Value-at-Risk and Expected Shortfall in Technology Hardware and Equipment Industry Using Fuzzy Model

The fuzzy logic systems assist in simplifying large-scale risk management frameworks. For risks that do not have a proper quantitative probability model, a fuzzy logic system can aid model the cause-and-effect relationships, assess the degree of risk exposure and rank the key risks in a reliable way, considering both the available data and experts' opinions. For companies with broad risk exposure, diversified business and operations in multiple geographic regions, the long list of risks that need to be monitored makes in-depth risk analysis excessive, especially when there are entangled relationships among risk factors. Such an analysis could be costly and extremely tedious without the use of a fuzzy logic system. In addition, fuzzy logic systems include rules that clearly explain the linkage, dependence and relationships among modeled factors. It is helpful for identifying risk mitigation solutions. Resources can then be used to mitigate the risks with the highest level of exposure and relatively low hedging cost. This paper studied the application of Fuzzy Logic System Approach in determining the company's value-at-risk and also to assess risk analysis. This was applied to Technology Hardware and Equipment Industry in the Philippine. It was explored in areas where fuzzy logic models may be applied to improve risk assessment and risk decision-making. It discussed the methodology, framework and process of using fuzzy logic systems for risk management.