1. Introduction

Introduction to Valuation

Philosophical basis for valuation

  • A postulate of sound investing is that an investor does not pay more for an asset than its worth.
  • Consequently, perceptions of value have to be backed up by reality, which implies that the price paid for any asset should reflect the cashflows that it is expected to generate.

Generalities about Valuation

1. Since valuation models are quantitative, valuation is objective

  • the inputs leave plenty of room for subjective judgments. Thus, the final value that we obtain from these models is colored by the bias that we bring into the process.
  • There are two ways of reducing the bias in the process.
    • The first is to avoid taking strong public positions on the value of a firm before the valuation is complete.
    • The second is to minimize the stake we have in whether the firm is under or over valued, prior to the valuation.
  • When using a valuation done by a third party, the biases of the analyst(s) doing the valuation should be considered before decisions are made on its basis.

2. well-researched and well-done valuation is timeless

  • the value will change as new information is revealed. Given the constant flow of information into financial markets, a valuation done on a firm ages quickly, and has to be updated to reflect current information

3. A good valuation provides a precise estimate of value

  • It is unrealistic to expect or demand absolute certainty in valuation, since cash flows and discount rates are estimated with error. This also means that you have to give yourself a reasonable margin for error in making recommendations on the basis of valuations.

4. The more quantitative a model, the better the valuation

  • As models become more complex, the number of inputs needed to value a firm increases, bringing with it the potential for input errors.
  • The first is the principle of parsimony, which essentially states that you do not use more inputs than you absolutely need to value an asset.
  • The second is that the there is a trade off between the benefits of building in more detail and the estimation costs (and error) with providing the detail.
  • The third is that the models don’t value companies: you do.

5. To make money on valuation, you have to assume that markets are inefficient

  • it is not clear how markets would become efficient in the first place, if investors did not attempt to find under and over valued stocks and trade on these valuations.
    • First, if something looks too good to be true – a stock looks obviously under valued or over valued – it is probably not true.
    • Second, when the value from an analysis is significantly different from the market price, we start off with the presumption that the market is correct and we have to convince ourselves that this is not the case before we conclude that something is over or under valued.

6. The product of valuation (i.e., the value) is what matters; The process of valuation is not important.

  • The process can tell us a great deal about the determinants of value and help us answer some fundamental questions -- What is the appropriate price to pay for high growth? What is a brand name worth? How important is it to improve returns on projects? What is the effect of profit margins on value?