Identifying Broad and Narrow Financial Risk Factors with Convex Optimization

2016 ◽  
Author(s):  
Alexander Shkolnik ◽  
Lisa R. Goldberg ◽  
Jeffrey R Bohn
Keyword(s):  
Risk Factors ◽  
Convex Optimization ◽  
Financial Risk

scholarly journals Numerical estimates of risk factors contingent on credit ratings

2021 ◽  
Author(s):  
T. Gärtner ◽  
S. Kaniovski ◽  
Y. Kaniovski
Keyword(s):  
Risk Factors ◽  
Financial Risk ◽  
Credit Rating ◽  
Likelihood Function ◽  
Adverse Outcome ◽  
Credit Ratings ◽  
Industry Sector ◽  
Random Events ◽  
Historical Transition ◽  
Industry Sectors

AbstractAssuming a favorable or an adverse outcome for every combination of a credit class and an industry sector, a binary string, termed as a macroeconomic scenario, is considered. Given historical transition counts and a model for dependence among credit-rating migrations, a probability is assigned to each of the scenarios by maximizing a likelihood function. Applications of this distribution in financial risk analysis are suggested. Two classifications are considered: 7 non-default credit classes with 6 industry sectors and 2 non-default credit classes with 12 industry sectors. We propose a heuristic algorithm for solving the corresponding maximization problems of combinatorial complexity. Probabilities and correlations characterizing riskiness of random events involving several industry sectors and credit classes are reported.

Store brand and perceived risk on private label brand attitude

2020 ◽  
Vol 12 (1) ◽  
pp. 133-150 ◽  
Author(s):  
M.K.M. Manikandan
Keyword(s):  
Risk Factors ◽  
Perceived Risk ◽  
Tamil Nadu ◽  
Financial Risk ◽  
Perceived Quality ◽  
Negative Influence ◽  
Private Label ◽  
Social Risk ◽  
Content Type ◽  
The Social

Purpose The purpose of this paper is to find the influence of retailer equity and perceived risk on attitudes toward private label brand (PLB) grocery products. Design/methodology/approach Retailer equity includes four variables: retailer awareness, retailer association, retailer perceived quality and retailer loyalty. The perceived risk factors include functional risk, financial risk and social risk. The attitude toward PLBs was taken as the dependent variable. The study was carried out by using a standardized questionnaire for all three constructs. The convenience sampling method was adopted to carry out data collection from customers of organized retail stores in the city of Coimbatore, in the state of Tamil Nadu, India. The relationship between the three variables was studied with structural equation modeling using IBM SPSS Amos software. Findings The study revealed that excluding the Financial Risk and the Social Risk, functional risk alone has significant influence over the PLB Attitude. The Retailer Equity variables, retailer perceived quality and retailer loyalty have positive influence on the PLB Attitude, while the other two variables do not show any influence. Retailer Awareness shows a negative influence over the social risk. Retailer Association does not show any influence on any of the three risk factors. Retailer perceived quality shows negative influence over the functional risk while retailer loyalty negatively influences social risk. Research limitations/implications The research study was carried out in cities that are populous in the Indian state of Tamil Nadu. All the respondents came from three cities in Tamil Nadu, namely, Coimbatore, Tiruppur and Madurai. Hence, extending the findings of the study to other countries where organized retail penetration is deeper may be attempted with caution. Practical implications The study will offer managers in the retail industry some understanding of the risk-relieving factors in operation when buying grocery goods. Originality/value The research paper contributes to the literature concerning the role played by retailer equity and perceived risk factors on attitudes toward PLBs.

scholarly journals ETHICS, SOCIAL RESPONSIBILITY AND CORRUPTION AS RISK FACTORS

10.26458/1711 ◽  
2017 ◽  
Vol 17 (1) ◽  
pp. 17
Author(s):  
Alexandru GRIBINCEA
Keyword(s):  
Risk Factors ◽  
Social Responsibility ◽  
Financial Risk ◽  
Financial Structure ◽  
Insurance Company ◽  
Financial Return ◽  
Net Profit ◽  
The Cost

