#### What returns might a founder friendly venture capital fund generate?

*Written by **Eisaiah Engel** on December 28, 2018.*

The book, *Grays Sports Almanac for Venture Capital*, proposes that a venture fund could combine optionality with the Founder Friendly Standard to travel in time, purchasing equity in companies at early day prices after their investment cases become robust.

This Microsoft Excel Model (uses macros), called GSAVC Fund Simulator. Version 1G 2018-12-28.xlsm, is a step towards a financial model for such a fund. Six independently simulated variables drive the outcome of each iteration in the simulation.

This model differs from the fund in the book in the following two ways:

- Modeled on a Y Combinator SAFE valuation cap, no discount rather than a warrant as the SAFE agreement provides more principal protection and, thanks to the valuation cap, behaves similarly to a warrant.
- Invests a fixed $1,000 each time and is missing the main feature of the warrants described in the book: that the fund would have the right to buy more equity after investment cases are more robust. (You might be able to do this with the optional Y Combinator SAFE pro-rata side letter, as long as the companies develop significant customer traction before their Series A funding rounds.)

We made the above tradeoffs so we could invest uniform amounts of $1,000 using the widely known SAFE agreement. The macrofund in this model is made up of microfunds that share 50% of their portfolios. To make the model as conservative as possible, portfolio company valuations do not go above $1B.

This document contains a list of definitions for the terms used in GSAVC Fund Simulator version 1G for *Grays Sports Almanac for Venture Capital*.

Field color legend:

- Blue are fields you can edit.
- Green are controlled by the macro simulation.
- Black are calculated with formulas.

### Number of businesses that start each year in the USA

This is a count of the new businesses that start in the United States that have 1+ employees: 552,000.

…anywhere from 125 to 250 companies per year that are founded in the United States (out of roughly 552,000 new employer firms that open each year) reach $100 million in revenues in a reasonable timeframe.

Source: Kedrosky, P. (2013). The Constant: Companies That Matter. [ebook] Kansas City, MO: Ewing Marion Kauffman Foundation, p.5. Available at: https://www.kauffman.org/what-we-do/research/2013/05/the- constant-companies-that-matter [Accessed 14 May 2018].

### Fundable businesses

This is a count of how many businesses in the USA are funded each year. The model assumes we purchase SAFE notes in companies that are fundable: 60,000 companies (the higher number in David S. Rose’s estimate below). This number narrows down the odds by assuming that Liquidity Scenarios 1, 2, and 3 only happen within this pool of 60,000 and that we will only invest in companies within this pool of 60,000.

In very general terms, in the US roughly 1,500 startups get funded by venture capitalists, and 50,000 by angel investors. VCs look at around 400 companies for every one in which they invest; angels look at 40… Looked at that way, of the 50,000-60,000 deals that get funded each year 30,000 of them should not have been funded (let alone the other few million who wanted funding)…so therefore there no really great people with really great ideas who go unfunded.

Source: Rose, David S. “How Many Start-Ups in the US Get Seed/VC Funding per Year?”Quora, 21 Apr. 2012, www.quora.com/How-many-start-ups-in-the-US-get-seed-VC-funding-per-year.

### Liquidity Scenarios

This is a collection of the four different valuation scenarios we model at the moment of liquidity.

#### Liquidity Scenario 1 – Achieves 100M+ in yearly revenue

Divide 552,000 new US employer firms by 250 and 125 respectively to find the lower bounds of 2,208 and the upper bounds of 4,416 in the odds calculation.

…anywhere from 125 to 250 companies per year that are founded in the United States (out of roughly 552,000 new employer firms that open each year) reach $100 million in revenues in a reasonable timeframe.

Source: Kedrosky, P. (2013). The Constant: Companies That Matter. [ebook] Kansas City, MO: Ewing Marion Kauffman Foundation, p.5. Available at: https://www.kauffman.org/what-we-do/research/2013/05/the- constant-companies-that-matter [Accessed 14 May 2018].

#### Liquidity Scenario 2 – Achieves “High-Growth Company” status

To find the “1 in X Businesses that start” number used in the model, divide 100,000 by each metro area’s High-Growth Density metric. This is done on this spreadsheet and the data on the spreadsheet was taken from the metro area rankings of the *Kauffman Index of Growth Entrepreneurship*.

High-Growth Company Density represents the prevalence of fast-growing private companies that have at least $2 million in annual revenue and 20 percent annualized growth over a three-year period, which compounds to 72.8 percent after the three years.

