Research on the Early Warning Mechanism of Financial Risk by Computer Technology

2014 ◽  
Vol 687-691 ◽  
pp. 4922-4925
Author(s):  
Liang Liu ◽  
Chun Ling Li
Keyword(s):  
Financial Markets ◽  
Empirical Analysis ◽  
Early Warning ◽  
Early Warning System ◽  
Financial Risk ◽  
Warning System ◽  
Warning Signal ◽  
Financial Risks ◽  
Early Warning Mechanism ◽  
Starting Point

The briefly review and the development of the financial risk early warning theory is first discussed in this study and the domestic and foreign research is analyzed as a brief summary. Secondly, the concept of financial risks, financial crisis and the financial early warning is defined. Financial fragility as a starting point is used to establish the rationality model of the financial risk early warning system. The early warning indicators is selected on the basis of the 12 indicators of macro-financial risks, 15 net financial indicators is selected to represent the financial markets according to the characteristics of China's financial markets. In the empirical part, the previous empirical analysis method is chosen to build the financial risk early warning signal system. In order to display China's financial risk profile, the proper model for the calculation is made on the basis of empirical analysis. Thus, in order to minimize the local financial risk, the early warning system should be established by the local government, together with some other necessary measures.

Early Warning System for SMEs as a Financial Risk Detector

2009 ◽  
pp. 220-238 ◽  
Author(s):  
Ali Serhan Koyuncugil
Keyword(s):  
Data Mining ◽  
Risk Management ◽  
Early Warning ◽  
Financial Management ◽  
Early Warning System ◽  
Quantitative Data ◽  
Financial Risk ◽  
Warning System ◽  
Theoretical Background ◽  
Effect Level

This chapter introduces an early warning system for SMEs (SEWS) as a financial risk detector which is based on data mining. In this study, the objective is to compose a system in which qualitative and quantitative data about the requirements of enterprises are taken into consideration, during the development of an early warning system. Furthermore, during the formation of system; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. Using the system, SME managers could easily reach financial management, risk management knowledge without any prior knowledge and expertise. In other words, experts share their knowledge with the help of data mining based and automated EWS.

scholarly journals Algorithm to Predict the Rainfall Starting Point as a Function of Atmospheric Pressure, Humidity, and Dewpoint

Climate ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 131
Author(s):  
Alfonso Gutierrez-Lopez ◽  
Ivonne Cruz-Paz ◽  
Martin Muñoz Mandujano
Keyword(s):  
Early Warning ◽  
Atmospheric Pressure ◽  
Urban Areas ◽  
Early Warning System ◽  
Warning System ◽  
Forecast Model ◽  
Flood Damage ◽  
Precipitation Forecast ◽  
Rainfall Forecasting ◽  
Starting Point

Forecasting extreme precipitations is one of the main priorities of hydrology in Latin America and the Caribbean (LAC). Flood damage in urban areas increases every year, and is mainly caused by convective precipitations and hurricanes. In addition, hydrometeorological monitoring is limited in most countries in this region. Therefore, one of the primary challenges in the LAC region the development of a good rainfall forecasting model that can be used in an early warning system (EWS) or a flood early warning system (FEWS). The aim of this study was to provide an effective forecast of short-term rainfall using a set of climatic variables, based on the Clausius–Clapeyron relationship and taking into account that atmospheric water vapor is one of the variables that determine most meteorological phenomena, particularly regarding precipitation. As a consequence, a simple precipitation forecast model was proposed from data monitored at every minute, such as humidity, surface temperature, atmospheric pressure, and dewpoint. With access to a historical database of 1237 storms, the proposed model allows use of the right combination of these variables to make an accurate forecast of the time of storm onset. The results indicate that the proposed methodology was capable of predicting precipitation onset as a function of the atmospheric pressure, humidity, and dewpoint. The synoptic forecast model was implemented as a hydroinformatics tool in the Extreme Precipitation Monitoring Network of the city of Queretaro, Mexico (RedCIAQ). The improved forecasts provided by the proposed methodology are expected to be useful to support disaster warning systems all over Mexico, mainly during hurricanes and flashfloods.