 The financial risk characterises the variability of net profit, subject to the financial structure of the insurance. The capital of the insurance company has two elements (the equity and the borrowed one) that differ fundamentally in the cost they generate. If the company uses loans, it will bear systematically the related financial expenses, too. Through its size and cost, indebtedness leads to the variation and changes the size of financial risk. Resorting to the debt is justified through the high remuneration of equity in relation to borrowed capital, thus increasing the financial return.  

scholarly journals Risk Factors Impacting the Project Value Created by Green Buildings in Saudi Arabia

2020 ◽  
Vol 10 (21) ◽  
pp. 7388
Author(s):  
Wael Alattyih ◽  
Husnain Haider ◽  
Halim Boussabaine
Keyword(s):  
Risk Factors ◽  
Saudi Arabia ◽  
Financial Risk ◽  
Significant Risk ◽  
Principal Component ◽  
Green Building ◽  
Building Design ◽  
Green Buildings ◽  
Sustainable Urban Development ◽  
Green Building Design

Green buildings are playing a pivotal role in sustainable urban development around the world, including Saudi Arabia. Green buildings subject to various sources of risk that influence the potential outcomes of the investments or services added in their design. The present study developed a structured framework to examine various risks that may lead to green buildings’ value destruction in Saudi Arabia. The framework initiates with identification of 66 potential risk factors from reported literature. A questionnaire compiling a list of identified risk factors was hand-delivered to 300 practitioners (managers, engineers, and architects) having knowledge of value engineering in the construction industry, and an overall response rate of 29.7% was achieved. Subsequently, descriptive statistics ranked the risk factors based on scores given by the respondents. The principal component analysis extracted 16 components, based on the likelihood of risk factors impacting the value created by green building design. Finally, the factor analysis grouped the 35 most significant risk factors in 5 clusters—i.e., 8 in functional risk, 13 in financial risk, 3 in operational risk, 3 in environmental risk, and 8 in management risk cluster. The study enhances the understanding of the importance of the risk factors’ impact on value creation. Based on the results, the value management (or engineering) teams and the top-level management can identify, manage, and control the risk factors that have a significant impact on the project value created by green building design.

scholarly journals Effect of Consumer Demographics and Risk Factors on Online Purchase Behaviour in Malaysia

Societies ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 10
Author(s):  
Noorshella Che Nawi ◽  
Abdullah Al Mamun ◽  
Nurul Hasliana Binti Hamsani ◽  
Mohd Nazri bin Muhayiddin
Keyword(s):  
Risk Factors ◽  
Financial Risk ◽  
Peninsular Malaysia ◽  
Social Risk ◽  
Cross Sectional ◽  
Online Purchase ◽  
Consumer Demographics ◽  
The Government ◽  
Cross Sectional Design ◽  
Psychological Risk

It is evident that there has been a rapid growth of electronic commerce and online shopping. Hence, this study examined the effect of selected antecedents and risk factors on online purchase behaviour in Malaysia under the premise of an adapted stimulus–organism–response (SOR) model. This study used a cross-sectional design to collect data from 330 selected respondents from Peninsular Malaysia. The findings revealed that the age of consumers, as well as perceived after-sales risk, financial risk, psychological risk, and social risk, had a significant effect on the online purchase behaviour in Malaysia. Apart from enriching the existing body of knowledge, this study offers several significant practical implications. Based on the findings, it is recommended that the government and online businesses should focus on Generation Y, who are known to be more tech-savvy, through policies and programmes in order to reduce the various types of perceived risks associated with online transactions. It is believed that this effort could enhance online consumerism among the residents of Malaysia.

