The underlying structure of the stock market is asymmetrical in nature and structured in such a way that there is more of an upward bias as it is easier to buy a stock than it is to short-sell a stock. This is on purpose and largely due to two factors 1). The fundamental role the stock market is supposed to play in terms of capital formation via IPOs (although most start-ups exit via the private market – private equity uses debt – bit of a misnomer) and 2). Maintaining support for the dollar vis-a-vis finacialization. The higher, more liquid, and less volatile the market, the more companies tend to IPO. Yet, when the sole purpose becomes the management of expectations via repitition to maintain confidence at the expense of fundamentals, it becomes nothing more than a confidence game. If the stock market was structured symmetrically, the ability to buy would be just as easy as it is to sell. Not only is the structure of the market asymmetrical, so is the flow of information.
Information Flows/Sell-Side Catch-22:
The information inherently flows 1). From the companies 2). To the regulators, sell-side/investment banking analysts, industry publications, and/or media outlets 3). To the investment community (buy-side) whom composes large institutions more so compared with individual investors.
Why is this important? It is the large institutional money that moves markets, not individual investors. More importantly, the asymmetries of information place the advantage with the companies. As a result, companies seldom stray from their investor relations slide decks and the forward financials received by the sell-side which are used in their models do not stray far from company guidance in most instances.
Why is this? Because, the sell-side is in a precarious position being an intermediary between the companies and investors. If estimates are too high or too low, sell-side analysts find they are unable to have their questions answered during conference call Q&A’s. Many buy-side analysts bemoan that sell-side analysts are biased offering more Buy-or-Neutral recommendations at the expense of Sell recommendations. Well, you have to take into consideration the asymmetrical structure of the market and the fact that issuing a Sell recommendation typically confers limited access to managment meetings between the company and buy-side whereby the sell-side acts as the liaison. Yet, even in its bemoaning, the buy-side highly values such meetings with management. Therefore, the sell-side finds itself in a Catch-22 between both the companies and buy-side. As a result, the asymmetrical structure of the market and information flows limits the usefulness of the current valuation models. The most common valuation models employed to derive the estimated values are discounted cash flow (DCF) and multiples, typically being used in conjunction.
The Limits of Current Models:
Discounted Cash Flow:
Discounted cash flow models provide greater detail of the inner workings of a company compared with multiples on a standalone basis, which is why the value using multiples is typically derived based off of 1 year DCF estimates (derived from the sell-side which is derived from company guidance as mentioned previously) against historical company and sector multiple averages. However, I think modeling 10 year time horizons for DCF’s is limited because error rates grow exponentially the further out into the future you go. For example, the error rates of future estimates to be included should be cut-off at 10%-20%, yielding success rates of 80%-90%. Additionally, if you could see 10 years into the future, you wouldn’t be at that desk making estimates of what earnings would look like 10 years into the future to begin with. It makes more sense to a utilize 2-3 year time horizon, or 3-5 year time horizon at most with frequent updates (contingent upon the cone-of-uncertainty and maintaining a 80%-90% success rate mentioned previously). Moreover, the differential between an estimated stock price using a 10 year DCF and 5 year DCF is not that meaningful as the bulk the value is in the the terminal value itself. Additionally, DCF’s do not provide much value for early stage companies that are cash flow negative. But, there is a big difference between having a business that is cash flow negative in an early growth stage and a business model that becomes more cash flow negative the more it grows, ahem, WeWork…..which brings me to multiples.
Historical Company and Industry Average Multiples:
To reiterate, discounted cash flow models provide greater detail of the inner workings of a company compared with multiples on a standalone basis, which is why the value using multiples is typically derived based off of 1 year DCF estimates (derived from the sell-side which is derived from company guidance) against historical company and sector multiple averages. All the multiples do is convey a relationship of what things go for in the market relative to a fundamental.
Investors simply form a model of what things go for in the market based on multiples similar to going to a flea market and finding an item that is cheap which you know sells for a higher price in the market, simply arbitraging the price differential between the two. This stylized way of thinking is limited. The dynamics are the same when using a historical or industry average multiples approach.
Historical Company Average Multiples
When looking at a historical company average multiples approach, you simply overlay the business cycle, factors for improved company fundamentals to understand the historical multiple while taking into consideration the Molodovsky Effect. By using an average, you are implicitly breaking that down into a 50/50 scenario whereby with new information you merely switch the weighting to reflect the new estimated price target. It’s important to delineate if performance is consistently above and/or below average, otherwise the valuation will be peristently inflated and/or deflated.
Historical Industry Average Multiples
When looking at a historical industry average multiples approach, you simply overlay the business cycle, factors for improved company fundamentals in relation to historical industry multiples while taking into consideration the Molodovsky Effect. By using an average, you are implicitly breaking that down into a 50/50 scenario whereby with new information you merely switch the weighting to reflect the new estimated price target. It’s important to delineate if performance is consistently above and/or below the industry average, otherwise the valuation will be peristently inflated and/or deflated.
Lastly, it seldom makes sense to compare a company multiple with the market as a whole as a result of the idiosyncratic risk for a individual company coupled with the manner in which the multiples are weighted for the market as a whole.
Key Points Regarding the P/E Ratio:
Considering the manner in which “E” in the P/E ratio can be manipulated upwards, it makes sense to add back those factors that make earnings seem better than they are. It is also important to understand the manner in which the multiples are derived. For example, is the high “P/E” multiple the result of “P” increasing or “E” decreasing. Conversely, is the low “P/E” multiple the result of “P” decreasing or “E” increasing. Distinguishing between those factors is important in conjunction with earnings surprises and modeling of positive reinforcing factors.
Key Points Regarding Clicks and ESG
It is clear that companies are not solely valued in the markets based on their ability to generate earnings based on 1. Tech companies that are valued by clicks or 2. Environmental, Social, and Corporate Governance (ESG). In both instances, the only reason stocks can maintain value based on clicks or ESG is due to conditioning. Despite those similarities, the two approaches yield vastly different outcomes. Eventually, a company based solely on clicks will fail. However, ESG offers a set of criteria that allows stocks to maintain and/or increase in value based on a set of parameters without undue influence nor at the expense of earnings.
Please refer to the following report on investor expectations and arbitrage: Investors Make Investments with the Expectation to Make Money – Otherwise they Wouldn’t Make the Investment in the First Place https://internationalcapitalmarkets.org/2019/09/11/all-investors-make-investments-with-the-expectation-to-make-money-otherwise-they-wouldnt-make-the-investment-in-the-first-place/