Computer Simulation in Financial Risk Management

Computer programs that simulate complex processes in the real world can provide a quantitative tool for determining how much debt can be added safely to a company's capital structure. The increasing number of bankruptcies and defaults in today's international business arena result from debt overload and point to major shortcomings in the conventional financial evaluation process. In this book, Roy L. Nersesian describes why current methods of risk management fail and how computer simulation can be employed to determine the safe level of debt more accurately. Because the decision to add debt to an organization requires favorable, and essentially independent, decisions from both the borrower and lender, it is necessary to quantify both perspectives. Through actual examples readers will learn how to do this and to translate an actual business situation into a simulation model or program.



Current evaluation systems, according to Nersesian, fail to incorporate the cyclical nature of business activity. They result all too often in an overly optimistic projection of cash flow. Simulation techniques are better able to incorporate the transience of good times and put quantitative analysis of risk on par with quantitative analysis of reward. Simulation techniques also reduce the role of speculative, and highly subjective, judgment. For example, decisionmakers who are not familiar personally with a particular business area, assign more risk to that area than those who are. A quantified risk management system enables executives to rank projects by the degree of risk much as they currently rank them by degree of profitability. The book presents the concept of simulation in terms that can be understood by generalists in corporations and financial institutions. At the same time, it provides computer programmers with an understanding of risk management principles. It will provide a valuable resource for: financial executives, planners and strategists in corporate and governmental organizations; bank lending officers; and computer programmers working with these organizations.