scholarly journals Management of innovation projects: financial risks

2019 ◽  
Vol 135 ◽  
pp. 04053
Author(s):  
Tatyana Burtseva ◽  
Lyudmila Rudenko ◽  
Olga Fokina ◽  
Olga Pavlyutenkova
Keyword(s):  
Risk Factors ◽  
Cluster Analysis ◽  
Risk Management ◽  
Financial Risk ◽  
Financial Risks ◽  
Financial Risk Management ◽  
Project Activity ◽  
Management Of Innovation ◽  
Innovation Projects ◽  
Main Target

Management of innovative projects requires a deep assessment of various risks, and financial risks here are especially important. Management of financial risks in the field of innovative activity significantly affects the efficiency of the whole work. It is also one of the most important components of the project activity. The article describes research results of the main target segments for planning a program of financial risk management. The research is based on a cluster analysis that describes the most significant groups of risk factors. Enterprises implementing innovative projects need to pay special attention to these factors, especially when developing various measures for the formation and development of innovative activities and the management of various risks.

scholarly journals A Framework for Analysis and Prediction of Operational Risk Stress

2021 ◽  
Vol 26 (1) ◽  
pp. 19
Author(s):  
Peter Mitic
Keyword(s):  
Risk Factors ◽  
Financial Risk ◽  
Time Window ◽  
Operational Risk ◽  
Specific Reference ◽  
Mild Stress ◽  
Regulatory Capital ◽  
Regulatory Requirements ◽  
Extreme Stress ◽  
Loss Data

A model for financial stress testing and stability analysis is presented. Given operational risk loss data within a time window, short-term projections are made using Loess fits to sequences of lognormal parameters. The projections can be scaled by a sequence of risk factors, derived from economic data in response to international regulatory requirements. Historic and projected loss data are combined using a lengthy nonlinear algorithm to calculate a capital reserve for the upcoming year. The model is embedded in a general framework, in which arrays of risk factors can be swapped in and out to assess their effect on the projected losses. Risk factor scaling is varied to assess the resilience and stability of financial institutions to economic shock. Symbolic analysis of projected losses shows that they are well-conditioned with respect to risk factors. Specific reference is made to the effect of the 2020 COVID-19 pandemic. For a 1-year projection, the framework indicates a requirement for an increase in regulatory capital of approximately 3% for mild stress, 8% for moderate stress, and 32% for extreme stress. The proposed framework is significant because it is the first formal methodology to link financial risk with economic factors in an objective way without recourse to correlations.

scholarly journals Perceived Risk Factors Affect Intention To Use FinTech

2020 ◽  
Vol 6 (2) ◽  
pp. 453-463
Author(s):  
Kin Leong Tang ◽  
Chee Keong Ooi ◽  
Jia Bao Chong
Keyword(s):  
Risk Factors ◽  
Perceived Risk ◽  
Structural Equation ◽  
Financial Risk ◽  
Functional Performance ◽  
Negative Impact ◽  
Intention To Use ◽  
Four Dimensions ◽  
Significant Negative Impact ◽  
Negative Effect

Objective: Studies show there is a high acceptance of FinTech development in Malaysia. However, the perceived risk factors that hinder a user's intention to use FinTech remains vague. Research on perceived risk is limited, especially the use of FinTech in the context of Malaysia. Therefore, this study aims to narrow the gap in perceived risk factors of FinTech. Methodology: A total of 302 participants participated in the study. Collected data and hypotheses were tested using the method of structural equation modelling. Results: It is found that three of the four dimensions of financial risk, legal risk and operational risk have a significant negative impact on the intention to use FinTech. The findings found that security risks do not have a significant negative effect on the intention to use FinTech. This result is consistent with the finding that Malaysian consumers' perception of e-payment is not significantly related to perceived security. Implication: The results help practitioners better conceptualise and reduce risk barriers in preparing for the disruption of FinTech. Practitioners are also advised to pay attention to FinTech's operational skills and system functional performance in FinTech services.

Sign in / Sign up

Export Citation Format

Share Document