FINANCIAL MODELING. Simon Benninga. With a section on Visual Basic for Applications by Benjamin Czaczkes. F ourth E dition. The MIT. Library of Congress Cataloging-in-Publication Data Benninga, Simon. Financial modeling / Simon Benninga.—Fourth edition. pages cm Includes bibliographical . Items 8 - 17 Financial Modeling By Simon Benninga, 3rd Edition. Karen Lopez. A E= mc 2 This eBook is downloaded from 1 aracer.mobi .

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Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. Financial Modeling bridges this . Financial Modeling Benninga - Download as PDF File .pdf), Text File .txt) or read Financial modeling / Simon Benninga. or information storage and retrieval ). FIN T01– FINANCIAL MODELING – Winter Instructor: Dr. Ying Simon Benninga, Financial Modeling: Fourth Edition, The MIT Press, Cambridge.

The cash receipts or cash flows, as we will call them may be certain or uncertain. In this chapter we analyze the values of nonrisky cash flows—future receipts that we will receive with absolute certainty. The basic concept to which we will return over and over is the concept of opportunity cost. Opportunity cost is the return that would be required of an investment to make it a viable alternative to other, similar, investments. When we calculate the internal rate of return, we compare the calculated return to the investment's opportunity cost to judge its value. When it is applied to risky cash flows as in the next chapter , we will sometimes call the opportunity cost the risk-adjusted discount rate RADR or the weighted average cost of capital WACC. Books24x7, Inc. If a bank would pay us an annual interest rate of 10 percent on a five-year deposit, then this 10 percent is the investment's opportunity cost, the alternative benchmark return to which we want to compare the investment.

We use all of these models to calculate the weighted average cost of capital WACC , the appropriate discount rate for valuation of firm cash flows. Throughout this chapter we apply our techniques to calculating the cost of capital for Abbott Laboratories. A Terminological Note As noted in the previous chapter, "cost of capital" is a synonym for the "appropriate discount rate" to be applied to a series of cash flows.

In finance, "appropriate" is most often a synonym for "risk-adjusted. Consider, for example, the case of a stock whose dividends are anticipated to grow at 10 percent per year. We've simply taken the NPV for a very long series of dividends, whereas the actual problem in the equation relates to an infinite series of dividends. To do this infiniteseries calculation, we need to resort to some manipulation of the formula.

Note the proviso at the end: In order for the infinite sum on the first line of the formula to have a finite solution, the growth rates of the dividends must be less than the discount rate.

We can fix the technical problem by redefining the formula, as in the following spreadsheet: To calculate the value of the firm's share, we first discount the dividends for years 1—5. Denote the long-term growth rate by g2 in our example this is 8 percent.

As shown in the spreadsheet, the value of the share is estimated at Gordon, who first published this formula in a paper entitled "Dividends, Earnings and Stock Prices," Review of Economics and Statistics 41 May , pp.

The compound growth rate of Abbott's dividends over the period is Applying the Gordon formula gives cells J22 and J23 Abbott's cost of equity as Thus the "correct" growth rate is a judgment call—it depends on your expectations of what the company can and will pay out in dividends in the future.

In this case, the cost of equity would be Based on a more extensive analysis of Abbott, you might decide that the historical rate of Abbott's dividend growth has no relevance for its future dividend growth rate. This is one of the hard decisions that analysts have to make!

By anticipating future sales growth and capital needs for the company, we can perhaps predict the company's future dividend. The CAPM derives the firm's cost of capital from its covariance with the market return.

It is calculated by the following formula: In cell J5 of the spreadsheet fragment in section 2. At this point we outline the application of the model to finding the cost of capital without entering into the theory. The rest of the variability in the Abbott returns can be diversified away by including Abbott's shares in a diversified portfolio of shares. In this section we consider two SML formulations. The difference between these two methods has to do with the way taxes are incorporated into the cost of capital equation.

Here rf is the risk-free rate of return in the economy and E RM is the expected rate of return on the market. The choice of values for the SML parameters is often problematic. A common approach is to choose n rf equal to the risk-free interest rate in the economy for example, the yield on Treasury bills.