For example, if the High-Growth Company Density for a metropolitan area were 306.7, it would mean that for every 100,000 employer businesses in that metro area, there were 306.7 high-growth firms.

Source: Morelix, Arnobio, and Josh Russell-Fritch.2017 Kauffman Index of Growth Entrepreneurship.Ewing Marion Kauffman Foundation, pp. 10 www.kauffman.org/kauffman-index/reporting/-/media/e37f4200462347dbb0d385e01e656be2.ashx.

Using the example above, Washington DC has a High-Growth Company Density value of 306.7 in 100,000 companies or 1 out of every 326 companies. The top cities in the 90th percentile are Washington DC, Austin, Atlanta, Columbus, and Nashville. Check out the odds for each city here.

#### Liquidity Scenario 3 – Returns capital

We model capital being returned 25% of the time (often less than the full amount of principal invested):

About three-quarters of venture-backed firms in the U.S. don’t return investors’ capital, according to recent research by Shikhar Ghosh, a senior lecturer at Harvard Business School.

Source: Gage, Deborah. “The Venture Capital Secret: 3 Out of 4 Start-Ups Fail.” The Wall Street Journal, 20 Sept. 2012, www.wsj.com/articles/SB10000872396390443720204578004980476429190.

#### Liquidity Scenario 4 – Loses all value

This is a catch-all category that returns $0 in capital back.

### Calculating the SAFE agreement terms

A collection of the inputs and calculations used to fill in the blanks in the SAFE agreement.

#### Founders’ last full-time salaries

The model assumes that the company has no assets that can be used as collateral. To establish a value for the company, we start with the sum of all the founders’ last-known salaries when they had jobs (salary or contract labor). This is simulated as a linear variable between $50,000 and $250,000. These are the recommended minimum and maximum inputs when investing.

#### Last 12 months gross sales

Then, we add up the last 12 months of gross sales. Because we are using gross sales and not accounting for discounts, returns, or cost of goods sold, there is a cap of $500,000. This is simulated as a linear variable between $0 and $500,000.

#### Multiple to establish post-money valuation cap for SAFE round

Then, we multiply by 2X the sum of the Founders’ last full-time salaries and the Last 12 months gross sales to establish a post-money valuation cap.

#### Post-Money Valuation Cap for SAFE Round

The term Post Money Valuation Cap comes from the Y Combinator SAFE agreement. It’s used to determine the valuation of the company, which determines how many shares of stock the SAFE note can convert into (referred to as SAFE Preferred Stock).

The Post-Money Valuation Cap is ‘post’ all of the safe money. It is NOT also ‘post’ the Equity Financing (e.g. Series A) money.

Source: Levy, Carolyn. “Y Combinator – QUICK START GUIDE – Post-Money SAFE.” San Francisco, Sept. 2018. Page 4. https://www.ycombinator.com/docs/Post Money Safe User Guide.pdf

#### Company Capitalization

This is like the term ‘fully diluted shares outstanding.’ The Y Combinator SAFE agreement has its own custom term for fully diluted shares outstanding (below). Our model assumes that it’s fixed at 10M shares in all scenarios.

Company Capitalization is calculated as of immediately prior to the Equity Financing and (without double-counting):

* Includes all shares of Capital Stock issued and outstanding;

Source: Levy, Carolyn. “SAFE (Simple Agreement for Future Equity) – Valuation Cap, No Discount.” San Francisco, Sept. 2018. http://www.ycombinator.com/docs/Postmoney%20Safe%20-%20Valuation%20Cap%20-%20v1.0.docx

* Includes all Converting Securities;

* Includes all (i) issued and outstanding Options and (ii) Promised Options;

* Includes the Unissued Option Pool; and

* Excludes, notwithstanding the foregoing, any increases to the Unissued Option Pool (except to the extent necessary to cover Promised Options that exceed the Unissued Option Pool) in connection with the Equity Financing.

#### SAFE Price

This establishes the price per share at which the SAFE agreement can convert into equity.

SAFE Price means the price per share equal to the Post-Money Valuation Cap divided by the Company Capitalization.

Source: Levy, Carolyn. “SAFE (Simple Agreement for Future Equity) – Valuation Cap, No Discount.” San Francisco, Sept. 2018. http://www.ycombinator.com/docs/Postmoney%20Safe%20-%20Valuation%20Cap%20-%20v1.0.docx

#### SAFE Preferred stock

These are the total number of shares that this SAFE agreement can convert into.

