The Importance of Risk Analysis in Capital Budgeting

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The Importance of Risk Analysis in Capital Budgeting

By | April 2007
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The Importance of Risk Analysis in Capital Budgeting
In today's business environment, company executives are often required to participate in a company's capital budgeting process as the sponsor, reviewer or approving authority of investment decisions. In any of these capacities, it is imperative that the executive understands many of the key aspects of capital budgeting such as analyzing income statements, balance sheets, cash flows, appropriately discounting cash flows and, most importantly, identifying risk. Capital budgeting investment decisions are important because of the potential effects on the company's current and future assets. Many times the decisions regarding investments are irreversible in the sense that liquidation of a particular investment, after a commitment, can be costly and/or devastating to the financial strength of the company (Abdelsamad, 1979). To ensure investment decisions do not lead to negative consequences, company executives need to analyze the risks associated with the investment decision and mitigate those risks. The better the executive understands the nature and level of risks, the better the decision, and ultimately, the better financial strength of the company. However, analyzing risk can be very difficult. Ho and Pike (1991) describe why the challenge of handling risk and uncertainty is one of the most prominent problems in capital budgeting practice. They describe the uncertainty of risks due to the underlying economic environment and its instabilities and inflation levels. In practice, executives can handle risks in two ways. The simple risk-adjustment method is based on the executive's estimations and intuitive adjustments to cash flows. The probabilistic risk analysis (PRA) is based on evaluation of the uncertainties associated with particular variables before decisions are made. "Commonly-employed PRA techniques include sensitivity analysis, basic probability analysis, decision-tree analysis, Monte Carlo simulation...

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