Results 41 to 50 of about 9,640,886 (365)
MACHINE LEARNING METHODS FOR SYSTEMIC RISK ANALYSIS IN FINANCIAL SECTORS
Financial systemic risk is an important issue in economics and financial systems. Trying to detect and respond to systemic risk with growing amounts of data produced in financial markets and systems, a lot of researchers have increasingly employed ...
Gang Kou+4 more
semanticscholar +1 more source
Artificial Intelligence and Systemic Risk
Artificial intelligence (AI) is rapidly changing how the financial system is operated, taking over core functions because of cost savings and operational efficiencies. AI will assist both risk managers and microprudential authorities.
Jón Dańıelsson+2 more
semanticscholar +1 more source
The Information in Systemic Risk Rankings [PDF]
We propose to pool alternative systemic risk rankings for financial institutions using the method of principal components. The resulting overall ranking is less affected by estimation uncertainty and model risk. We apply our methodology to disentangle the common signal and the idiosyncratic components from a selection of key systemic risk rankings that
Federico Nucera+6 more
openaire +9 more sources
Spatiotemporal Pattern and Drivers of Ecological Quality in Inner Mongolia
With the escalating global climate change and frequent human activities, Inner Mongolia, as a crucial ecological barrier in the Beijing-Tianjin-Hebei region, Bohai Economic Rim, and even the whole country, confronts many ecosystem issues.
Shouwei Li+6 more
doaj +1 more source
Macroprudential policy and bank systemic risk [PDF]
This paper investigates the effectiveness of macroprudential policy to contain the systemicrisk of European banks between 2000 and 2017. We use a new database (MaPPED) collected by experts at the ECB and national central banks with narrative ...
Meuleman, Elien, Vander Vennet, Rudi
core +1 more source
Pitfalls in systemic-risk scoring [PDF]
Regulatory data used to identify Systemically Important Financial Institutions (SIFIs) have gradually become public since 2014. Exploiting this transparency shock, we show that the scoring methodology implemented by the Basel Committee on Banking Supervision is biased and can create wrong incentives for regulated banks. Using regulatory data for 106 US
Benoît, Sylvain+2 more
openaire +7 more sources
Land Use Change in the Russian Far East and Its Driving Factors
This study systematically analyzes land use changes in the Russian Far East from 2000 to 2020, identifying key transformations and their driving factors.
Cong Wang, Xiaohan Zhang, Liwei Liu
doaj +1 more source
On the systemic nature of weather risk [PDF]
PurposeThe purpose of this paper is to assess the losses of weather‐related insurance at different regional levels. The possibility of spatial diversification of insurance is explored by estimating the joint occurrence on unfavorable weather conditions in different locations, looking particularly at the tail behavior of the loss distribution.Design ...
Xu, Wei+3 more
openaire +6 more sources
FloodKAN: Integrating Kolmogorov–Arnold Networks for Efficient Flood Extent Extraction
Flood events are among the most destructive natural catastrophes worldwide and pose serious threats to socioeconomic systems, ecological environments, and the safety of human life and property. With the advancement of remote sensing technology, synthetic
Cong Wang, Xiaohan Zhang, Liwei Liu
doaj +1 more source
Factors Influencing Wild Venison Consumption in Illinois
Venison serves as a sustainable alternative to conventional protein sources and is closely tied to wildlife conservation efforts. This study sought to identify key factors influencing wild game consumption.
Huicheng Chen+3 more
doaj +1 more source