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.
General
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