Expectations investing (by Alfred Rappaport and Michael J. Mauboussin)

• Investment is basically about predicting current value of a future stream of cash better than the market.
• The key to successful investing is to estimate the expectations embedded in the current stock price and then to assess the likelihood of a revision in expectations (that will drive the price).
• Use current price (and its history) to estimate what the market expects in terms of earnings and growth. Identify likely revisions of expectations in the future:
  • Use DCF model to reverse current price and earnings into a future trajectory.
  • What possible revision drivers do we see, what is their likely direction.
  • Buy / sell / hold, based on expectations with a margin of safety.

• DCF model (based on FCF discounted at the cost of capital):
  • Sales growth, Operating profit margin -> Operating profit
  • Operating profit - Tax (<- tax rate) -> Net operating profit after tax
  • NOPAT - reinvestment -> Free cash flow
  • FCF discounted at cost of capital -> Corporate value
  • CV + non-operating assets - debt -> Shareholder value (if there's stock options compensation plan, subtract that too, see appendix to ch. 5).
  • Residual value: NOPAT / Cost of capital (assumes NOPAT is constant). This simplifies thinking about far future. Can also calculate residual value for constant slow growth (as NOPAT / (COC - growth rate)).

• Expectation revisions:
  • Value triggers: sales, operating costs, investments.
  • Value factors: volume, price and mix, operating leverage (wider margins as initial investment is recovered), economies of scale (cheaper production at scale), cost efficiencies (cutting costs, optimizing the process), investment efficiencies (more of similar investment can have more/less impact).
  • Dependency graph:
    • Sales -> Volume, Price and mix, operating leverage, economies of scale.
    • Volume, Price and mix -> Sales growth rate.
    • Operating costs -> cost efficiencies.
    • Price and mix, operating leverage, economies of scale, cost efficiencies -> operating profit margin.
    • Investments -> Investment efficiencies -> Incremental investment rate.
  • With this infrastructure in place we can analyze impact of each possible change.
  • Revision causes:
    • Volume: industry growth, market share.
    • Price and mix: price changes, mix changes.
    • Op leverage: preproduction costs, position in investment cycle.
    • Economies of scale: purchasing, production, distribution, learning curve.
    • Cost efficiencies: proces change, technology, outsourcing.
    • Investment efficiencies: technology, facilities reconfiguration, working-capital management.
  • Frameworks:
    • Five forces: industries, esp. cap-intensive:
      • Barriers to entry,
      • Substitution threat,
      • Buyer power,
      • Supplier power,
      • Rivalry among firms.
    • Value chain analysis: business activities, esp. in vertically-integrated companies and activities succeptible to technological change:
      • Customer priorities,
      • Distribution channels,
      • Offering (appropriate products and services),
      • Input / raw materials,
      • Assets / core competency.
    • Disruptive technology: innovation, esp. in technology rich business, market leading companies:
    • Information rules: information economics, esp. with high up-front and low incremental cost, network effects, lock-in:
      • Giveaways (to build user base),
      • Link-and-leverage (transfer user base to an additional product),
      • Adaptation (next big thing instead of optimizing this one).

• How to estimate price-implied expectations:
  • DCF, go forward with growth until the tail can be reasonably estimated with residual formula.
  • Look for significant value triggers (see above).
  • Analyze possibe changes to those triggers, their probabilities and impacts. Calculate expected value. See if there's enough error margin.
• Beyond DCF:
  • Real options (e.g. expanding the business) can apply Black-Scholes formula.
    • Mostly applies to visionary companies with market leadership e.g. Amazon is a good example.
  • Financing fast growth for young companies requires high stock price, i.e. the market must believe in it.

• Business categories:
  • Physical: tangible assets are important.
  • Serice: people are important.
  • Knowledge: people and IP.
• Mergers and acquisitions:
  • Costs: integrating the new business.
  • Benefits: synergies.
  • You can observe the market reaction to confirm your hypotheses. Also if you disagree with the market, this can create greater opportunities.
• Share buybacks: good if the stock is undervalued and there's no better investment of cash. Otherwise not so good, especially if used to engineer the report numbers.
  • The best way to assess share buybacks is as a capital allocation / investment decision.