Monte Carlo Simulation: SEIS and EIS Investor Return

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I had a few spare hours this week to build a Monte Carlo model to predict SEIS and EIS returns for investors. As input, I used data from Beauhurst plus common “investor wisdom”.

Exit Data

Beauhurst “Exits in the UK. Acquisitions and IPO 2011-2020”. I used the data from the report to create a table making sure that the distribution (and positive skewness) is similar to the Beahurst Data. To adjust for inflation, I increased the exit values by 25%. I fully expect people to question this percentage. ?Some say we are in a bull market that will continue others expect mean reversion.

SEIS input

An often-quoted statistic is that 70% of the investments in start-ups will fail to create a return, 20% will be good investments and 10% are the star performers. For a SEIS investment I translated this into the following input:

Complete failure (Mean 50%, SD 5%). Complete failure means a SEIS adjusted return of -27.5%

Negative IRR (Mean 20%, SD 5%). Normally distributed between 0 and – 27.5%

Good investment versus Star performer (Mean 65%, SD 8%)

For a good investment, I use a multiple on valuation (Mean 6, SD 2).

For a star performer, I used the Beahurst exit Data

Time to exit (Mean 5 years, SD 1.25 years). This is probably a bit lower than expected but I wanted to consider other liquidity events like dividends. Not all SEIS investments are large Tech exits.

Average Investment (Mean ￡75.000, SD ￡12.500)

Ownership % (Mean 23%, SD 3.8%)

I struggled with dilution. Dilution is very likely but how much is difficult to estimate. I can’t recall ever seeing historic data. I used the following input.

Average Dilution (Mean 38%, SD 6%)

I used XIRR to calculate IRR. For valuation purposes, I adjusted the valuation upon investment by 50%.

Model run: 10.0000

EIS input

I assume that EIS investments are less risky and quicker to Exit than SEIS investments but have a higher valuation.

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Complete failure (Mean 35%, SD 5%). Complete failure means a SEIS adjusted return of -38.5%

Negative IRR (Mean 15%, SD 5%). Normally distributed between 0 and – 38.5%

Good investment versus Star performer (Mean 45%, SD 3%)

For a good investment, I use a multiple on valuation (Mean 3.5, SD 0.75).

For a star performer, I used the Beahurst exit Data

Time to exit (Mean 4 years, SD 1 year)

Average Investment (Mean ￡450.000, SD ￡150.000)

Ownership % (Mean 25%, SD 2.5%)

Average Dilution (Mean 25%, SD 8%)

I used XIRR to calculate IRR. For valuation purposes, I adjusted the valuation upon investment by 30%.

Model run: 10.0000

Results SEIS

Expected IRR +/- 15%

Average valuation: +/-￡350K

Results EIS

Expected IRR +/- 12%

Average valuation

+/-￡ 1.7 mln

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I expected the returns to be a bit higher (15%-20%). Besides that, the results are not that surprising. SEIS returns are riskier but higher. EIS is less risky but with a slightly lower return. Compared to other asset classes the return/risk profile is (very) high.

Notes

-?????????This is not an in-depth project. Just a bit of fun pairing existing Exit Data with "Investor Wisdom" in a Monte Carlo model.

-?????????I don’t believe Angel investment is an efficient market. An investor can find/create Alpha. Having said that: Beta and randomness are key IRR drivers. A portfolio approach is recommended.

-?????????If as an investor your valuation paid is significantly higher than the average you expect to create/find more Alpha, have faster exit times, and/or expect a significant increase in Exit prices versus historic 2011-2020 prices.

-?????????“Compound interest is the most powerful force in the universe”. The difference between a 12% IRR and a 15% IRR is a lot bigger than you think it is. Time to liquidity is very important

-?????????Changes in the input have a big impact on the outcome. The dilution factor is a bit of a stab in the dark. If your assumptions are different from my assumptions the outcome will be very different.?Just make sure your assumptions are grounded and possibly based on historic data.

-?????????If I find better data and/or other Monte Carlo models I might recalculate/change the model but otherwise this is a one-time fun project.

-?????????A low-value, non-sexy investment with a dividend stream can easily create an IRR that is higher than the big, heavily diluted, highly-priced tech exit.

-?????????Excuses for the jargon. I did not want to spend ages writing the article.

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