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Angel Investing

Angel Investing · Chapter 1 of 4

How much of my wealth can go into startups?

The rule travels by word of mouth: do not put more than 5% to 10% into startups. Almost no one knows how to apply it, because the second half of the sentence is missing. 5% to 10% of what?

Of annual income, the amount repeats every year and exceeds any prudent limit. Of total wealth, the apartment you live in enters the calculation. The defensible base is investable financial wealth, once the emergency reserve has been set aside.

Program ceiling = (investable financial wealth − emergency reserve) × 5% to 10%

The second mistake is treating the ceiling as a limit per check. Whoever respects the percentage and puts it all into one company has followed the rule and broken what actually protects them: diversification. The ceiling applies to the whole program, over years.

An example, not a prescription. Investable wealth of R$ 2 million, a reserve of R$ 200,000 and a 7% band give a ceiling of R$ 126,000. With 30% kept aside to follow on in the companies that prove themselves, R$ 88,000 remains for the first checks. Across twelve companies, the average check is close to R$ 7,000. That number, not the R$ 126,000, is the one to keep in mind when the first round comes along.

The question stops being “do I like this company?” and becomes “does this company deserve one of my twelve slots?”.

In the full program

The three buckets of wealth, the five prerequisites before the first check, the six entry traps and the Allocation Calculator, which delivers the first page of your personal investment policy.

Educational material. It does not recommend an allocation for any particular person; percentages and examples are references, not prescriptions.

Angel Investing · Chapter 2 of 4

Why does almost all of the return come from one or two companies?

“Angel investing returns so much a year” is a sentence that circulates with varying numbers and almost never with a source. The average exists. The problem is that almost no angel gets the average.

The reference study, by Wiltbank and Boeker, followed angels organized in groups in the United States, with more than a thousand recorded exits. Three facts coexist in the sample. The average multiple was around 2.6 times capital. Slightly more than half of the exits returned less than was invested. And about 7% of the exits accounted for roughly three quarters of all the return. The pattern has a name: power law.

Hence the practical question: how many companies does a portfolio need to probably contain a winner? Suppose, purely as a teaching hypothesis, that each company has a 5% chance of being a big winner.

CHANCE OF AT LEAST ONE WINNER IN THE PORTFOLIO

3 companies: about 14%
10 companies: about 40%
20 companies: about 64%
30 companies: about 79%

And how much does the winner need to deliver? Ten checks of R$ 10,000. Six companies close and return zero; three return the capital. For the portfolio to double, the tenth needs to return R$ 170,000: 17 times the check.

The selection question changes. It stops being “will this company work out?” and becomes “if it works out very well, will it return my whole portfolio?”. The second question eliminates many good companies, and that is what it is meant to do.

In the full program

Why the mean and the median diverge and what that says about the typical angel, the six traps of the math, among them selling the winner too early, and the Portfolio Simulator, to test the number of companies and the distribution of outcomes without promising any of them.

Educational material. It does not recommend an allocation for any particular person; percentages and examples are references, not prescriptions.

Angel Investing · Chapter 3 of 4

Which signals make an experienced angel walk away from a round?

Every early-stage company has problems. Whoever turns down a deal at any signal invests in nothing. The experienced angel does something else: separates what ends the conversation from what becomes a condition.

The rule fits in one line. What depends on money and time can be fixed. What depends on character, or on a right already lost, cannot be fixed with a check.

SIGNALS THAT END IT, WHATEVER THE REST

Integrity. Numbers that do not match the documents; debt, liabilities or a partner left out.
Structure. A cap table that does not add up; founders already below 50% at pre-seed or seed.
Ownership. Code, brand or main asset that does not belong to the company.
Commitment. Lead founder part-time, with no date to go full-time.

The rest is the majority, and becomes a condition with a date and proof: the hire missing from the team, the metric the round needs to move, the anchor customer contract still to be signed, the pending formality.

Medium signals weigh together. “The round closes Friday and I am only talking to you” adds up haste and exclusivity: it takes away the time for diligence and isolates the investor. A legitimate round has a deadline and accepts verification.

Most bad decisions do not come from a lack of information. They come from ignored information: the signal was in the diligence, and the angel invested because “the rest was good”. Written on paper, next to the signal, the sentence loses its force.

In the full program

The five sets of signals that weigh together, the investment memo in eleven parts, with a dated hypothesis and a pre-mortem, and the four decision disciplines, among them how to say no without closing the door.

Educational material. It does not recommend an allocation for any particular person; percentages and examples are references, not prescriptions.

Angel Investing · Chapter 4 of 4

Why do smart investors join bad rounds?

“Everyone is getting in, and the round closes Friday.” The sentence is designed to keep you from thinking.

Angel investing is ideal ground for errors of judgment: little information, a lot of uncertainty, charismatic founders, short deadlines, investors who influence one another. And the outcome of each decision only shows up years later, mixed with luck.

THE FIVE MOST COSTLY BIASES

Fear of missing out. Deciding out of haste, or because others got in.
Anchoring. Taking the proposed valuation as the starting point and adjusting little.
Sunk cost. Letting the money already invested decide the next check.
Halo effect. The brilliant founder hides the market or the cash position.
Confirmation. Doing diligence only in search of reasons to invest.

No one thinks they are biased. Whoever invested out of fear of missing out remembers the decision as conviction. Whoever doubled down on the company that was sinking remembers it as loyalty. Memory rewrites decisions so that they make sense.

That is why bias is not corrected by willpower. Knowing what anchoring is does not stop anyone from anchoring. What stops it is a step in the process: your own deadline to decide, a night between the analysis and the decision, the reasons written down before the investment.

And the yardstick changes. A well-made decision can go wrong through bad luck; a poorly made one can go right through good luck. What can be controlled is the process.

In the full program

The discipline that counters each bias, the Decision Journal, with the eight fields of each entry, and the annual review, which separates bad luck from pattern and turns each pattern into a new rule.

Educational material. It does not recommend an allocation for any particular person; percentages and examples are references, not prescriptions.

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