Key take aways from Exit Strategies for Entrepreneurs and Angel Investors

Early Exits
Early Exits

Key advice for Startups and emerging companies

  • Start small
  • Stay lean
  • Raise only the funding you really need and grow judiciously.
  • Alignment from all parties on exit strategy is extremely important
  • Best time to sell a company is when the future has never looked brighter

On VCs

  • Interest of VCs might not be aligned with interest of founders and angel investors
  • VCs need to satisfy the needs of their LPs
    • Need their successful companies to generate a minimum of 10-30X return for their fund to perform respectably, taking into account overall failure rates
    • They thus need to wait longer to exit and work their investments harder.
    • They are ok to accelerate the growth of their investments with their capital or blow it up quick for a capital right off. The latter helps minimize management overheads.
    • They will block a sale if the return multiples do not meet their expectation
  • VC return multiples of term sheet valuation
    • Series A – 10X return
    • Series B – 4-7X returns
    • SEries C – 2-4X returns
  • VC funds have been getting bigger overtime. The need to deploy their capital forces them to seek for opportunities where likelihoods are slim.
  • Companies with VC money tend to exit at year 16 on the average

On Angels

  • Invest much less money than VCs
    • USD10,000 to USD250,000
  • Happy to exit in a few years with a 3-5X return
  • In the 50s and 60s
  • prior successful entrepreneurs or senior executives
  • allocate around 5-10% for angel investing
  • has experience and inclination to be great mentors and valuable directors
  • Companies with angel only money tend to exit at year 4 on the average

Drivers of acquisition

  • trend has been dramatic shift towards earlier exits
  • huge amounts of cash on balance sheets of large corporation
  • growth in Private equity and buy out funds

Insights on Growth

  • The first USD10 to USD20 million valuation are the easiest and less challenge on the skills of the CEO
    • It is easy for young companies to maintain year on year compound annual growth rates of 100% or even 200%
  • Knowledge of how hard it is to be a CEO and lots of money in the bank is usually a huge deterrent for serial entrepreneurship.
  • VCs replace CEOs of 75% of companies within 18 months of their initial investments
    • Founder’s shares get trapped in an illiquid private company for another 5-10 years
  • Use a 2 year time horizon
    • year 1 develop technology
    • year 2 develop distribution

On valuation

  • A lot of factors that have the biggest impact on a company’s short term value fluctuation will be out of management’s control
  • The factors will also be unforeseen
  • General valuation multiples
    • SAAS companies are typically valued at 3-4 RR
    • Service body shops 0.5 of per staff revenue or PE ratio of 3-4

On sales process

  • Typically 4-5 months
  • CEOs must focus on the business to ensure metrics are at their best during the sales to maximize valuation
    • can add up to 10-20% more valuation
  • Until the very last phase of the sales, it is best to delegate the sales process to a professional
    • Business broker or M&A advisor – use them as the bad guy
      • big firms shoot for exit above USD100million
        • 2-3% of final value
      • boutique firms shoot for USD20-70 million
        • 4-6% of final exit value

Related references

  • Evolution and revolution as organizations grow, Larry Greiner Harvard Business School
  • Raising money: The canadian guide to successful business financing, Douglas Gray and Brian Nattrass
  • High Anxiety or Great Expectations, Bart Schachter and George Hoyem, Venture Capital Journal

Insights from party at Ilya’s place

  • The successful investor is not very different from an investigative journalist or a crime detective
  • Most useful data are public.
  • The only difference between the successful investor and a mediocre one is the amount of work he is willing to dedicate towards validating all the key assumptions.
  • Investment relationships team of all public companies are very willing and helpful with providing information.
  • More qualitative data can be obtained by calling up customers or ex-employees of competitors
  • Once you are able to reconstruct a company’s business model, you will be able to predict generally whether a company will make or miss earnings
  • Legacy technology companies tend to have a longer half life than expected. The key is to determine how much longer the half life is and if there are legal protections that will extend it.
  • Beyond the core functionality, it is important to go into the realms of human psychology (adrenaline and dopamine) to figure out the defensible strategy
  • Smaller funds are structured to incentivize playing to win (1%-2% carry) while bigger funds are structured to incentivize playing not to lose (expecting only returns matching LIBOR rate of 2.5%) . The difference in mind set results in very different strategies.

