In this course, participants will develop an understanding of the intuitive foundations of asset and investment valuation, and how alternative valuation techniques may be used in practice. This is part of a Specialization in corporate finance created in partnership between the University of Melbourne and Bank of New York Mellon (BNY Mellon).
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Defining Attitudes Towards and Alternative Measures of Risk
-This week we will define a statistical measure of stand-alone risk as being the standard deviation of returns. We will describe three alternative attitudes towards risk, settling on risk aversion as being the standard assumption made in financial markets. We will then analyse the impact of combining assets into a portfolio upon both risk and return and then quantify the benefits from diversification by comparing performance against a suitable benchmark.
Linking risk with expected return
-This week we differentiate between systematic and unsystematic risk and explain how the expected returns that are reflected in the prices of assets should be linked to only one type of risk. We illustrate how the Capital Asset Pricing Model might be used to link systematic risk with expected return and then discuss the empirical shortcomings of the model. This leads to a description of more advanced models and we conclude with a review of survey evidence that considers the approach taken by finance mangers of large listed firms in practice.
Using financial statement analysis to measure cost of capital
-This week we will explain the logical underpinnings of the Weighted Average Cost of Capital Formula and show how it might be estimated in practice by a firm. We will also consider the many challenges that might be faced in using this approach to estimating hurdle rates and conclude with a warning about the perverse outcomes that might occur if the technique is used in a haphazard manner.
Addressing financial reality with real options analysis
-This week we describe how standard NPV analysis might lead to incorrect decisions when we fail to account for the impact of (or upon) firm flexibility. We then describe the three most common types of real options that firms face in practice and then explain how decision trees might be used to arrive at an approximation of the value of the real option that is embedded within a project. We conclude by considering empirical evidence on the take-up of real options analysis and discuss the situations in which real options analysis might most be needed.
Paul Kofman and Sean Pinder