Results 21 to 30 of about 51,480 (78)

Pre-big bang model has Planck problem [PDF]

Class.Quant.Grav. 15 (1998) 2803-2812, 1997
The pre-big bang's kinetic driven inflationary mechanism is not an adequate form of inflation: the Planck length grows more rapidly than the scale factor. In order to explain our large universe, the resulting post-big bang universe requires the same unnatural constants (Planck problem) as those of any other non-inflationary big bang model.
arxiv   +1 more source

From small markets to big markets [PDF]

arXiv, 2019
We study the most famous example of a large financial market: the Arbitrage Pricing Model, where investors can trade in a one-period setting with countably many assets admitting a factor structure. We consider the problem of maximising expected utility in this setting.
arxiv  

Financial Market Trend Forecasting and Performance Analysis Using LSTM [PDF]

arXiv, 2020
The financial market trend forecasting method is emerging as a hot topic in financial markets today. Many challenges still currently remain, and various researches related thereto have been actively conducted. Especially, recent research of neural network-based financial market trend prediction has attracted much attention. However, previous researches
arxiv  

Predicting Stock Prices with FinBERT-LSTM: Integrating News Sentiment Analysis [PDF]

The stock market's ascent typically mirrors the flourishing state of the economy, whereas its decline is often an indicator of an economic downturn. Therefore, for a long time, significant correlation elements for predicting trends in financial stock markets have been widely discussed, and people are becoming increasingly interested in the task of ...
arxiv   +1 more source

Network topology of the Euro Area interbank market [PDF]

In: Mingione, M., Vichi, M., Zaccaria, G. (eds), High-quality and Timely Statistics. CESS 2022. Studies in Theoretical and Applied Statistics. Springer, Cham (2024)
The rapidly increasing availability of large amounts of granular financial data, paired with the advances of big data related technologies induces the need of suitable analytics that can represent and extract meaningful information from such data. In this paper we propose a multi-layer network approach to distill the Euro Area (EA) banking system in ...
arxiv   +1 more source

A Wavelength Broker for Markets of Competing Optical Transport Networks [PDF]

arXiv, 2015
The current trend in optical networks is to open the entire wholesale market to competition. As a result, we will see, instead of a single big market player, optical transport networks competing with each other to attract customer demand. This paper presents a wavelength broker who acts on behalf of enterprises, web host companies, financial firm etc ...
arxiv  

On Multivariate Financial Time Series Classification [PDF]

arXiv
This article investigates the use of Machine Learning and Deep Learning models in multivariate time series analysis within financial markets. It compares small and big data approaches, focusing on their distinct challenges and the benefits of scaling. Traditional methods such as SVMs are contrasted with modern architectures like ConvTimeNet.
arxiv  

Financial Markets and ESG: How Big Data is Transforming Sustainable Investing in Developing countries [PDF]

arXiv
This study explores the role of big data adoption and financial market development in driving ESG investments in developing countries, using an instrumental variable (IV) approach to address endogeneity. The results show that big data adoption significantly enhances ESG investing, as data-driven analytics improve sustainability assessments and capital ...
arxiv  

Research and Design of a Financial Intelligent Risk Control Platform Based on Big Data Analysis and Deep Machine Learning [PDF]

arXiv
In the financial field of the United States, the application of big data technology has become one of the important means for financial institutions to enhance competitiveness and reduce risks. The core objective of this article is to explore how to fully utilize big data technology to achieve complete integration of internal and external data of ...
arxiv  

Analysis of Financial Risk Behavior Prediction Using Deep Learning and Big Data Algorithms [PDF]

arXiv
As the complexity and dynamism of financial markets continue to grow, traditional financial risk prediction methods increasingly struggle to handle large datasets and intricate behavior patterns. This paper explores the feasibility and effectiveness of using deep learning and big data algorithms for financial risk behavior prediction.
arxiv