arXiv research

This paper summarizes closed-form relations for SE(3) maps and their derivatives.

In this paper, the geometric meaning of (alpha,beta)-norms is made clear. On this basis, we introduce a new class of Finsler metrics called general (alpha,beta)-metrics, which are defined by a Riemannian metric and an 1-form. These metrics not only generalize original (alpha,beta)-metrics naturally, but also include so…

PPO optimizes LLM-generated alpha weights for better trading performance.

Hybrid ML ensemble predicts market risk and generates alpha.

In this paper, we study a class of Finsler metrics called general $(α,β)$-metrics, which are defined by a Riemannian metric $α$ and a $1$-form $β$. We find an equation which is necessary and sufficient condition for such Finsler metric to be a Douglas metric. By solving this equation, we obtain all of general $(α,β)$-m…

This study introduces a new GAS blending ensemble model for Bitcoin price prediction.

Multiple hypothesis testing is a core problem in statistical inference and arises in almost every scientific field. Given a set of null hypotheses $\mathcal{H}(n) = (H_1,\dotsc, H_n)$, Benjamini and Hochberg introduced the false discovery rate (FDR), which is the expected proportion of false positives among rejected nu…

GAIF enhances online multiple testing with feedback, improving statistical power.

We study the problem of optimal trading using general alpha predictors with linear costs and temporary impact. We do this within the framework of stochastic optimization with finite horizon using both limit and market orders. Consistently with other studies, we find that the presence of linear costs induces a no-tradin…

Study assesses additional factors for identifying persistent alpha in pension funds.

Alpha-GPT 2.0 integrates human insights into AI-driven investment research.

Survey of AI in quant finance, from deep learning to LLMs.

Paper reviews the evolution of alpha from human insight to AI-powered systems.

LLMs show potential for predicting financial returns, contrary to common belief.

Hybrid AI system combines technical, sentiment analysis for adaptive equity trading.

AlphaEval evaluates alpha mining models efficiently and comprehensively.

AlphaNet improves supernets training with alpha-divergence.

We found that factors decay over time, with momentum fitting best.

The paper proposes a new risk model for foundation models in finance.

In the online multiple testing problem, p-values corresponding to different null hypotheses are observed one by one, and the decision of whether or not to reject the current hypothesis must be made immediately, after which the next p-value is observed. Alpha-investing algorithms to control the false discovery rate (FDR…

New probabilistic scheme combines deep learning with Runge-Kutta methods for solving PDEs.

It was proved in 1998 by Ben-David and Litman that a concept space has a sample compression scheme of size d if and only if every finite subspace has a sample compression scheme of size d. In the compactness theorem, measurability of the hypotheses of the created sample compression scheme is not guaranteed; at the same…

Study SL(2,C) character schemes for finitely generated groups.

A new method for computing image curvature efficiently and accurately.

Reduces multiclass and regression compression schemes to binary ones.

Study evaluates UK CDC schemes, finding intergenerational cross-subsidies in flat-accrual schemes and dynamic-accrual schemes can reduce but not eliminate them.

We study first-order optimization methods obtained by discretizing ordinary differential equations (ODEs) corresponding to Nesterov's accelerated gradient methods (NAGs) and Polyak's heavy-ball method. We consider three discretization schemes: an explicit Euler scheme, an implicit Euler scheme, and a symplectic scheme.…

Generalizes soft noncommutative schemes to flag varieties.

AES scheme improves Bermudan and American option pricing for Heston models.

In this paper we propose a new kind of high order numerical scheme for backward stochastic differential equations(BSDEs). Unlike the traditional $θ$-scheme, we reduce truncation errors by taking $θ$ carefully for every subinterval according to the characteristics of integrands. We give error estimates of this nonlinear…

Defines hypercomplex analytic spaces and schemes.

We extend the scheme developed in B. Düring, A. Pitkin, "High-order compact finite difference scheme for option pricing in stochastic volatility jump models", 2019, to the so-called stochastic volatility with contemporaneous jumps (SVCJ) model, derived by Duffie, Pan and Singleton. The performance of the scheme is asse…

New schemes for SDEs on manifolds keep solutions close to the manifold.

Vector fields on schemes have flows if rings are finitely generated.

In this paper we propose a generalized numerical scheme for backward stochastic differential equations(BSDEs). The scheme is based on approximation of derivatives via Lagrange interpolation. By changing the distribution of sample points used for interpolation, one can get various numerical schemes with different stabil…

Extends JKO scheme for iterative algorithms with unknown parameters.

A new scheme for FBSDEs simplifies computation without Monte Carlo.

A discretization scheme for nonnegative diffusion processes is proposed and the convergence of the corresponding sequence of approximate processes is proved using the martingale problem framework. Motivations for this scheme come typically from finance, especially for path-dependent option pricing. The scheme is simple…

Study on statistical estimation over Gaussian MAC, comparing analog and digital schemes.

Efficient simulation scheme for rough Heston model reduces computational cost.

Study finds risk management significantly improves pension scheme efficiency in Kenya.

In this paper, we propose an acceleration scheme for online memory-limited PCA methods. Our scheme converges to the first $k>1$ eigenvectors in a single data pass. We provide empirical convergence results of our scheme based on the spiked covariance model. Our scheme does not require any predefined parameters such as t…

In the present paper, we introduce a numerical scheme for the price of a barrier option when the price of the underlying follows a diffusion process. The numerical scheme is based on an extension of a static hedging formula of barrier options. For getting the static hedging formula, the underlying process needs to have…

The paper analyzes convergence of Riemannian SA schemes for stochastic optimization.

New CDC scheme avoids intergenerational subsidies, offering better outcomes.

We introduce (binary) Darboux transformation for general differential equation of the second order in two independent variables. We present a discrete version of the transformation for a 6-point difference scheme. The scheme is appropriate to solving a hyperbolic type initial-boundary value problem. We discuss several …

We present a new high-order compact scheme for the multi-dimensional Black-Scholes model with application to European Put options on a basket of two underlying assets. The scheme is second-order accurate in time and fourth-order accurate in space. Numerical examples confirm that a standard second-order finite differenc…

We develop high-order approximations for the Heston model.