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.
Study compares Islamic banks' accounting and market performance.
Detects malicious accounts in permissionless blockchains using graph properties and ML.
Paper examines LLM capability benchmarks through construct validity, favoring nomological account.
EB improves asset pricing by mining large strategies without lookahead bias.
Unified model improves multi-task learning by accounting for temporal misalignment.
GEM detects malicious accounts using adaptive embeddings from heterogeneous graphs.
AI-driven sales prioritization boosts renewal bookings by 8.08%.
Although the growth of share-based payments with performance conditions (hereafter, SPPC) is prominent today, the theoretical price of SPPC has not been sufficiently studied. Reflecting such a situation, the current accounting standards for share-based payments issued in 2004 have had many problems. This paper develops…
The performance of optimizers, particularly in deep learning, depends considerably on their chosen hyperparameter configuration. The efficacy of optimizers is often studied under near-optimal problem-specific hyperparameters, and finding these settings may be prohibitively costly for practitioners. In this work, we arg…
A family of parsimonious Gaussian cluster-weighted models is presented. This family concerns a multivariate extension to cluster-weighted modelling that can account for correlations between multivariate responses. Parsimony is attained by constraining parts of an eigen-decomposition imposed on the component covariance …
Tests assess if predictions are prudent by comparing observations and predictions.
The paper improves privacy accounting for discrete-valued mechanisms and the subsampled Gaussian mechanism.
A new method for tighter privacy loss accounting in adaptive analyses.
Decision trees perform well in complex interactions, even when interactions are not fully accounted for.
This paper tackles post-trade allocation inefficiencies and presents a uniform return allocation method.
Affective states have a critical role in driving performance and safety. They can degrade driver situation awareness and negatively impact cognitive processes, severely diminishing road safety. Therefore, detecting and assessing drivers' affective states is crucial in order to help improve the driving experience, and i…
Paper presents adaptive minimax risk classifiers for multidimensional concept drift.
Dimensionality reduction is a topic of recent interest. In this paper, we present the classification constrained dimensionality reduction (CCDR) algorithm to account for label information. The algorithm can account for multiple classes as well as the semi-supervised setting. We present an out-of-sample expressions for …
This paper applies quantum theory to cost accounting, focusing on WIP valuation.
As machine learning systems move from computer-science laboratories into the open world, their accountability becomes a high priority problem. Accountability requires deep understanding of system behavior and its failures. Current evaluation methods such as single-score error metrics and confusion matrices provide aggr…
This paper introduces compositional data analysis for financial ratios, improving industry-level analysis.
Bayesian decision theory outlines a rigorous framework for making optimal decisions based on maximizing expected utility over a model posterior. However, practitioners often do not have access to the full posterior and resort to approximate inference strategies. In such cases, taking the eventual decision-making task i…
Accounting frameworks follow stipulations of existing Accounting Theories. This exploratory research sets out to trace the evolution of accounting theories of Charge and Discharge Syndrome and the Corollary of Double Entry. Furthermore, it dives into the theories of Income Determination, garnishing it with areas of div…
Optimal tontine strategy maximizes withdrawals while minimizing shortfall.
Bayesian method for semi-structured models accounts for both types of uncertainty.
Computation of moments of transformed random variables is a problem appearing in many engineering applications. The current methods for moment transformation are mostly based on the classical quadrature rules which cannot account for the approximation errors. Our aim is to design a method for moment transformation for …
In this paper we consider an information theoretic approach for the accounting classification process. We propose a matrix formalism and an algorithm for calculations of information theoretic measures associated to accounting classification. The formalism may be useful for further generalizations and computer-based imp…
We introduce a new pension product that offers retirees the opportunity for a lifelong income and a bequest for their estate. Based on a tontine mechanism, the product divides pension savings between a tontine account and a bequest account. The tontine account is given up to a tontine pool upon death while the bequest …
D-CBRS manages memory for continual learning by accounting for intra-class diversity.
Fake engagement is one of the significant problems in Online Social Networks (OSNs) which is used to increase the popularity of an account in an inorganic manner. The detection of fake engagement is crucial because it leads to loss of money for businesses, wrong audience targeting in advertising, wrong product predicti…
Accounting fraud is a global concern representing a significant threat to the financial system stability due to the resulting diminishing of the market confidence and trust of regulatory authorities. Several tricks can be used to commit accounting fraud, hence the need for non-static regulatory interventions that take …
Big data transforms accounting and auditing, enhancing insights but posing challenges.
Paper introduces Functional Effects Models to account for individual heterogeneity in panel data.
AI bias arises from human-defined goals, not algorithmic flaws.
The paper explores how equivariant models' biases affect latent representations for better performance.
Assessment of risk levels for existing credit accounts is important to the implementation of bank policies and offering financial products. This paper uses cluster analysis of behaviour of credit card accounts to help assess credit risk level. Account behaviour is modelled parametrically and we then implement the behav…
We present a continuous-time maximum likelihood estimation methodology for credit rating transition probabilities, taking into account the presence of censored data. We perform rolling estimates of the transition matrices with exponential time weighting with varying horizons and discuss the underlying dynamics of trans…
It is often the case that, within an online recommender system, multiple users share a common account. Can such shared accounts be identified solely on the basis of the userprovided ratings? Once a shared account is identified, can the different users sharing it be identified as well? Whenever such user identification …
Electricity accounts for 25% of global greenhouse gas emissions. Reducing emissions related to electricity consumption requires accurate measurements readily available to consumers, regulators and investors. In this case study, we propose a new real-time consumption-based accounting approach based on flow tracing. This…
Proposes a credit scoring system for Aave accounts.
New tontine model with transaction costs for retirees.
Bayesian calibration speeds up ABM for pandemic modeling.
Chunking is a significant CL problem, accounting for half of performance drop, and current methods don't address it.
The paper proposes a test to assess rater accuracy while accounting for rater covariates.
A new classification rule for FDA improves classification performance by accounting for unequal covariance matrices.
A new privacy accountant for Gaussian differential privacy measures individual privacy losses.
SLEID detects illicit accounts in DeFi transactions using semi-supervised learning.
This review explores ChatGPT in accounting and finance.