The following spreadsheet fragment illustrates this approach. Benninga-Sarig show that the SML has to be adjusted for the marginal corporate tax rate in the economy. Denoting the corporate tax rate by TC, the BenningaSarig tax-adjusted SML is This formula can be applied by an adaptation of the previous approach: n rf is equal to the risk-free interest rate in the economy in this case, the yield on Treasury bills.

For Abbott Labs, the Benninga-Sarig approach gives a slightly lower cost of equity: 2. On the one hand, historic averages are appropriate if we think that the future anticipated rates of return will correspond to the historic average. On the other hand, we may want to take current market data to calculate directly the future anticipated market yield. As Benninga and Sarig show, the Gordon model gives us an approach for doing so.

This formula ties the cost of equity to currently observable market parameters. We now want to calculate the cost of the firm's debt. In principle, this is the marginal cost to the firm before corporate taxes of borrowing an additional dollar. In practice the cost of debt often turns out to be more difficult to calculate than the cost of equity.

There are at least four ways of calculating the firm's cost of debt. We will state them briefly and then go on to illustrate the application of three of the methods to Abbott Labs.

The first two methods are easy to apply and, although they may not be theoretically perfect, they are often used in practice. Although this method is the easiest to use, it confuses past costs with the future anticipated cost of debt that we actually want to measure. If a company is rated A and has mostly medium-term debt, then we can use the average yield on medium-term, A-rated debt as the firm's cost of debt.

Note that this method is somewhat problematic because the yield on a bond is its promised return, whereas the cost of debt is the expected return on a firm's debt.

Since there is usually a risk of default, the promised return is generally higher than the expected return. Both these methods are relatively easy to apply.

In many cases problems or errors that are encountered in these methods are not critical. We can then estimate the firm's cost of debt by using the security market line SML. This approach is, in principle, similar to the process applied to the firm's equity, although—as we will show—the actual application requires many shortcuts and fuzzinesses. This method requires a lot of work and is mathematically nontrivial; we postpone its discussion until Chapter For cost of capital calculations it would be used in practice only if the firm we are analyzing has significant amounts of risky debt.

Thus cost of capital estimation is not a science, it is an art. Users of cost of capital estimates should always do a sensitivity analysis around the numbers calculated.

Given the data on the company you are analyzing, some sloppiness in the cost of capital calculations with its accompanying savings in time may be expedient.

The average maturity of this debt was about five years. At the end of the yield to maturity of five-year AA1 debt was about 5. The second method uses this number as the cost of debt. When we try to apply this formula, things get very complicated: Firms typically have many bond issues, and these issues—if traded at all much corporate debt consists of private placements —are typically traded infrequently. Compared to stock data, bond return data are thus hard to get and may be inaccurate.

The maturity of the debt. ISBN 1. Three Cases 2. Theory and an Initial Example 3. Debt Repayment Schedules 3. Measuring the Cash Produced by the Business 3. Some Accounting Issues 5 6 7 Bank Valuation 5. The Equivalent-Loan Method 6. Calculating the Highest Acceptable Lease Rental 6. A Valuation Example 5. First Federal Savings Bank The 6.

Implementing Propositions 3—5 9. An Example 9. The Capital Market Line 9. Adjusting for Dividends Appendix 2: Excel versus Statistics Exercises Efficient Portfolios without Short Sales Constant Correlation The Single-Index Model How to Bootstrap: Making a Bingo Card in Excel 14 15 Impact of Earnings Announcements on Stock Prices The Importance of the Variance-Covariance Matrix What Does the Market Think?

An Example If you downloadd an e-book, you may obtain a unique access code by emailing digitalproducts-cs mit. Its no-nonsense, hands-on approach makes it an indispensable tool. Downloadable instructor resources available for this title: I've found earlier editions of Simon Benninga's Financial Modeling to be a great reference, and I've used them often.

The fourth edition again offers helpful tips for using Excel in the most efficient and powerful manner to solve finance problems. These tips are illustrated in clear, step-by-step fashion so that the reader can start using them right away. The fourth edition also offers an improved flow of topics within the primary headings of Corporate Finance and Valuation, Portfolio Models, Valuation of Options, Valuing Bonds, and Monte Carlo Methods, along with updated examples and exercises.

Financial Modeling continues to be a valuable resource for practicing finance professionals, students, and professors. Simon Benninga. Roger B. Myerson and Eduardo Zambrano.