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.
Algorithm improves SLR efficiency in financial narratives.
Study of common financial data patterns across stocks.
This review examines DL models for financial forecasting.
Digital Financial Services continue to expand and replace the delivery of traditional banking services to the customers through innovative technologies to meet the growing complex needs and globalization challenges. These diversified digital products help the organizations (service providers) to improve their firm perf…
This research uses BERT for financial sentiment analysis and LSTM for stock return prediction.
Study evaluates financial misstatement detection methods, highlighting evaluation process impact.
Algorithms are increasingly common components of high-impact decision-making, and a growing body of literature on adversarial examples in laboratory settings indicates that standard machine learning models are not robust. This suggests that real-world systems are also susceptible to manipulation or misclassification, w…
This review examines deep learning in financial fraud detection over 5 years.
LR-Robot accelerates SLRs by combining expert oversight and AI, revealing trends and patterns in financial research.
Long short-term memory network outperforms seasonal model in JSE Top 40 forecasting.
Green bond leaks impact equity markets, altering investor reactions.
Paper uses neural nets for financial optimization problems.
Multi-stage financial decision optimization under uncertainty depends on a careful numerical approximation of the underlying stochastic process, which describes the future returns of the selected assets or asset categories. Various approaches towards an optimal generation of discrete-time, discrete-state approximations…
Comprehensive review of robust portfolio selection models.
This paper addresses the log-optimal portfolio for a general semimartingale model. The most advanced literature on the topic elaborates existence and characterization of this portfolio under no-free-lunch-with-vanishing-risk assumption (NFLVR). There are many financial models violating NFLVR, while admitting the log-op…
The article reviews how to set stochastic volatility model parameters.
Wealth inequality is an important matter for economic theory and policy. Ongoing debates have been discussing recent rise in wealth inequality in connection with recent development of active financial markets around the world. Existing literature on wealth distribution connects the origins of wealth inequality with a v…
Study analyzes COFCO's acquisition of Mengniu Dairy, revealing financial and non-financial impacts.
Generative Adversarial Networks create realistic financial correlation matrices.
Mining financial text documents and understanding the sentiments of individual investors, institutions and markets is an important and challenging problem in the literature. Current approaches to mine sentiments from financial texts largely rely on domain specific dictionaries. However, dictionary based methods often f…
New method improves conditional covariance estimation using targeted groups of assets.
Reliable calculations of financial risk require that the fat-tailed nature of prices changes is included in risk measures. To this end, a non-Gaussian approach to financial risk management is presented, modeling the power-law tails of the returns distribution in terms of a Student- (or Tsallis) distribution. Non-Gau…
We study the concept of financial bubble in a market model endowed with a set of probability measures, typically mutually singular to each other. In this setting we introduce the notions of robust bubble and robust fundamental value in a consistent way with the existing literature in the case a unique prior exists. The…
In line with the recent research and debates about econophysics and financial economics, this article discusses on usual misunderstandings between the two disciplines in terms of modelling and basic hypotheses. In the literature devoted to econophysics, the methodology used by financial economists is frequently conside…
The basic financial purpose of a firm is to maximize its value. An inventory management system should also contribute to realization of this basic aim. Many current asset management models currently found in financial management literature were constructed with the assumption of book profit maximization as basic aim. H…
Faster trading algorithms aren't always better, as shown in simulated financial markets.
Deep learning models improve financial price forecasting accuracy.
Explains financial market simulation mechanisms and agent behaviors.
Financial portfolio optimization is a widely studied problem in mathematics, statistics, financial and computational literature. It adheres to determining an optimal combination of weights associated with financial assets held in a portfolio. In practice, it faces challenges by virtue of varying math. formulations, par…
The paper reviews recent statistical methods for financial markets, focusing on jumps, volatility, and microstructure noise.
Proposes neural model for stock embeddings to capture nuanced asset correlations.
I sketch a program for a microeconomic theory of the main component of the business cycle as a recurring disequilibrium, driven by incompleteness of the financial market and by information asymmetries between borrowers and lenders. This proposal seeks to incorporate five distinct but connected processes that have been …
Graph auto-encoders predict stock market instability by measuring graph structure changes.
Topological data analysis reveals complex financial-ratio-stock return relationships.
Study clusters Kenyan medical insurance companies based on financial performance and reporting consistency.
According to theoretical models of valuing risky corporate securities, risk of default is primary component in overall yield spread. However, sizable empirical literature considers it otherwise by giving more importance to non-default risk factors. Current study empirically attempts to provide relative solution to this…
We consider stochastic control systems affected by a fast mean reverting volatility driven by a pure jump Lévy process. Motivated by a large literature on financial models, we assume that evolves at a faster time scale than the assets, and we study the asymptotics as $\varepsilon\t…
LLMs improve financial analysis by processing large data sets.
Financial models shape markets through performativity, creating self-fulfilling prophecies.
Survey of determinism issues in financial AI systems.
Paper assesses financial potential for enterprise development.
Trust lies at the crux of most economic transactions, with credit markets being a notable example. Drawing on insights from the literature on coordination games and network growth, we develop a simple model to clarify how trust breaks down in financial systems. We show how the arrival of bad news about a financial agen…
The paper surveys mathematical results on filtration enlargement with financial examples.
This paper reviews transfer learning for financial data predictions, highlighting its potential.
The econophysics approach to socio-economic systems is based on the assumption of their complexity. Such assumption inevitably lead to another assumption, namely that underlying interconnections within socio-economic systems, particularly financial markets, are nonlinear, which is shown to be true even in mainstream ec…
This paper contributes to the literature on international stock market comovements and contagion. The novelty of our approach lies in application of wavelet tools to high-frequency financial market data, which allows us to understand the relationship between stock markets in a time-frequency domain. While major part of…
Paper extends quantile factor analysis with probabilistic methods for better economic policy and financial condition prediction.
A new GCN model detects cryptocurrency fraud by considering network evolution and balance theory.