THE DIRECT D E T E R M I N A T I O N of RISK-ADJUSTED DISCOUNT RATES and LIABILITY BETA
RUSSELL E. BINGHAM T H E H A R T F O R D FINANCIAL SERVICES G R O U P
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Subject Abstract 1. Summary 2. Total Return Model 3. After-Tax Discounting 4. Derivation of Risk-Adjusted Discount Rate and Liability Beta Figure l : Baseline Risk / Return Line vs Leverage 5. Liability Beta Figure 2: Equity vs Liability Beta Figure 3: Equity Beta vs Risk-Adjusted Discount Rate (After-Tax) 6. Underwriting Profit Margin Figure 4: Underwriting Profit Margin vs Loss Payout Figure 5: Underwriting Profit Margin vs Investment Yield Figure 6: Underwriting Profit Margin vs Market Risk Premium Figure
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Secondly, the importance of using after-tax discount rates and the
equivalency of net present value rates of return and internal rates of return that follow as a consequence is reviewed, again discussed in detail in [1], [2] and [3]. This foundation provides the critical model structure and valuation framework from which risk-adjusted discount rates and liability beta can be determined.
An important principle is introduced - that being that the risk-adjusted total rate of return must equal the risk-free rate. This fundamental principle provides a stepping stone from which a direct estimate of the liability beta becomes possible within the total return framework. Liability betas are shown in The
relationship to the total return to shareholders and the linkage with equity betas demonstrated.
sensitivity of the underwriting profit margin to variations in loss payout, investment yield, market risk premium and leverage is demonstrated and discussed.
Liability betas cannot be directly measured, and Cummins [6] and Fairley [9] presented approaches to estimate them. Kozik [10] discussed the many problematic aspects of CAPM and liability beta theory, demonstrating why any estimate of liability beta is likely to be subject to much debate. It is important to keep in mind, however, that the development of a liability beta is a secondary objective to that of determining the appropriate risk-adjusted discount, rate. This paper proposes a shift in focus
1. Which firms are the “identical twins” of the Collinsville investment? Using the β’s for those assets and the methodology learned in this course, determines the appropriate discount rate for the Collinsville investment.
Week 1 – Introduction – Financial Accounting (Review) Week 2 – Financial Markets and Net Present Value Week 3 – Present Value Concepts Week 4 – Bond Valuation and Term Structure Theory Week 5 – Valuation of Stocks Week 6 – Risk and Return – Problem Set #1 Due Week 7* – Midterm (Tuesday*) Week 8 - Portfolio Theory Week 9 – Capital Asset Pricing Model Week 10 – Arbitrage Pricing Theory Week 11 – Operation and Efficiency of Capital Markets Week 12 – Course Review – Problem Set #2 Due
The formula is: βA=DD+EβD+ED+EβE. From Exhibit 4, we find discount brokerage companies less relied on debt. Thus βD’s effect is small and we assume βD = 0. Here we use the current Debt/Value, since market value is more accurate.
magnitude of these risks, this paper advocates for a more proactive solution. Active investing in
Cernauskas, D., & Tarantino, A. (2011). Essentials of Risk Management in Finance. Hoboken: John Wiley & Sons, Inc.
The learning objectives for students in this course are: (l) improve your understanding of financial securities and markets, (2) develop the ability to analyze investment companies, common stocks, and bonds for investment decisions, (3) understand how options are
This essay will highlight the use of Capital asset pricing model ( CAPM ) to be considered as a pricing theory model for assets . CAPM model helps investors to analyse the risk and what expectation to keep from an investment (Banz , 1981) . There are two types of risk
The risk premium is equal to the difference between the risk-free rate and the expected market return. The case study provides two historical equity risk premiums; the geometric and arithmetic mean. The conventional wisdom is that the geometric mean is considered a better estimate for valuation over long periods, while the arithmetic mean a better estimate for valuation over shorter periods. To coincide with the choice of the 20yr yield on U.S. Treasuries, the geometric mean was therefore chosen for this analysis i.e. (Rm-Rf) = 5.9%
To find the asset Beta (βa), we need to find the weighted average β of equity and the weighted average β of debt. We consider the β of debt to be 0, as debt has no relationship with market risk and it is evident from the balance sheet that Ameritrade had no interest bearing debt in 1997[1].
The success of the model is attributed to Yale’s ability to combine both quantitative analysis (mean-variance analysis) with market judgments to structure its portfolio. In addition, Yale also uses statistical analysis to actively test their models with factors affecting the market, therefore understanding the sensitivity of their portfolio in response to various market changes. Yale also follows and forecasts the cash flow of private equity and real assets in its portfolio to decide the need for hedging.
“The IRR rule is redundant as an investment criterion because the net present value (NPV) rule always dominates it.”
For estimation of betas, the above equation was run for the period from Jan, 2003 to Dec, 2006. Based on the estimated betas we have divided the sample of 63 stocks into 10 portfolios each comprising of 6 stocks except portfolio no.1, 5 and 10 having seven stocks each. The first portfolio 1 has the 7 lowest beta stocks and the last portfolio 10 has the 7 highest beta stocks. The rationale for forming portfolios is to reduce measurement error in the betas.
Bodie, Z., Kane, A., & Marcus, A. J. (2008). Essentials of Investments. (7th ed.) McGraw-Hill. New York.
As indicated by the case study S&P 500 index was use as a measure of the total return for the stock market. Our standard deviation of the total return was used as a one measure of the risk of an individual stock. Also betas for individual stocks are determined by simple linear regression. The variables were: total return for the stock as the dependent variable and independent variable is the total return for the stock. Since the descriptive statistics were a lot, only the necessary data was selected (below table.)
Even though there are flaws in the CAPM for empirical study, the approach of the linearity of expected return and risk is readily relevant. As Fama & French (2004:20) stated “… Markowitz’s portfolio model … is nevertheless a theoretical tour de force.” It could be seen that the study of this paper may possibly justify Fama & French’s study that stated the CAPM is insufficient in interpreting the expected return with respect to risk. This is due to the failure of considering the other market factors that would affect the stock price.