SAFE Preferred Stock means the shares of the series of Preferred Stock issued to the Investor in an Equity Financing, having the identical rights, privileges, preferences and restrictions as the shares of Standard Preferred Stock, other than with respect to: (i) the per share liquidation preference and the initial conversion price for purposes of price-based anti-dilution protection, which will equal the Safe Price; and (ii) the basis for any dividend rights, which will be based on the Safe Price.

Source: Levy, Carolyn. “SAFE (Simple Agreement for Future Equity) – Valuation Cap, No Discount.” San Francisco, Sept. 2018. http://www.ycombinator.com/docs/Postmoney%20Safe%20-%20Valuation%20Cap%20-%20v1.0.docx

#### Purchase Amount

This is the total amount that the investor pays to buy the SAFE. This is fixed at $1K in all scenarios in our model.

THIS CERTIFIES THAT in exchange for the payment by [Investor Name] (the “Investor”) of $[_____________] (the “Purchase Amount”) on or about [Date of SAFE]…

Source: Levy, Carolyn. “SAFE (Simple Agreement for Future Equity) – Valuation Cap, No Discount.” San Francisco, Sept. 2018. http://www.ycombinator.com/docs/Postmoney%20Safe%20-%20Valuation%20Cap%20-%20v1.0.docx

### Minimum liquidity valuation

This number determines how much the company is worth at the time of Investment. This is a random variable that is normally distributed with the mean at the Post-Money Valuation Cap for the SAFE round and standard deviation of 20%.

## Valuation outcomes

The model simulates these valuation scenarios.

### Valuation multiple of revenue

This is used when Column C has a value of True, which happens when liquidity scenarios 1 or 2 are chosen. A RevMultiple will be chosen from the Percentile, ReveMultiple, Revenue, and Age table. The source of this data is this table, which was derived from this data.

This is a simulated random variable that is distributed with the probabilities from Liquidity Scenario 2.

### Liquidity Scenario 1 – Achieves 100M+ in yearly revenue

If the model choses scenario 1, the revenue is a constant $100M, even though the Kedrosky research says it can be more than $100M. The $100M will be multiplied by the Valuation multiple of revenue to establish a valuation.

### Liquidity Scenario 2 – Achieves “High Growth Company” status

If the model choses scenario 2, it mixes and matches the RevMultiple, Revenue, and Age from this table. Although these numbers are visualized together in rows, the model chooses RevMultiple and Revenue separately. For example, the model can choose a multiple of 5x and revenue of $3,000,000. The age is always associated with the revenue number in the table below.

Percentile | RevMultiple | Revenue | Age |

0% | 1.0 x | 1,000,000 | 1 Year |

10% | 1.2 x | 3,000,000 | 1 Year |

25% | 1.3 x | 5,000,000 | 2 Years |

50% | 1.9 x | 10,000,000 | 5 Years |

75% | 2.4 x | 26,000,000 | 10 Years |

90% | 3.0 x | 65,000,000 | 16 Years |

100% | 5.0 x | 100,000,000 | 16 Years |

Source: Combination of Tables 1, 2, and 3 from this spreadsheet.

### Liquidity Scenario 3 – Returns capital

If the model choses scenario 3, the Minimum Liquidity Valuation is chosen.

### Liquidity Probability – randomly generated

This is a simulated variable distributed based on odds defined in Liquidity Scenarios above.

### Valuation at Liquidity

This field is a copy of the valuation in the chosen Liquidity scenario.

### Timing – No of Years to Liquidity

If the model chooses Liquidity Scenario is 1 or 2, then the number of years is chosen from the age field in the Percentile, RevMultiple, Revenue, and Age table. This is always associated with the revenue field from the table in the link above. If the Liquidity Scenario is 3, then this value is three years.

### SAFE cash flow

This collection of fields calculates the return generated by the SAFE note.

#### Company Share Price

This is the company’s valuation divided by the total number of shares outstanding (always assumed to be 10M shares).

#### Total payout (assumes no dividends)

This is the company’s share price multiplied by the SAFE Preferred Stock.

#### Capital Gain or loss

This is the difference of the Total payout minus the Purchase Amount for the SAFE.

*Limit of Liability/Disclaimer of Warranty: **Eisaiah Engel (“the author”) is not providing any financial, economic, legal, accounting, or tax advice or recommendations in this post. The author is not a lawyer. The information contained in this post was prepared for general information purposes only, does not constitute research, advice, or a recommendation from the author to the reader and is not a substitute for personalized financial or legal advice. Neither the author nor any of his affiliates make any representation or warranty as to the accuracy or completeness of the statements contained in this post. The author and his affiliates expressly disclaim any liability (including any direct, indirect, or consequential loss or damages) for all posts and their content.*