Study on early Warning Mechanism of Water Resources Security

2012 ◽  
Vol 260-261 ◽  
pp. 1079-1085
Author(s):  
Ming Qi Chang ◽  
Yan Li Fan
Keyword(s):  
Water Resources ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Operating Mechanism ◽  
Systematic Method ◽  
Early Warning Mechanism ◽  
Multi Level ◽  
Degree Classification

Early warning system of water resources security is a multi-level and complex system made of many factors. By analyzing current situation of water resources security early warning, operating mechanism of water resources security early warning system is put forward. Logic, time and knowledge related to operating mechanism are discussed. For early warning threshold decision is one of key technologies in water resources security early warning, warning threshold decision and warning degree classification of water resources security early warning are set forth. These methods are systematic method, control chart method, catastrophe theory method and expert decision method. Adopting the water resources security early warning system, situation can be analyzed and predicted promptly and effectively.

scholarly journals Early Warning System for Economic and Financial Risks in Kazakhstan

2009 ◽  
Author(s):  
Biswa Nath. Bhattacharyay ◽  
Dennis Dlugosch ◽  
Benedikt Kolb ◽  
Kajal Lahiri ◽  
Irshat Mukhametov ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Financial Risks

A Fish Swarm Algorithm for Financial Risk Early Warning

2018 ◽  
Vol 14 (4) ◽  
pp. 54-63
Author(s):  
Liu Yunshan
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Financial Risk ◽  
Simulation Analysis ◽  
Warning System ◽  
The Sustainable Development ◽  
Artificial Fish Swarm Algorithm ◽  
Artificial Fish Swarm ◽  
The Index System ◽  
Swarm Algorithm

The financial risk early warning system is important for promoting the sustainable development of enterprise, and in this article, the fish swarm algorithm is applied to it. First, the main financial risk factors of enterprise are summarized. Second, the index system of the financial risk early warning system is constructed based on relating theory. Third, the basic theory of artificial fish swarm algorithm is studied, and the mathematical models are constructed. Then, the wavelet neutral network is improved based on the fish swarm algorithm, and the algorithm procedure is designed. Finally, a simulation analysis is carried out, and the predicting correctness of samples is 100%, and results show that the fish swarm algorithm is an effective method for improving the financial risk early warning system.

Early Warning System for Financial Crises

2018 ◽  
pp. 1-25 ◽  
Author(s):  
Amir Manzoor
Keyword(s):  
Financial Crisis ◽  
Early Warning ◽  
Financial Crises ◽  
Early Warning System ◽  
Financial Stability ◽  
Time Horizon ◽  
Warning System ◽  
False Alarms ◽  
Financial Risks ◽  
Policy Makers

To maintain financial stability, prevention of financial crisis is very important. This prevention is especially is especially important for developing countries where we need robust instruments for prediction of financial crises. One such instrument is Early Warning System (EWS). An EWS provided signals that could reflect the likelihood of a financial crisis over a given time horizon. Changing nature of financial risks due to liberalization of economies has increased the importance of an effective EWS. This chapter explores the state of the art of EWS. It is suggested that policy makers should take into account their objectives and related thresholds of various while developing an EWS since there exists a sharp trade-off between correctly calling crises and false alarms.

scholarly journals Development of an operational coastal flooding early warning system

2012 ◽  
Vol 12 (2) ◽  
pp. 379-390 ◽  
Author(s):  
D.-J. Doong ◽  
L. Z.-H. Chuang ◽  
L.-C. Wu ◽  
Y.-M. Fan ◽  
C. C. Kao ◽  
...  
Keyword(s):  
Storm Surge ◽  
Early Warning ◽  
System Integration ◽  
Early Warning System ◽  
Warning System ◽  
Wave Model ◽  
Warning Signal ◽  
Coastal Flooding ◽  
Economic Losses ◽  
Astronomical Tide

Abstract. Coastal floods are a consistent threat to oceanfront countries, causing major human suffering and substantial economic losses. Climate change is exacerbating the problem. An early warning system is essential to mitigate the loss of life and property from coastal flooding. The purpose of this study is to develop a coastal flooding early warning system (CoFEWs) by integrating existing sea-state monitoring technology, numerical ocean forecasting models, historical database and experiences, as well as computer science. The proposed system has capability of offering data for the past, information for the present and future. The system was developed for the Taiwanese coast due to its frequent threat by typhoons. An operational system without any manual work is the basic requirement of the system. Integration of various data sources is the system kernel. Numerical ocean models play an important role within the system because they provide data for assessment of possible flooding. The regional wave model (SWAN) that nested with the large domain wave model (NWW III) is operationally set up for coastal wave forecasting, in addition to the storm surge predicted by a POM model. Data assimilation technology is incorporated for enhanced accuracy. A warning signal is presented when the storm water level that accumulated from astronomical tide, storm surge, and wave-induced run-up exceeds the alarm sea level. This warning system has been in practical use for coastal flooding damage mitigation in Taiwan for years. An example of the system operation during the Typhoon Haitung which struck Taiwan in 2005 is illustrated in this study.

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