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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.

168,742 papers · 148 categories

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48 results for momentum construction

New method constructs axial vector fields and defines quasi-local spin-angular momentum.

problem Constructing axial vector fields on Riemannian two-spheres.
method Using centre-of-mass unit sphere reference systems and Lie-propagated unit sphere reference systems.
result Constructive definition of quasi-local spin-angular momentum and balance relations.

Generalizes momentum map to Courant algebroid for constrained mechanics.

problem Generalizing momentum map to new geometric structures.
method Generalized momentum section on Lie algebroid to Courant algebroid, constructed cohomological formulations.
result Identified momentum section in constrained Hamiltonian mechanics with Courant algebroid symmetry.

We provide a model for an open invariant neighborhood of any orbit in a symplectic manifold endowed with a canonical proper symmetry. Our results generalize the constructions of Marle and Guillemin and Sternberg for canonical symmetries that have an associated momentum map. In these papers the momentum map played a cru…

2001-10-08abs ↗pdf ↗

The paper extends a theorem about momentum maps to singular symplectic spaces.

problem Extending a theorem about momentum maps to singular symplectic spaces.
method Using integral affine stratification and equivariant locally trivial fibrations, the paper extends the linear variation theorem to singular values of the momentum map.
result Cohomology classes of symplectic forms on reduced spaces vary linearly within strata.

This paper examines momentum spillover across multiple asset classes using only pricing data.

problem Challenges in studying momentum spillover across diverse asset classes due to lack of common characteristics.
method Utilised a linear and interpretable graph learning model to reveal momentum spillover network.
result Network momentum strategy yields a Sharpe ratio of 1.5 and an annual return of 22%.

Study finds physical momentum portfolios in Indian stock market yield higher returns than benchmarks.

problem Determining abnormal returns for physical momentum portfolios in the Indian stock market.
method Constructed physical momentum portfolios for daily, weekly, monthly, and yearly timescales, evaluated historical returns and risk profiles.
result Daily time scale physical momentum portfolios showed the strongest reversal with a 16-fold profit.

DeepUnifiedMom uses deep learning to create better momentum portfolios.

problem Lack of unified momentum portfolios across different time frames.
method Multi-task learning with multi-gate mixture of experts.
result DeepUnifiedMom outperforms benchmark models in diverse asset classes.

Enhanced trend-following strategy using network momentum for commodity futures.

problem Improving systematic trend-following in commodity futures markets.
method Combines univariate and cross-sectional trend indicators, including network momentum.
result Statistically significant improvements in portfolio performance metrics.

L2GMOM learns financial networks and optimizes momentum strategies.

problem Expensive databases and financial expertise limit network construction accessibility.
method End-to-end machine learning framework (L2GMOM) that learns networks and optimizes trading signals.
result Significant improvement in portfolio profitability and risk control with Sharpe ratio of 1.74.

We show that it is natural to consider the energy-momentum tensor associated with a spinor field as the second fundamental form of an isommetric immersion. In particular we give a generalization of the warped product construction over a Riemannian manifold leading to this interpretation. Special sections of the spinor …

2003-02-18abs ↗pdf ↗

The article examines in some detail the convergence rate and mean-square-error performance of momentum stochastic gradient methods in the constant step-size and slow adaptation regime. The results establish that momentum methods are equivalent to the standard stochastic gradient method with a re-scaled (larger) step-si…

2016-03-14abs ↗pdf ↗

Deep neural network learns portfolio construction and volatility forecasting.

problem Diversified risk-adjusted time-series momentum portfolios need robust volatility estimation.
method Multi-Task Learning in a deep neural network architecture.
result Deep learning approach outperforms existing TSMOM strategies.

This paper analyzes two Lie group momentum optimization algorithms and their convergence rates.

problem Optimizing functions on Lie groups using momentum-based dynamics.
method Investigates Lie Heavy-Ball and Lie NAG-SC algorithms, quantifying their convergence rates under smoothness and convexity assumptions.
result Lie NAG-SC accelerates optimization over the momentumless case, while Lie Heavy-Ball does not.

In the past 20 years, momentum or trend following strategies have become an established part of the investor toolbox. We introduce a new way of analyzing momentum strategies by looking at the information ratio (IR, average return divided by standard deviation). We calculate the theoretical IR of a momentum strategy, an…

2014-02-13abs ↗pdf ↗

DanSmp predicts stock movement using a hybrid-relational MKG and dual attention networks.

problem Predicting stock price trends in volatile financial markets.
method Constructs a bi-typed MKG with hybrid-relations and uses DanSmp, a dual attention network, to learn momentum spillover signals.
result DanSmp improves stock prediction accuracy using the MKG.

The paper analyzes convergence in SGD with momentum and proposes a diagnostic test.

problem Detecting convergence in stochastic gradient descent with momentum.
method Analyzes the transient and stationary phases of SGD with momentum, constructs a statistical diagnostic test.
result The proposed diagnostic test effectively detects convergence in the stationary phase of SGD with momentum.