Related References

MongoDB versus Amazon

  • A scenario of company versus company
  • On 9th Jan 2019, Amazon announced the launch of DocumentDB a direct competitor to MongoDB
  • Key areas used to assess potential impact of new entrant
    • If incumbent’s distribution channel was in anyway disrupted by new entrants
    • If solution has sufficient lock in cost
    • Market segment differentiation through analysis of product features
  • Short term: Loss aversion, reversion to mean scenario
    • Market reacted by falling 17%
    • Market recovered in 14 days

Related references

Key insights for Jerry’s birthday party

On web scraping

  • There is only a total of 180 million registered domains in the world
  • There is a total of 120 billion web pages in the world
  • .IO is the most popular top level domain right now in the world
  • make sure to buy up “CompanyEntity” domain as they tend to get a lot of traffic
  • Similarities comparison
    • pull out words on website’s about us page and comparing with other website’s about us page
    • reduce total number of dimensional space to compute similarities – sample space 500,000 word
    • K-Means as opposed to Cosine similarities is a cheaper approach
    • still need humans to tag specific data sets
  • Detecting structure in page
    • find the tables and row
    • extract the values within the column, check if is
      • place
      • person
      • address
    • tag all the rest of the content on the page as the same entity
  • Approaches
    • pure machine – inaccurate
    • pure human – not-scalable
    • set process to mix of machine and human for optimal configuration
  • On Distill Networks/Bots blocking
    • this company utilizes machine learning to detect for bots
    • currently only 10 of 1000 fortune 1000 companies are using their service
    • fat tail companies will have the resource and motivation to protect their publicly available data
    • long tail companies will have neither the resource nor motivation to protect their publicly available data

On enterprise sales

  • It takes 5 years to pass through the trough of sorrows after the initial hype. Enterprise companies come to trust you after you have been around long enough
  • Most enterprise companies do not have the capacity to plough through the volume of automated sales leads generated even if they want to. The main bottleneck is their sales team
  • Enterprise companies are willing to pay really high margins
  • Sample concepts
    • – used by hedge fund managers to track how well a software has gain traction amongst users based on javascript snippet

On Social networks

  • Facebook uses collaborative filtering
  • Most lucrative advertising audience are still North America Whites
  • African demographic don’t spend much which makes them really bad advertising targets but are really loyal users once acquired
  • African demographic drive much of the music and culture
  • To ensure optimize monetization spend as well as server resource, could use Facebook page like condition to filter for more lucrative demographics
  • Short video is the trend now
    • SnapChat is considered messaging than video
    • Instagram is in the space
    • Tic Tak is in the space
    • Differentiation is a challenge in this space
  • iMessage is the largest competitor of Facebook Messenger. The former spans across East and West.

On Venture Capital

  • Founders might potentially get blocked from selling company by investors past trough of sorrow stage (typically 5 years in)
  • Founders might want to exit while investors need to get their return multiples (4x minimal)
  • Investors might seek to replace CEO to bring in a growth/scaling CEO as opposed to a product centric CEO

On Mobile gaming

  • Each games has a life span of 5-6years
  • In app purchases is the main driver of revenue
  • Failure rate is very high
  • Assuming 4 experimental teams, the operations typically generates one successful mobile game per year.


  • Jerry
  • Perry
  • Yi

Insights from Hannes

Three critical conditions for any projects to work

  1. If the technology will work
  2. If there is an actual applicable use case
  3. If we can build a viable business model

Once these three conditions are met, it then makes sense to double down on investment and scale the projects rapidly.

Insights from conversations with Ilya

The market is a representation of leveraged corporate earnings around the world.

Leverage occurs in two forms.  Firstly, through corporate debts take on by companies in expectation of increased future corporate returns. Secondly, through borrows taken on by potential shareholders in expectation of appreciation in equity value due to expectation of future corporate returns.

Corporate returns are driven mainly by productivity. Productivity is a function of technology. Technology advancement is a function of innovation. The market will inevitably increase in size in the long run so long as technology advancement and innovation continues to persist.

Cyclical Boomz and Busts are the results of interplays between market participants and central banks (via fiscal policies and regulations) in reaction to prevailing leverage levels in the market.

Market capitalization in 2008 dropped by a total of 50%. Using this as a proxy, we can assume the effect of leverage is approximately 50% of the market capitalization.

Beware that the market can stay irrational longer than you can stay liquid.

Reflections for the evening on return on capital

Having ample resources and financing at the onset of a project promotes wastefulness financial habits which quickly becomes part of the culture if not managed properly. Being under-resourced during the initial onset of a project forces project leaders to be scrappy and judicious in the use of resources that are made available to them. This promotes thriftiness which quickly becomes part of the culture. Such a culture has the by-product of maximizing return on capital when more becomes available.

