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.
Better neural arithmetic logic units improve cell counting model generalization.
The theory of geometric zeta functions for locally symmetric spaces as initialized by Selberg and continued by numerous mathematicians is generalized to the case of higher rank spaces. We show analytic continuation, describe the divisor in terms of tangential cohomology and in terms of group cohomology which generalize…
Probabilistic numerics expands numerical tasks with black box methods.
In this paper, we propose a phase shift deep neural network (PhaseDNN) which provides a wideband convergence in approximating a high dimensional function during its training of the network. The PhaseDNN utilizes the fact that many DNN achieves convergence in the low frequency range first, thus, a series of moderately-s…
In this paper, we propose a novel investment strategy for portfolio optimization problems. The proposed strategy maximizes the expected portfolio value bounded within a targeted range, composed of a conservative lower target representing a need for capital protection and a desired upper target representing an investmen…
A new way to describe correlation matrices makes modeling easier.
This work learns models for population dynamics using variational methods and higher-order quadrature.
Median-of-means sampling outperforms mean-of-means for large sample sizes in numerical integration.
Comprehending complex systems by simplifying and highlighting important dynamical patterns requires modeling and mapping higher-order network flows. However, complex systems come in many forms and demand a range of representations, including memory and multilayer networks, which in turn call for versatile community-det…
Extends Perelman's theorem to positive intermediate curvature conditions.
The paper introduces MRVaR and MRCov for elliptical and log-elliptical distributions.
New loss function improves accuracy of MRI parameter estimation.
This paper is the continuation of Part I, expanding previous results of math.DG/9803051. This paper uses techniques in noncommutative geometry as developed by Alain Connes in order to study the twisted higher index theory of elliptic operators on orbifold covering spaces of compact good orbifolds, which are invariant u…
Study evaluates neural networks based on random graph structures and finds key performance indicators.
Study finds the order of Dehn twists in various groups.
Study finds phase transition in context-sensitive language model with short-range interactions.
We report an empirical study of Tehran Price Index (TEPIX). To analyze our data we use various methods like as, rescaled range analysis (), modified rescaled range analysis (Lo's method), Detrended Fluctuation Analysis (DFA) and generalized Hurst exponents analysis. Based on numerical results, the scaling range of…
The paper examines how insurers manage risks and liquidity in a dynamic market.
Closed-form relations and approximations for SE(3) derivatives for robust numerical simulations.
Bayesian method reconstructs hidden higher-order interactions from network data.
A new sampler tackles critical phenomena by leveraging scale invariance.
A contour integral method recently proposed by Weideman [IMA J. Numer. Anal., to appear] for integrating semi-discrete advection-diffusion PDEs, is extended for application to some of the important equations of mathematical finance. Using estimates for the numerical range of the spatial operator, optimal contour parame…
Introduce Collapsed Effective Operators for higher-order structures.
The paper proposes a method to compute higher infinitesimals in numerical and symbolic analysis.
The convolution method for the numerical solution of forward-backward stochastic differential equations (FBSDEs), introduced in [21], uses a uniform space grid. In this paper we utilize a tree-like spatial discretization that approximates the BSDE on the tree, so that no spatial interpolation procedure is necessary. In…
Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only o…
New COS method formula improves option pricing accuracy.
Homology of abelian differentials stabilizes with more zeros.
We study the optimal investment-consumption problem for a member of defined contribution plan during the decumulation phase. For a fixed annuitization time, to achieve higher final annuity, we consider a variable consumption rate. Moreover, to have a minimum guarantee for the final annuity, a safety level for the wealt…
A framework uses variational Bayes for solving inverse problems efficiently.
This article reviews -bundles and their applications in geometry and physics.
We solve for the SO(3)-invariant Kahler-Einstein metric on with cone singularities along a smooth conic curve using numerical approach. The numerical results show the sharp range of angles () for the solvability of equations, and the right limit metric space (). These results exactly …
Study on energy storage's impact on electricity prices and profitability.
We give an abstract formulation of the formal theory partial differential equations (PDEs) in synthetic differential geometry, one that would seamlessly generalize the traditional theory to a range of enhanced contexts, such as super-geometry, higher (stacky) differential geometry, or even a combination of both. A moti…
Under suitable conditions on the range of the Gauss map of a complete submanifold of Euclidean space with parallel mean curvature, we construct a strongly subharmonic function and derive a-priori estimates for the harmonic Gauss map. The required conditions here are more general than in previous work and they therefore…
Motivated by Tverberg-type problems in topological combinatorics and by classical results about embeddings (maps without double points), we study the question whether a finite simplicial complex K can be mapped into R^d without higher-multiplicity intersections. We focus on conditions for the existence of almost r-embe…
The COS method for European options pricing is improved with a new bound for the number of terms.
Matrix approximation method for Bachelier option pricing and Greeks under stochastic volatility models
In this paper, a standard PDE for the pricing of arithmetic average strike Asian call option is presented. A Crank-Nicolson Implicit Method and a Higher Order Compact finite difference scheme for this pricing problem is derived. Both these schemes were implemented for various values of risk free rate and volatility. Th…
Paper proposes a new LSTM model for spatio-temporal learning.
Extended univariate Range Value-at-Risk to multivariate settings.
Improved GAN performance using higher-order Wasserstein moments.
New ensemble method improves model stability exponentially.
In this work, we develop a novel regularizer to improve the learning of long-range dependency of sequence data. Applied on language modelling, our regularizer expresses the inductive bias that sequence variables should have high mutual information even though the model might not see abundant observations for complex lo…
We focus on the robust principal component analysis (RPCA) problem, and review a range of old and new convex formulations for the problem and its variants. We then review dual smoothing and level set techniques in convex optimization, present several novel theoretical results, and apply the techniques on the RPCA probl…
New estimator stabilizes higher-order influence functions for stable statistical inference.
New curvature measure for causal sets derived from optimal transport.
Quantized Neural Networks (QNNs) are often used to improve network efficiency during the inference phase, i.e. after the network has been trained. Extensive research in the field suggests many different quantization schemes. Still, the number of bits required, as well as the best quantization scheme, are yet unknown. O…