# Quest for a correct intrinsic value for Standard & Poors 500 – december 2020

## Why

A very simplistic assumption on ‘Retire Early’ and investing in index funds is to have an average index return of 7% annually (or more). Then simulations of the past (only on the US stock market!) show that you can take out 4% of your portfolio each year, and still have a growing portfolio.

This logic requires an assumed ** average **return of you index fund of 7%. Financial Independent Folks consider this as a given for any market situation, just because they state that you never know the right moment to start or to invest. But as you can easily find out yourself by looking at the past is that if you start in an expensive market, you get far less than 7% annually: a meagre 0.1% annual return (average for the next 10 years after a start in an expensive market). And just as well, if you start in a cheap market, you get more than 7%: a royal 13.8% annual return. See here.

So… to be sure if the 4% will hold in the future, it is essential to make an assumption on where we are today. Fair, cheap, expensive market?

## December 2020

This is basically an update to previous posts on the same topic:

- Market valuation – December 2018: see here
- Expected annual returns: see here
- And the validity of the 4% rule: see here

Today there are signs of an extremely overheated, speculative market: take a look at how stocks like Tesla have exploded in price. You may like Tesla, but there is no way to justify a share price equal to 22 times sales. For the fans: Tesla’s growth is good but a 15% annual sales growth also does not justify the share price.

Other signs are the enormous speculation with CALL options (Put/Call ratio today is at a level of february 2000), the large leverage applied by many small investors, the doubling of IPO prices on the first day of trading (and subsequent meltdown…).

I wanted something more substantial, more numerical justified than just ‘signs’ of an overheated stock market. So I tried to calculate the intrinsic value of the SP500. There are simplified rules of thumb to do this. A well known example is the ‘Buffett yardstick’ of Buffett Indicator: the total value of the stock market against the overall size of the economy. It is calculated by dividing the stock market cap by gross domestic product (GDP). See here.

Another simple indicator is the Shiller CAPE index.

But what if you try to valuate each of the companies of an index? For instance, the Standard & Poors 500 index? There are approximately 500 stocks in there, that would be a lot of work, but it is a weighted index: the largest market caps are heavily overweighed, smaller companies have a very small weight. The top – 40 companies already constitute 50% of the index. Let’s continue with the Top – 40.

## Better approach

So, I have made an Excel with a Discounted Free CashFlow (DFCF) calculation for each of these 40 stocks, representing 50 % of the index. The input for each calculation is:

- the expected average growth rate of the company (‘s cash flows) for the next 10 years

- the discounting factor (using classic investment theory, based on the WACC) for each stock

- the current Free Cash Flow.

The calculation gives me a DFCF for each of the 40 stocks.

