Equity Module Lessons

We then introduce the Factor Module.  This module extends the Markowitz/CAPM/Single Index approach adopted in the first module to include multiple factors.  The addition of multiple factors allows for additional sources of systematic risk to be taken into account when designing a portfolio.

The last equity module, the Free Cash Flow to Equity Module, addresses the joint problems of estimating intrinsic value and expected return.  Traditional, application of the Modern Portfolio Theory assumes that the historic return average provides an unbiased estimate of future or expected returns.  In the Free Cash Flow to Equity module the intrinsic value of a stock is assessed.  As a result, when compared to the spot stock price a forecast of expected return can be made. In turn this can be contrasted to historical averages.

This module lets you analyze a historical data set of either prices or returns to identify the efficient set of portfolios.  The efficient set starts from the premise that investors strictly prefer more expected return to less, and strictly prefer less portfolio return volatility (i.e., risk) to more.  That is, they prefer more return and are adverse to risk.  The efficient set of portfolios consists of the set of portfolios that cannot be dominated.  A portfolio cannot be dominated if investors cannot find another portfolio that provides a higher expected return with no more risk, or strictly less risk without giving up expected return.

This module identifies the efficient set of portfolios using historical data.  It goes beyond a traditional Markowitz/CAPM/Single Index Model analysis to provide insight into the dynamic behavior of risk and return over time.  It also permits a variety of back-testing experiments to be conducted that test the realized performance of portfolios being worked with.

The module also lets you estimate betas and construct efficient portfolios directly from beta estimates using the Single Index Model.

This module complements the Portfolio Returns and Efficient Portfolios Module in many ways.  Many empirical studies have strongly questioned the performance of CAPM's beta for explaining observed returns.  For example,  Fama and French demonstrate that factors based on fundamentals, such as firm size and book-to-market ratios, are superior to beta when predicting returns. In the following lessons you will learn about how to integrate these factors into the problem of identifying the efficient set of portfolios.  The module, however, is general and lets you explore using any factors.  A visual display lets you see how well the factors influence the dynamic aspects of risk and return behavior.

This module supplements the previous two modules by automating collecting historical price data into Excel.

This module lets you assess the intrinsic value of any stock by applying either a constant growth or a two stage abnormal growth model to the future free cash flows from the firm.

In addition, given the spot security price it automatically computes the expected return from the assessed intrinsic value.