scholarly journals Incorporating Financial Big Data in Small Portfolio Risk Analysis: Market Risk Management Approach

2021 ◽  
Author(s):  
Donggyu Kim ◽  
Seunghyeon Yu
2020 ◽  
Vol 7 (6) ◽  
pp. 19
Author(s):  
Mouhamadou Saliou Diallo

The study of the BRVM market risk using the VaR method is a determining factor in assessing the performance of our equity portfolio composed of the BRVM composite index and the BRVM10 index. It has enabled us, with the help of Basel regulations, to use backtesting to determine the minimum amount of capital that an investor must hold per day to protect against risk. The kupiec test enables us to determine the reliability of VaR calculated at different confidence levels. The result of our study confirms, using the extreme VaR method, the robustness of our threshold-based portfolio risk management approach. It also confirms the problem of market attractiveness during times of financial crisis.


2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Jia Liu ◽  
Shiyong Li ◽  
Xiaoxia Zhu

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.


Author(s):  
A. M. Karminsky ◽  
E. V. Seryakova

Amid instability of financial markets and macroeconomic situation the necessity of improving bank risk-management instrument arises. New economic reality defines the need for searching for more advanced approaches of estimating banks vulnerability to exceptional, but plausible events. Stress-testing belongs to such instruments. The paper reviews and compares the models of market risk stress-testing of the portfolio of different financial instruments. These days the topic of the paper is highly acute due to the fact that now stress-testing is becoming an integral part of anticrisis risk-management amid macroeconomic instability and appearance of new risks together with close interest to the problem of risk-aggregation. The paper outlines the notion of stress-testing and gives coverage of goals, functions of stress-tests and main criteria for market risk stress-testing classification. The paper also stresses special aspects of scenario analysis. Novelty of the research is explained by elaborating the programme of aggregated complex multifactor stress-testing of the portfolio risk based on scenario analysis. The paper highlights modern Russian and foreign models of stress-testing both on solo-basis and complex. The paper lays emphasis on the results of stress-testing and revaluations of positions for all three complex models: methodology of the Central Bank of stress-testing portfolio risk, model relying on correlations analysis and copula model. The models of stress-testing on solo-basis are different for each financial instrument. Parametric StressVaR model is applicable to shares and options stress-testing;model based on "Grek" indicators is used for options; for euroobligation regional factor model is used. Finally some theoretical recommendations about managing market risk of the portfolio are given.


2014 ◽  
Vol 926-930 ◽  
pp. 4105-4109
Author(s):  
Xiao Li Cao

With the popularity of the Internet and global information continues to advance organizational information systems have become an important strategic resource for the survival of the importance of information security to protect its widespread concern. Once the information security organization information system is destroyed, the Organization for Security attribute information would cause tremendous impact the organization's business operation, the losses include not only economic, but also likely to organize image, reputation is a strategic competitive advantage even fatal injuries. However, the existing information systems of information security risk management approach to information system risk analysis and assessment with specific organizational environment and business background with fragmentation, lack of risk analysis and description of the formation process, carried only consider "technical" factors security decisions, lack of full expression to achieve the desired goal of a number of decisions on organizational decision-making. Therefore, the information system to carry information security risk management is essential.


2019 ◽  
Vol 16 (6) ◽  
pp. 60-77
Author(s):  
E. V. Vasilieva ◽  
T. V. Gaibova

This paper describes the method of project risk analysis based on design thinking and explores the possibility of its application for industrial investment projects. Traditional and suggested approaches to project risk management have been compared. Several risk analysis artifacts have been added to the standard list of artifacts. An iterative procedure for the formation of risk analysis artifacts has been developed, with the purpose of integrating the risk management process into strategic and prompt decision-making during project management. A list of tools at each stage of design thinking for risk management within the framework of real investment projects has been proposed. The suggested technology helps to determine project objectives and content and adapt them in regards to possible; as well as to implement measures aimed at reducing these risks, to increase productivity of the existing risk assessment and risk management tools, to organize effective cooperation between project team members, and to promote accumulation of knowledge about the project during its development and implementation.The authors declare no conflict of interest.


2020 ◽  
pp. 111-136
Author(s):  
Manuela Lucchese ◽  
Giuseppe Sannino ◽  
Paolo Tartaglia Polcini

Author(s):  
D.I. Gray ◽  
J.I. Reid ◽  
D.J. Horne

A group of 24 Hawke's Bay hill country farmers are working with service providers to improve the resilience of their farming systems. An important step in the process was to undertake an inventory of their risk management strategies. Farmers were interviewed about their farming systems and risk management strategies and the data was analysed using descriptive statistics. There was considerable variation in the strategies adopted by the farmers to cope with a dryland environment. Importantly, these strategies had to cope with three types of drought and also upside risk (better than expected conditions), and so flexibility was critical. Infra-structure was important in managing a dryland environment. Farmers chose between increased scale (increasing farm size) and geographic dispersion (owning a second property in another location) through to intensification (investing in subdivision, drainage, capital fertiliser, new pasture species). The study identified that there may be scope for further investment in infra-structural elements such as drainage, deeper rooting alternative pasture species and water harvesting, along with improved management of subterranean clover to improve flexibility. Many of the farmers used forage crops and idling capacity (reduced stocking rate) to improve flexibility; others argued that maintaining pasture quality and managing upside risk was a better strategy in a dryland environment. Supplementary feed was an important strategy for some farmers, but its use was limited by contour and machinery constraints. A surprisingly large proportion of farmers run breeding cows, a policy that is much less flexible than trading stock. However, several farmers had improved their flexibility by running a high proportion of trading cattle and buffer mobs of ewe hoggets and trade lambs. To manage market risk, the majority of farmers are selling a large proportion of their lambs prime. Similarly, cattle are either sold prime or store onto the grass market when prices are at a premium. However, market risk associated with the purchase of supplements and grazing was poorly managed.


2020 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
Dr. Pham Tuan Anh

The construction materialindustry is one of the most rapidly growing sectors, with many achievements both in Vietnam and in Asia. In recent years, its rapid growth has produced revenues from business activities. One of the key objectives of thispaper is to assess market risk volatility in construction material businesses in the 2012-2014 pre-low inflation period. Our first findings are to be found that beta values in general (< 1) for most of our constructionmaterialcompanies are appropriate when we apply quantitative, statistical and analytical methods to evaluate the asset beta and beta CAPM of 20 listed Viet Nam construction materialcompanies.However, we analyze the market risk volatility, determined byasset and equitybeta var, during the post-low inflation period in thissector and compare results in two circumstances: risk fluctuation in pre-law inflation time 2012-14is lower than that in post-low inflation period 2015-2017.Finally, if we observe in2 periods, BetaCAPM or equity beta mean goes up in case post-low inflation period. At last, policies in risk management and governance are suggested in the conclusion based on the research results and findings. In the post-low inflation environment, we alert that Beta fluctuations could bea little higher.JEL classification numbers:G00, G390, C83


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