Symbol | Weight | Price | DFCF | DFCF/Price | Growth % | Discounting % |

AAPL | 6,94 | 137 | 68 | 49% | 3 | 8,0 |

MSFT | 5,40 | 225 | 174 | 77% | 9 | 7,8 |

AMZN | 4,45 | 3312 | 1929 | 58% | 12 | 8,0 |

FB | 2,11 | 278 | 233 | 84% | 8 | 8,0 |

GOOGL | 1,69 | 1763 | 1859 | 105% | 10 | 8,0 |

GOOG | 1,64 | 1764 | 1860 | 105% | 10 | 8,0 |

TSLA | 1,60 | 661 | 153 | 23% | 20 | 9,0 |

BRK,B | 1,41 | 229,8 | 245 | 107% | 2 | 6,7 |

JNJ | 1,28 | 154 | 154 | 100% | 2 | 6,4 |

JPM | 1,21 | 125 | 195 | 156% | 2 | 6,0 |

V | 1,15 | 214 | 76 | 36% | 4 | 8,1 |

PG | 1,09 | 139 | 147 | 106% | 3 | 6,0 |

UNH | 1,04 | 347 | 508 | 146% | 5 | 6,3 |

NVDA | 1,01 | 518 | 159 | 31% | 10 | 10,0 |

MA | 0,96 | 345 | 129 | 37% | 4 | 8,0 |

HD | 0,92 | 267 | 212 | 80% | 6 | 9,0 |

DIS | 0,91 | 176 | 62 | 35% | 2 | 8,3 |

PYPL | 0,88 | 233 | 128 | 55% | 13 | 9,0 |

VZ | 0,78 | 59 | 114 | 194% | 1 | 6,0 |

ADBE | 0,76 | 452 | 270 | 60% | 12 | 9,0 |

CMCSA | 0,74 | 51 | 74 | 145% | 4 | 6,7 |

NFLX | 0,73 | 531 | 84 | 16% | 12 | 8,2 |

BAC | 0,73 | 30 | 109 | 363% | 2 | 6,4 |

INTC | 0,70 | 47 | 140 | 297% | 6 | 6,3 |

WMT | 0,69 | 144 | 266 | 185% | 2 | 4,7 |

T | 0,68 | 29,7 | 116 | 391% | 0 | 4,9 |

MRK | 0,68 | 81,5 | 157 | 193% | 4 | 4,9 |

KO | 0,66 | 54 | 55 | 102% | 1 | 5,3 |

CRM | 0,66 | 222 | 117 | 53% | 11 | 9,0 |

PEP | 0,66 | 147 | 187 | 127% | 2 | 5,4 |

PFE | 0,65 | 37 | 64 | 172% | 2 | 6,0 |

ABT | 0,63 | 108 | 42 | 39% | 1 | 7,7 |

TMO | 0,62 | 464 | 251 | 54% | 7 | 8,0 |

CSCO | 0,60 | 45 | 82 | 183% | 7 | 8,0 |

ABBV | 0,58 | 105 | 693 | 660% | 14 | 6,0 |

NKE | 0,57 | 141 | 26 | 18% | 2 | 7,5 |

XOM | 0,56 | 41,6 | 17 | 41% | -5 | 8,0 |

AVGO | 0,55 | 429 | 654 | 153% | 8 | 7,9 |

QCOM | 0,53 | 148 | 87 | 59% | 8 | 9,0 |

ACN | 0,52 | 258 | 225 | 87% | 7 | 8,5 |

The weighted over- or undervaluation of the 40 stocks can then be compared with the weighted current number for the S&P 500.

Weight % | DFCF / Price | Growth | Discounting | |

Average or Total | 50 | 99% | 7 | 7.6 |

Just to be sure, I did the same thing using the ‘intrinsic value’ given by my data source provider for each stock. With this result:

Weight % | DFCF / Price | Growth | Discounting | |

Average or Total | 50 | 78 % | 7 | 7.6 |

## Important remarks

- A straightforward FCF calculation is still a rough measure, if you do not take
**company or sector specifics**into account. For instance; Netflix is hugely overpriced by this measure, but you should take assets like its series ownership, growth perspective, market dominance etc into account. However, in the list of 40 stocks these ‘company specifics’ will cause both over- and undervaluations, and I take the simple assumption that these will somewhat average out against each other. - The advantage of this straightforward mathematical calculation is that you are
**more objective**and use only the numbers and facts. Compared to eg. the stock target price given by analysts, which are more subjective. Analysts mix their targets with emotional, commercial, personal and market influences and opinions. - The calculation is heavily dependent on the discounting factor. You would think that this is an objective and exact number, but it is not. As an example, the WACC for Apple is 11.05 % because the cost of equity is high; but it would obviously be irrational to use that as a discounting factor. If Apple would want to massively apply debt, the WACC would go to 3% and their intrinsic value would triple.
- Growth rate is another difficult number. See my post on Cisco. Growth of Cisco went from an assumed 40% annually to zero % within a year. The stock price dropped 85% as a consequence. I have tried to put a fair number on growth, assuming both what a company accomplished in the past, but also what could be maintained during the next 10 years in the future.

## Market level conclusion

Method | S&P 500 today 29.dec.2020 | Intrinsic / Price | Correct S&P 500 |

Intrinsic Value based on Free Cash Flow | 3735 | 99% | 3688 |

Intrinsic Value Data Feed | 3735 | 78% | 2926 |

Depending on method 1 or 2, we are expensive (22%) or we are almost at the correct level. This is somewhat surprising to me, I thought we would be extremely expensive. Reasons (for a more justifiable high market) are:

- extremely
**low interest**levels, which imply a low discounting factor. Which also carries a risk: if rates would go up, the index would go down big way - the
**top-7**of the S&P 500 are**high growth**stocks. And they are likely to keep growing fast. I do not see the end of decent growth for Amazon, Tesla, Microsoft, Google,.. These heavyweights count for 23% of the S&P 500, and their growth is 10% annually! This obviously also has a risk: if the growth decreases, these stocks will suffer badly - There are also sectors which are
**undervalued**: for instance banks, or telecoms. These counterbalance for the overpriced stocks.