper, we propose two random Euler filters for complex-valued nonlinear filt…

2018-01-02abs ↗pdf ↗

Study optimal execution in a transient price impact model with multiple traders.

problem Optimal execution among multiple traders with transient price impact.
method Analyzed NN-player optimal execution games in an Obizhaeva--Wang model with and without regularization. Derived equilibrium solutions and explained their behavior.
result Existence of equilibrium restored with a specific time-dependent cost on block trades, and equilibrium is tractable.

We consider a Nash equilibrium between two high-frequency traders in a simple market impact model with transient price impact and additional quadratic transaction costs. Extending a result by Schöneborn (2008), we prove existence and uniqueness of the Nash equilibrium and show that for small transaction costs the high-…

2013-05-17abs ↗pdf ↗

New algorithm improves understanding of decentralized SBO transient iteration complexity.

problem Limited understanding of how network topology, data heterogeneity, and nested structures affect SBO.
method D-SOBA framework with two variants: D-SOBA-SO and D-SOBA-FO, providing non-asymptotic convergence analysis and transient iteration complexity.
result First theoretical understanding of how network topology, data heterogeneity, and nested structures influence decentralized SBO.

SMC analysis reveals key transient effects in macroeconomic ABM.

problem Analysis of complex ABMs is challenging and often relies on ad hoc methods.
method Statistical model checking (SMC) implemented through MultiVeStA.
result Clear contrast across parameter families in macro-financial and structural sweeps.

Random matrix theory explains transient signal detectability in early-stopped gradient flow.

problem Transient signal detectability in early-stopped gradient flow.
method Random matrix theory applied to gradient flow in a linear teacher-student setting.
result Transient Baik-Ben Arous-Péché (BBP) transition in learning dynamics due to anisotropy and noise.

Improves inverse uncertainty quantification for time-dependent data using PCA and deep neural networks.

problem Efficiently quantify model input uncertainties from time-dependent experimental data.
method Functional PCA for dimensionality reduction, deep neural networks for surrogate modeling, Bayesian neural networks for uncertainty estimation.
result The proposed method reduces the computational cost and improves the agreement with experimental data.

A new kernel improves statistical surrogates for stochastic manifolds with diverse data.

problem Handling statistical surrogates for stochastic manifolds with heterogeneous data.
method A transient anisotropic kernel is introduced to improve statistical surrogates for stochastic manifolds with heterogeneous data.
result The transient anisotropic kernel provides a better representation of statistical dependencies in the learned probability measure.

Bayesian BIC for multi-trial data improves VAR model order selection.

problem Optimal VAR model order selection for multi-trial event-based data.
method Derive and apply Bayesian Information Criterion (BIC) for multi-trial ensemble data.
result Multi-trial BIC successfully recovers real model order and estimates small model order.

This study examines how market makers balance risk and impact in foreign exchange markets.

problem Balancing risk management with market impact in foreign exchange markets.
method An intermediate scenario approach considering both instantaneous and permanent market impact components.
result Transient market impact is more prevalent than previously thought, challenging traditional market impact models.

FAL improves formation resistivity prediction from cased boreholes with noise resistance.

problem Noise and high-frequency disaster in predicting formation resistivity from cased boreholes.
method Frequency-aware framework and temporal anti-noise block for LSTM.
result FAL achieves a 24.3% improvement in R2 over LSTM, reaching R2=0.91.

We study the problem of the optimal execution of a large trade in the presence of nonlinear transient impact. We propose an approach based on homotopy analysis, whereby a well behaved initial strategy is continuously deformed to lower the expected execution cost. We find that the optimal solution is front loaded for co…

2014-12-16abs ↗pdf ↗

Sharp pseudospectral bounds prevent transient amplification in coupled gradient descent.

problem Transient amplification in coupled gradient descent systems.
method Developed a sharp pseudospectral theory for block-triangular Jacobians, proving Kreiss constant bounds and matching minimax lower bounds.
result Obtained a finite-horizon iteration-complexity bound of O(K(J)2log(1/δ))O(K(J)^2 \log(1/δ)) for stochastic coupled descent.

Deep RL agents suffer from transient non-stationarity, which ITER mitigates.

problem Transient non-stationarity in deep RL agents affects generalization.
method Iterated Relearning (ITER) transfers knowledge between networks to reduce non-stationarity.
result ITER improves deep RL agents' performance on generalization benchmarks.

Optimal liquidation strategy with price impact and signal exploitation.

problem Maximizing revenue-risk in a market with transient and temporary price impact.
method Infinite dimensional stochastic control approach, backward stochastic differential equation, operator-valued Riccati equation.
result Explicit expression for the optimal trading strategy.

We study portfolio selection in a model with both temporary and transient price impact introduced by Garleanu and Pedersen (2016). In the large-liquidity limit where both frictions are small, we derive explicit formulas for the asymptotically optimal trading rate and the corresponding minimal leading-order performance …

2017-05-01abs ↗pdf ↗

TKRR improves KRR performance by aligning target functions with kernels.

problem Improving kernel ridge regression performance through target alignment.
method Focuses on truncated kernel ridge regression (TKRR) with an additional spectral truncation parameter.
result TKRR can achieve faster rates than full KRR, reaching parametric rates.

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 ↗