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 predicts academic achievement using students' support networks.
Study evaluates the impact of academic support center's face-to-face assistance on student performance.
Predicts academic risk in college students using interpretable machine learning.
This reviews the econophysics activities in Belgium from my admittedly biased point of view. Unknown historical notes or facts are presented for the first time explaining the aims, whence evolution of the research papers and friendly connections with colleagues. Comments on endeavors are also provided. The lack of offi…
Paper discusses how financial institutions' model risk management can benefit academic research.
Over the last 23 years, the U.S. Securities and Exchange Commission has required over 34,000 companies to file over 165,000 annual reports. These reports, the so-called "Form 10-Ks," contain a characterization of a company's financial performance and its risks, including the regulatory environment in which a company op…
This report was originally written as an industry white paper on Hedge Funds. This paper gives an overview to Hedge Funds, with a focus on risk management issues. We define and explain the general characteristics of Hedge Funds, their main investment strategies and the risk models employed. We address the problems in H…
Paper presents deep learning and ML for automated student performance estimation.
Study on academic finance evolution over 30 years.
Recently, due to the booming influence of online social networks, detecting fake news is drawing significant attention from both academic communities and general public. In this paper, we consider the existence of confounding variables in the features of fake news and use Propensity Score Matching (PSM) to select gener…
Study uses ML and causal analysis to predict student performance factors.
System identifies high impact research from academic papers.
Tool to estimate research impact for low-resource institutions.
We propose RecSim, a configurable platform for authoring simulation environments for recommender systems (RSs) that naturally supports sequential interaction with users. RecSim allows the creation of new environments that reflect particular aspects of user behavior and item structure at a level of abstraction well-suit…
SMM preserves matrix data structure for SVM classification.
Accurate time series prediction over long future horizons is challenging and of great interest to both practitioners and academics. As a well-known intelligent algorithm, the standard formulation of Support Vector Regression (SVR) could be taken for multi-step-ahead time series prediction, only relying either on iterat…
Geospatial framework assesses climate risks for California's banking and exposed sectors.
KT models struggle with student concept drift, but BKT remains the most stable.
Social media enhances or diminishes scientific status, depending on usage.
The study uses Hidden Markov Models to analyze student enrollment patterns and academic performance.
National statistical systems are the enterprises tasked with collecting, validating and reporting societal attributes. These data serve many purposes - they allow governments to improve services, economic actors to traverse markets, and academics to assess social theories. National statistical systems vary in quality, …
Study simulates liquidity in fractional ownership markets using ABM.
Study shows conventional data prep fails for insurance data, proposing new methods.
Network analysis techniques remain rarely used for understanding international management strategies. Our paper highlights their value as research tool in this field of social science using a large set of micro-data (20,000) to investigate the presence of networks of subsidiaries overseas. The research question is the …
A new method for name disambiguation in academic networks using multi-view attention and recurrent neural networks.
Gradient boosted decision trees (GBDT) is the leading algorithm for many commercial and academic data applications. We give a deep analysis of this algorithm, especially the histogram technique, which is a basis for the regulized distribution with compact support. We present three new modifications. 1) Share memory tec…
Recently, Basel Committee for Banking Supervision proposed to replace all approaches, including Advanced Measurement Approach (AMA), for operational risk capital with a simple formula referred to as the Standardised Measurement Approach (SMA). This paper discusses and studies the weaknesses and pitfalls of SMA such as …
Machine learning methods tend to outperform traditional statistical models at prediction. In the prediction of academic achievement, ML models have not shown substantial improvement over logistic regression. So far, these results have almost entirely focused on college achievement, due to the availability of administra…
Estimates citation impact to recommend best publication venue.
Game theory shows miners' hardware improvements don't centralize mining.
Develops a Bonus-Malus model for cyber risk insurance to incentivize cybersecurity.
This paper critiques the Standardized Measurement Approach (SMA) for operational risk and recommends maintaining Advanced Measurement Approach (AMA).
One of the important measures of quality of education is the performance of students in the academic settings. Nowadays, abundant data is stored in educational institutions about students which can help to discover insight on how students are learning and how to improve their performance ahead of time using data mining…
Bitcoin price prediction models fail to outperform a simple 'today's price' baseline, especially at longer horizons.
Recent research has demonstrated that feature attribution methods for deep networks can themselves be incorporated into training; these attribution priors optimize for a model whose attributions have certain desirable properties -- most frequently, that particular features are important or unimportant. These attributio…
Efficiently trains BERT on academic GPUs in 12 days.
On a daily investment decision in a security market, the price earnings (PE) ratio is one of the most widely applied methods being used as a firm valuation tool by investment experts. Unfortunately, recent academic developments in financial econometrics and machine learning rarely look at this tool. In practice, fundam…
Shifu2 discovers advisor-advisee relationships in collaboration networks.
Kaggle competitions offer valuable insights for business forecasting.
In recent years cryptocurrency trading has captured the attention of practitioners and academics. The volume of the exchange with standard currencies has known a dramatic increasing of late. This paper addresses to the need of models describing a bitcoin-US dollar exchange dynamic and their use to evaluate European opt…
The failure of landing a job for college students could cause serious social consequences such as drunkenness and suicide. In addition to academic performance, unconscious biases can become one key obstacle for hunting jobs for graduating students. Thus, it is necessary to understand these unconscious biases so that we…
Computer generated academic papers have been used to expose a lack of thorough human review at several computer science conferences. We assess the problem of classifying such documents. After identifying and evaluating several quantifiable features of academic papers, we apply methods from machine learning to build a b…
This study synthesizes stablecoin systems and develops a performance evaluation framework.
PhysicsFormer improves TSF models for GSWF with WEATHER-5K dataset.
Enhances insurance loss models using InsurTech data and machine learning.
Because the choice and tuning of the optimizer affects the speed, and ultimately the performance of deep learning, there is significant past and recent research in this area. Yet, perhaps surprisingly, there is no generally agreed-upon protocol for the quantitative and reproducible evaluation of optimization strategies…
Autonomous driving is getting a lot of attention in the last decade and will be the hot topic at least until the first successful certification of a car with Level 5 autonomy. There are many public datasets in the academic community. However, they are far away from what a robust industrial production system needs. Ther…
The professional services sector is at a turning point, with some industries showing growth opportunities.