Application of VaR in financial risk analysis of electricity markets

2003 ◽  
Author(s):  
Zhou Hao
Keyword(s):  
Risk Analysis ◽  
Electricity Markets ◽  
Financial Risk

Country Risk Analysis of Bangladesh

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Zahidur Rahman ◽  
Jannatul Ferdous Bristy
Keyword(s):  
Risk Analysis ◽  
Financial Risk ◽  
Political Risk ◽  
Multinational Companies ◽  
Country Risk ◽  
Low Risk ◽  
Primary Data ◽  
Policy Makers ◽  
Financial Factors ◽  
Political Economic

In the endeavor of conquering the worlds consumers, multinational companies face enormous risks. Such risks may arise from different political, economic, and financial factors. These factors are commonly referred to country risk as a whole. Focusing Bangladesh in this regard, objective of this study is to find out the level of country risk in terms of political, economic, and financial riskiness. Analysis of country risk has been done using an internationally recognized methodology named International Country Risk Guide (ICRG). For political risk analysis, primary data has been collected from 20 journalists, bureaucrats and policy makers, business persons, corporate professionals, and academicians with a structured closed-ended questionnaire. Results indicate that Bangladesh is in high risk position in terms of political risk, low risk position in terms of economic risk and very low risk position in terms of financial risk. Compositely, Bangladesh has been found to be a moderately risky country for investment.

scholarly journals Hydrological Layered Dialysis Research on Supply Chain Financial Risk Prediction under Big Data Scenario

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Jia Liu ◽  
Shiyong Li ◽  
Xiaoxia Zhu
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Risk Analysis ◽  
Risk Prediction ◽  
Financial Institutions ◽  
Surface Runoff ◽  
Financial Risk ◽  
Supply Chain Finance ◽  
Runoff Model

In recent years, internet development provides new channels and opportunities for small- and middle-sized enterprises’ (SMEs) financing. Supply chain finance is a hot topic in theoretical and practical circles. Financial institutions transform materialized capital flows into online data under big data scenario, which provides networked, precise, and computerized financial services for SMEs in the supply chain. By drawing on the risk management theory in economics and the distributed hydrological model in hydrology, this paper presents a supply chain financial risk prediction method under big data. First, we build a “hydrological database” used for the risk analysis of supply chain financing under big data. Second, we construct the risk identification models of “water circle model,” “surface runoff model,” and “underground runoff model” and carry on the risk prediction from the overall level (water circle). Finally, we launch the supply chain financial risk analysis from breadth level (surface runoff) and depth level (underground runoff); moreover, we integrate the analysis results and make financial decisions. The results can enrich the research on risk management of supply chain finance and provide feasible and effective risk prediction methods and suggestions for financial institutions.

scholarly journals A streamlined financial risk analysis for airports: case study of an airport disruption

2018 ◽  
Vol 35 ◽  
pp. 3-12 ◽  
Author(s):  
Francisco Jesus Jimenez Serrano ◽  
Antonin Kazda
Keyword(s):  
Risk Analysis ◽  
Financial Risk

scholarly journals Risk Analysis and Portfolio Modelling

2019 ◽  
Vol 12 (4) ◽  
pp. 154 ◽  
Author(s):  
David Edmund Allen ◽  
Elisa Luciano
Keyword(s):  
Risk Analysis ◽  
Financial Risk ◽  
Measurement Techniques ◽  
Risk Measurement ◽  
Risk Takers

Financial risk measurement is a challenging task because both the types of risk and their measurement techniques evolve quickly. This book collects a number of novel contributions for the measurement of financial risk, which addresses partially explored risks or risk takers in a wide variety of empirical contexts.

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