Ray Dalio: Beating the stock market by learning history

  • History inevitably repeats itself
  • If a trend is occurring that you don’t have a good idea of how it will pan out, it is more likely because you have not lived in a time where a similar situation had happened before and less likely because a similar situation had happened before
  • Application of FinTech is to make it possible to leverage on assets that we have like the following:
    • Human Capital
    • Social Capital
    • Real Assets
  • An economy built on talent versus an economy built on natural resources and tourism tends to grow faster
    • Singapore versus Jamaica
      • important to educate local population to ensure they do not become second class citizens in their own country to highly qualified expats
    • Three Kingdoms – Cao Cao versus Yuan Shao
  • Algorithms for decision making
    • Be wary of purely deriving algorithms through data mining and regression analysis.
      • The user of this algorithm will not be able to decipher causation versus correlation
      • The training data available might be missing existing significant events
    • The algorithm should instead be a derivation of your own thought processes. Computers/algorithms should be used to complement human decision making instead of replacing it.
  • An environment of radical transparency is helpful towards supporting idea meritocracy
    • helps match individuals strong in one area with other individuals strong in complementary areas.
    • A real world ensemble decision tree model
  • On China
    • Main challenges the country face
      • Debt restructuring
      • Economic restructuring – the need to shift away from export focused economy to domestic focused economy
      • Develop capital markets
      • Balance of payments
    • Developments to date
      • debt being restructured
      • economic restructuring happening dealing with state owned enterprises. Fast development of cutting edge industries. AI advancements comparable to US
      • capital markets like Hong Kong depth of liquidity is impressive
      • balance of payment is being dealt with effectively due to capable leaders and ability to control via levers unique to a strong central government
      • Strong emphasis on kids education
      • Reinforcing Integrity of law through eliminating corruption

Forum – Ten years after Lehman brother’s bankruptcy: where are we now and what lies ahead


  • Michael Hutchison, UC Santa Cruz
  • Darrell Duffie, Stanford University
  • Barry Eichengreen, UC Berkeley
  • Mark Levonian, Promontory Financial Group

next sources of financial risks

  • highlights
    • China’s corporate debt build up
    • FinTech disintermediating traditional bankers and removing central bank fiscal levers


  • cyber disintermediation
    • hackers screwing around with bank account records
    • corporate borrowers went away back in 2008. Banks forced to find riskier customers
    • new technologies are taking away a lot of the lending business
    • new technology
      • new payment systems
      • digital currencies – Singapore, Canada and China
    • cloud provider concentration – Fintech everything on cloud
  • US regulation backsliding risk
    • management of federal government
    • stress test rules
    • reduction of 100-200 billion capital in US
      • capital and liquidity
    • liquidity was the main trigger of the melt down
    • Dodd Frank bill
  • sovereign funds risk: Turkey is 3-4X of Greece economy
  • china corporate debt risk as its financial system becomes more integrated with the rest of the world
    • check for excessive short term borrowing
    • plenty of shadow banking in China growing rampantly
  • institutional funds risk
    • banking system is still concentrated in top 5
    • US absorbed 85% of low cost homes through Fanny Mae mortgages
      • quicken is the largest mortgage generator
  • largest banks in the world are all mainly Chinese versus Japanese back 10 years ago
  • 2008 melt down
    • caused by incompetent regulation rather than wrongful act of financial people.
      • Prosecution is setup to go after cases they would likely win
      • complexity of financial system
      • complexity of corporate structure
      • complexity versus usefulness of market actual needs
  • populist risk: under funded pension fund. Because of really low risk rates
  • financial consumers
    • not a priority versus banks
    • Dodd Frank act
    • consumer financial protection bureau
    • growth rate of structured notes?
  • trade war
    • economic consequences was very limited
    • Brexit effect took 4 quarters to show up


  • Volatility: is good if is driven by transparency
  • leading indicators of financial crisis
    • credit spreads
    • credit to GDP
    • rapid growth of housing credit signals impending recession
    • contracts imposed on borrowers – reduced conditions are signs of excessive borrowing
    • credit growth
      • Debt to GDP
      • corporate debt growth in China
    • dump truck index – real estate boom
    • number of cranes visible in urban skyline
  • blockchains (mainly used for security keeping)
    • Bank of America mellow – backup in blockchain
    • securities – T+2 in block chain