scholarly journals Real Time Financial Risk Monitoring as a Data-intensive Application

2019 ◽  
Author(s):  
Petra Ristau ◽  
Lukas Krain
Keyword(s):  
Real Time ◽  
Financial Risk ◽  
Data Intensive ◽  
Risk Monitoring ◽  
Data Intensive Application

Risk early warning management and intelligent real-time system of financial enterprises based on fuzzy theory

2020 ◽  
pp. 1-11
Author(s):  
Qiaoying Ding
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Financial Risk ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Theory ◽  
Fuzzy Comprehensive Evaluation ◽  
Real Time System ◽  
Enterprise Risk ◽  
Early Warning Management

The financial market is changing rapidly. Since joining the WTO, our country’s financial companies have faced pressure from dual competition at domestic and abroad. The complex internal and external environment has forced financial enterprise managers to improve risk prevention awareness, early warning and monitoring, so as to responding to emergencies and challenges in the financial market. However, traditional forecasting and analysis methods have problems such as large workload, low efficiency, and low accuracy. Therefore, this article applies intelligent computing to the forecast of financial markets, using related concepts of fuzzy theory and Internet intelligent technology, and proposes to establish a model system for financial enterprise risk early warning management and intelligent real-time monitoring based on fuzzy theory. This article first collected a large amount of data through the literature investigation method, and made a systematic and complete introduction to the related theoretical concepts of fuzzy theory and financial risk early-warning management, has laid a sufficient theoretical foundation for the subsequent exploration of the application of fuzzy theory in financial enterprise risk early warning management and intelligent real-time systems; Then a fuzzy comprehensive evaluation method that combines the analytic hierarchy process and fuzzy evaluation method is proposed, taking a listed company mainly engaged in automobile sales in our province as a case, the company’s financial risk management and modeling experiment of the intelligent real-time system; Finally quoted specific cases again, used the fuzzy comprehensive evaluation method to carry out risk warning and evaluation on the PPP projects of private enterprises in our province, and concluded that the project risk score is between 20-60, which is meet the severe-medium range in the risk level. Research shows that the use of fuzzy theory and modern network technology can make more accurate warnings and assessments of potential and apparent risks of financial enterprises, greatly improving the safety of financial enterprise management and reducing the losses caused by various risks.

scholarly journals Real-time risk monitoring in business processes: A sensor-based approach

2013 ◽  
Vol 86 (11) ◽  
pp. 2939-2965 ◽  
Author(s):  
Raffaele Conforti ◽  
Marcello La Rosa ◽  
Giancarlo Fortino ◽  
Arthur H.M. ter Hofstede ◽  
Jan Recker ◽  
...  
Keyword(s):  
Real Time ◽  
Business Processes ◽  
Risk Monitoring

scholarly journals QoS Management for Embedded Databases in Multicore-Based Embedded Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Woochul Kang ◽  
Jaeyong Chung
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Control Method ◽  
Network Connectivity ◽  
Time Data ◽  
Quality Of Data ◽  
Multiple Control ◽  
Data Intensive ◽  
Real Time Data

With ubiquitous deployment of sensors and network connectivity, amounts of real-time data for embedded systems are increasing rapidly and database capability is required for many embedded systems for systematic management of real-time data. In such embedded systems, supporting the timeliness of tasks accessing databases is an important problem. However, recent multicore-based embedded architectures pose a significant challenge for such data-intensive real-time tasks since the response time of accessing data can be significantly affected by potential intercore interferences. In this paper, we propose a novel feedback control scheme that supports the timeliness of data-intensive tasks against unpredictable intercore interferences. In particular, we use multiple inputs/multiple outputs (MIMO) control method that exploits multiple control knobs, for example, CPU frequency and the Quality-of-Data (QoD) to handle highly unpredictable workloads in multicore systems. Experimental results, using actual implementation, show that the proposed approach achieves the target Quality-of-Service (QoS) goals, such as task timeliness and Quality-of-Data (QoD) while consuming less energy compared to baseline approaches.

scholarly journals The Psychophysiology of Real-Time Financial Risk Processing

2002 ◽  
Vol 14 (3) ◽  
pp. 323-339 ◽  
Author(s):  
Andrew W. Lo ◽  
Dmitry V. Repin
Keyword(s):  
Financial Markets ◽  
Real Time ◽  
Financial Risk ◽  
Emotional Responses ◽  
Decision Making Process ◽  
Electrodermal Responses ◽  
Cardiovascular Variables ◽  
Risk Processing ◽  
Volume Pulse ◽  
Blood Volume Pulse

A longstanding controversy in economics and finance is whether financial markets are governed by rational forces or by emotional responses. We study the importance of emotion in the decision-making process of professional securities traders by measuring their physiological characteristics (e.g., skin conductance, blood volume pulse, etc.) during live trading sessions while simultaneously capturing real-time prices from which market events can be detected. In a sample of 10 traders, we find statistically significant differences in mean electrodermal responses during transient market events relative to no-event control periods, and statistically significant mean changes in cardiovascular variables during periods of heightened market volatility relative to normal-volatility control periods. We also observe significant differences in these physiological responses across the 10 traders that may be systematically related to the traders' levels of experience.

System Safety Analysis Method Based on Real-Time Online Risk Monitoring Technology

2018 ◽  
Author(s):  
Sijuan Chen ◽  
Zhijian Zhang ◽  
He Wang ◽  
Min Zhang ◽  
Huazhi Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Dynamic Characteristics ◽  
Safety Analysis ◽  
System Component ◽  
Analysis Method ◽  
System Safety ◽  
Monitoring Technology ◽  
The Real ◽  
Online Risk ◽  
Risk Monitoring

In the continuous operation process of Nuclear Power Plant (NPP), its configuration is full of variety over time because of the system’s dynamic characteristics. There is a great need to update the risk/safety analysis models when it becomes necessary to reflect those dynamic characteristics of the system/component. Most of the current methods for risk/safety analysis belong to the scope of safety pre-analyzing, which analyzes the system risk/safety before system being in service. The main purpose of these safety pre-analyzing is to guide system design and optimization, but the real-time operational risk/safety analysis of NPPs is considered little. In order to know well the real-time risk/safety for system, a System Safety Analysis Method based on Real-time Online Risk Monitoring Technology is proposed. The safety risk model is established based on the modular fault tree that is used to represent logic structure of system. The real-time risk/safety is monitored according to the correspondence monitoring signal or data of component/system. Simultaneously the method can account for the change of risks based on the established mapping relationship between the state transition rules and corresponding risk/safety model updating rules. Finally, a case monitoring the safety for the system of two redundant pumps was used to demonstrate the effectiveness of the method.

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