On-device research index

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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6 results for “Abercrombie & Fitch”

A Stock Trading System for a Medium Volatile Asset using Multi Layer Perceptronq-fin.ST

A trading system predicts stock prices using DNNs for Abercrombie & Fitch Co. shares.

problem Complexity and unpredictability of stock market prices.

method Feed-forward deep neural networks (DNNs) for price prediction, technical indicators for trade generation.

result Increased profitability with high Sharpe, Sortino, and Calmar ratios.

stock trading deep learning technical indicators Abercrombie & Fitch NYSE

2022-01-17abs ↗pdf ↗

RELARM: A rating model based on relative PCA attributes and k-means clusteringq-fin.CP

Following widely used in visual recognition concept of relative attributes, the article establishes definition of the relative PCA attributes for a class of objects defined by vectors of their parameters. A new rating model (RELARM) is built using relative PCA attribute ranking functions for rating object description a…

2016-08-23abs ↗pdf ↗

A copula based Markov Reward approach to the credit spread in European Unionq-fin.CP

In this paper, we propose a methodology based on piece-wise homogeneous Markov chain for credit ratings and a multivariate model of the credit spreads to evaluate the financial risk in European Union (EU). Two main aspects are considered: how the financial risk is distributed among the European countries and how large …

2019-02-02abs ↗pdf ↗

Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streamsq-fin.GN

Paper analyzes deep learning models for credit rating prediction using text and numerical data.

problem Improving credit rating prediction using multi-modal deep learning.

method Testing different deep learning models and fusion strategies for structured and unstructured datasets.

result CNN-based multi-modal model with two fusion strategies outperformed other models.

credit rating deep learning multi-modal structured data unstructured data

2023-04-21abs ↗pdf ↗

The Epistemic Risk of Risk: A Modal Framework for Quantitative Risk Managementq-fin.RM

This paper introduces modal epistemic tools for risk management.

problem Identifying and certifying risk claims when institutions lack the necessary epistemic stance.

method Develops crisp and fuzzy modal semantics for assurance and working commitment, distinguishing between object-level risk claims and meta-level epistemic diagnostics.

result Risk governance should model evidential incompleteness and failures of escalation, not just hazards and losses.

risk management epistemic tools modal logic certification working commitment

2026-05-11abs ↗pdf ↗

A comparative study of forecasting Corporate Credit Ratings using Neural Networks, Support Vector Machines, and Decision Treesq-fin.RM

This study compares neural networks, SVM, and decision trees for corporate credit rating predictions.

problem Predicting corporate credit ratings using machine learning methods.

method Applied four machine learning techniques (Bagged Decision Trees, Random Forest, SVM, MLP) to credit rating datasets.

result Decision tree-based models outperformed other techniques in terms of 'Notch Distance' measure.

Corporate Credit Ratings Machine Learning Neural Networks Support Vector Machines Decision Trees

2020-07-13abs ↗pdf ↗