Study norm-squared of momentum map in infinite dimensions with applications to symplectic geometry.

problem Understanding the norm-squared of the momentum map in infinite-dimensional settings.
method Calculation of Hessian, decomposition of stabilizer, application to symplectic and complex structures.
result Positive semi-definiteness of Hessian along complexified orbit and new central extensions of symplectomorphism group.

We empirically test predictability on asset price by using stock selection rules based on maximum drawdown and its consecutive recovery. In various equity markets, monthly momentum- and weekly contrarian-style portfolios constructed from these alternative selection criteria are superior not only in forecasting directio…

2014-03-31abs ↗pdf ↗

Paper glues characteristic data to Kerr spacetime, proving spacelike gluing.

problem Solving characteristic gluing problem for Einstein vacuum equations.
method Detailed characteristic gluing of strongly asymptotically flat data to Kerr spacetime.
result Alternative proof of spacelike gluing construction for strongly asymptotically flat spacelike initial data.

There exist three main approaches to reduction associated to canonical Lie group actions on a symplectic manifold, namely, foliation reduction, introduced by Cartan, Marsden-Weinstein reduction, and optimal reduction, introduced by the authors. When the action is free, proper, and admits a momentum map these three appr…

2005-01-07abs ↗pdf ↗

We generalize various symplectic reduction techniques to the context of the optimal momentum map. Our approach allows the construction of symplectic point and orbit reduced spaces purely within the Poisson category under hypotheses that do not necessarily imply the existence of a momentum map. We construct an orbit red…

2002-06-28abs ↗pdf ↗

The study finds that factor momentum is significant only at short lags compared to stock momentum.

problem Investigating the relationship between factor momentum and stock momentum.
method Replicated earlier findings and conducted a spanning test controlling for stock momentum and factor exposure.
result Factor momentum is significant only at short lags after controlling for stock momentum and factor exposure.

Constructs initial data for multiple black holes with specified ADM parameters.

problem Forming multiple black holes with specific ADM parameters.
method Smooth, asymptotically flat vacuum initial data with prescribed ADM energy, momentum, and angular momentum.
result Maximal development of data results in spacetimes containing multiple black holes.

We test the price momentum effect in the Korean stock markets under the momentum universe shrinkage to subuniverses of the KOSPI 200. Performance of the momentum strategy is not homogeneous with respect to change of the momentum universe. It is found that some submarkets generate the higher momentum returns than other …

2012-11-28abs ↗pdf ↗

Introduces homotopy momentum sections on multisymplectic manifolds.

problem No specific problem stated; focuses on introducing a new concept.
method Introduces a new concept of homotopy momentum sections on multisymplectic manifolds.
result Shows that a gauged nonlinear sigma model with Wess-Zumino term has homotopy momentum section structure.

Mathematical framework for field theories on Finsler spacetimes.

problem Developing a consistent calculus for field theories on Finsler spacetimes.
method Constructing configuration bundles and applying coordinate-free calculus of variations.
result Averaged energy-momentum conservation law for Finsler field theories.

Customer momentum is a positive relationship between a firm's returns and past returns of its customers.

problem Understanding the relationship between a firm's returns and its customers' past returns.
method Examined customer momentum using a long-short equally-weighted decile portfolio and Fama-French factor models.
result Customer momentum generates significant monthly returns and is statistically significant.

Combines MALA and Adam for efficient uncertainty quantification in deep learning.

problem Uncertainty estimation in deep neural networks.
method Integrates Metropolis Adjusted Langevin Algorithm (MALA) with momentum-based optimization (Adam) for efficient sampling from posterior distributions.
result The algorithm approximates the Gibbs posterior in total variation distance and efficiently quantifies epistemic uncertainty.

The paper analyzes how hyperparameters affect SGD with momentum's convergence rate.

problem The role of hyperparameters in SGD with momentum's convergence rate.
method Theoretical analysis using a hyperparameters-dependent stochastic differential equation (hp-dependent SDE).
result The optimal linear rate of convergence depends on both the learning rate and the momentum coefficient.

Study of dHYM connections on ruled surfaces with variable background metrics.

problem Finding new dHYM connections on ruled surfaces with variable metrics.
method Using momentum construction and moment map partial differential equations, coupled to scalar curvature of the background.
result Provide many new examples of dHYM connections coupled to a variable background Kähler metric.

This paper presents generalized momentum mappings for covariant Hamiltonian field theories. The new momentum mappings arise from a generalization of symplectic geometry to LVYL_VY, the bundle of vertically adapted linear frames over the bundle of field configurations YY. Specifically, the generalized field momentum obs…

2001-11-21abs ↗pdf ↗

We give a detailed discussion about existence and uniqueness of Lu's momentum map. More precisely, we introduce the infinitesimal momentum map, and we study its properties. This allows us to describe the theory of reconstruction of the momentum map from the infinitesimal one. We provide the conditions for the uniquenes…

2012-08-07abs ↗pdf ↗