Sim Simeonov's presentation from Angel Bootcamp 2011 teaches lessons for successful angel investing based on statistical analysis of thousands of angel investments over a twenty year period. For more info, see http://sim.vc/angels

1. Data-Driven Patterns for
Successful Angel Investing
Sim Simeonov
sim@fastignite.com
@simeons

2. Founding. Funding.
Growing. Startups.

3. Have fun
& make $$$

4. 58
%
IRR

5. Cash-on-Cash
3.2x

6. 66% lose money

7. 45% total loss

8. What determines investment success?

9. quality deal flow
picking winners
winning the deal
market environment

10. Can you pick winners?

11. If you can have asymmetric information
most of the time, ignore the advice here

12. quality deal flow
picking winners
winning the deal
market environment

13. investment optionality
dollar cost averaging

14. be a player
investment optionality
dollar cost averaging
play a lot

15. Angel Investment
Returns Analysis
Ingredients Instructions
• Kaufmann angel 1. Clean data
return data set
2. Analyze data set
• Additional data
3. Reverse-engineer
from angels
returns probability
Tools distribution
• Big data kitchen 4. Do Monte Carlo
5. Adjust & repeat #4
for all interesting
questions

16. Two things you don’t
want to see made:
sausage & econometrics

17. The end result, however…

18. 100%
80%
>10x
60% 5-10x
3-5x
40% 2-3x
1-2x
20% <1x
0%
% of % of % of % of
Angels deals $inv $return

19. Monte Carlo results

20. 100%
Portfolio
75% Size Size
Portfolio
P(return > X), %
5
10
25
50%
50
100
25%
0%
0x 2x 4x 6x 8x 10x
Cash-on-Cash Return

21. Why do a few angels get the
lion’s share of returns?

22. Lucky? Smart?

23. Portfolio Size
P(return > X), %
15% 200%
5 10 25 50 100
Portfolio Size
10%
5%
0%
5x 6x 7x 8x 9x 10x
Cash-on-Cash Return

24. Answer: most likely luck

26. 100%
Portfolio
200%
Size Size
Portfolio
P(return>X), %
75% 5
10
25
50
50% 100
25%
0x 1x 2x 3x 4x
Cash-on-Cash Return

28. Does the lean startup movement
benefit angel investors?

29. P(failure) reduced from 60% to 50%
125%
100%
75%
50%
25%
0%
5
10
20
25
50
100
DiffP(x > 1) DiffP(x > 2) DiffP(x > 3)

30. Answer: yes but very active angels
get disproportionate benefits

31. What’s the effect of big bets?

32. 50x vs. 1000x returns cap
80%
60%
40%
20%
0%
5
10
20
25
50
100
DiffP(x > 1) DiffP(x > 2) DiffP(x > 3)

33. 20%
50x cap, 55% fail
vs.
10%
1000x cap, 60% fail
0%
5 10 20 25 50 100
-10%
-20%
DiffP(x > 1) DiffP(x > 2) DiffP(x > 3)

34. Answer: big bets make the most
sense for very active angels

36. Be an active angel.
Benefit from:
- portfolio effects
- lean startup ecosystem
- making big bets

37. Be a selective angel.
Focus on:
- information asymmetry
- low-failure opportunities
- price

38. Econometrician seeks
angel investor data for
discrete long-term
relationship and intense
anything-goes analysis.
Must be clean and BS-free.
http://sim.vc/angels