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.
This paper reviews digital transformation research from 2011-2024, focusing on corporate finance.
Blockchain technology, and more specifically Bitcoin (one of its foremost applications), have been receiving increasing attention in the scientific community. The first publications with Bitcoin as a topic, can be traced back to 2012. In spite of this short time span, the production magnitude (1162 papers) makes it nec…
This study analyzes EU ETS literature trends using bibliometric methods.
Survey analyzes economic research on cryptocurrencies using hybrid methods.
Study maps research streams in biodiversity finance, identifies key areas.
In order to evaluate the quality of the scientific research, we introduce a new family of scientific performance measures, called Scientific Research Measures (SRM). Our proposal originates from the more recent developments in the theory of risk measures and is an attempt to resolve the many problems of the existing bi…
Paper extends ranking metrics theory for financial positions.
Paper extends ranking metrics theory for financial positions.
Record linkage involves merging records in large, noisy databases to remove duplicate entities. It has become an important area because of its widespread occurrence in bibliometrics, public health, official statistics production, political science, and beyond. Traditional linkage methods directly linking records to one…
This review explores XAI in finance, highlighting common techniques and areas needing improvement.
High-dimensional tensors or multi-way data are becoming prevalent in areas such as biomedical imaging, chemometrics, networking and bibliometrics. Traditional approaches to finding lower dimensional representations of tensor data include flattening the data and applying matrix factorizations such as principal component…
We propose two spectral algorithms for partitioning nodes in directed graphs respectively with a cyclic and an acyclic pattern of connection between groups of nodes. Our methods are based on the computation of extremal eigenvalues of the transition matrix associated to the directed graph. The two algorithms outperform …
Orchestrating the Twin Transition in GBS: A Socio-Technical Framework
Scoping review finds EEG key in MCI research, identifying ERP/EEG, QEEG, and machine learning.
This review examines EWSs in finance to prevent economic crises.
Collectively, machine learning (ML) researchers are engaged in the creation and dissemination of knowledge about data-driven algorithms. In a given paper, researchers might aspire to any subset of the following goals, among others: to theoretically characterize what is learnable, to obtain understanding through empiric…