In Part 1 we looked at at the historical returns of dollar cost averaging.

In Part 2 we compared dollar cost averaging with lump sum investing.

In this final part, we will look at the effect of market timing on both dollar cost averaging and lump sum investing. We’ll look at investment starting points during the 10 year low points, 10 year high points, and 10 year midway points.

Our goal is to try to see if it’s worth trying to time the market? Although many would say any attempt is futile at best.

Investing at Lows

Since 1920 there’s been ten points in time that were decade lows. Below are the results if you started Dollar Cost Averaging starting then.

The average 15 year return was 9% IRR.

And what if you did a lump sum investment at the lows?

Results are similar — 9% IRR.

Investing at Midway points

For dollar cost averaging:

And Lump sum:

Again fairly similar results, with lump sum having a slight edge with 10% vs 9% average 15 year IRR.

Investing at High points

For dollar cost averaging:

Lump sum:

Here we see that dollar cost averaging has a slight advantage of 10% vs 8% average 15 year IRRs.

Summary

So what do the three studies suggest?

1. Dollar cost averaging has been a very effective investment strategy.
2. Stick with a long term view. Five year negative returns can become quite favorable, with perhaps the exception of the 1920s.
3. Deciding between a lump sum investment and dollar cost averaging? History shows that there isn’t much difference between dollar cost strategy and lump sum investing. But human psychology may differ. How will you react to a 30% drop if you’ve invested all your capital? For those, you may wish to go with a dollar cost averaging strategy so it seems like you’re actually doing something vs sitting and waiting it out.

Dollar Cost Averaging & Market Timing — Part 3 was originally published in Mostly Business on Medium, where people are continuing the conversation by highlighting and responding to this story.

In Part 1 (Historical returns of Dollar Cost Averaging) of the dollar cost averaging study we looked at 5, 10 and 15 year returns of a dollar cost averaging investment study in the S&P 500 index with start dates from every year since 1920.

I now set out to do a study of the results to see how a lump sum investment would have done historically if one were to have invested a lump sum at different starting in each month beginning in 1920.

This would be for a scenario where someone gets a lump sum amount of cash, think for example inheritance, proceeds from a house, a sale of a business, etc.

I then recorded the 5 year, 10 year and 15 year returns for each starting year.

Results

Full spreadsheet of results

Histogram of Returns

Best 5 Year Return since 1990

Invested in December 1994:

• 5 Year Returns: 28%
• 10 Year Returns: 12%
• 15 Year Returns: 8%

Worst 5 Year Return since 1990

Invested in March 2004:

• 5 Year Returns: -6%
• 10 Year Returns: 7%
• 15 Year Returns: 8%

Best 10 Year Return since 1990

Invested in September 1990:

• 5 Year Returns: 16%
• 10 Year Returns: 19%
• 15 Year Returns: 12%

Worst 10 Year Return since 1990

Invested in March 1999:

• 5 Year Returns: -1%
• 10 Year Returns: -4%
• 15 Year Returns: 4%

Best 15 Year Return since 1990

Invested in November 1990:

• 5 Year Returns: 17%
• 10 Year Returns: 18%
• 15 Year Returns: 12%

Worst 15 Year Return since 1990

Invested in September 2000:

• 5 Year Returns: -2%
• 10 Year Returns: -1%
• 15 Year Returns: 4%

IRR Difference — Lump Sum vs Dollar Cost Averaging

Summary

The average returns of a lump sum strategy vs a dollar cost strategy are very similar.

What’s surprising is the chances of a 15 year period with a loss is slightly less with lump sum investing (0.1% vs 1.3% for dollar cost averaging).

Ignoring the averages, the data also shows that 45% of the time lump sum investment would have slightly worst results, the corollary of which is that 55% of the time lump sum investment would result in better returns. So it’s really close to coin toss of which strategy performs better.

Another interesting fact is that maximum drop in 5 years resulted in a -17% IRR in lump sum vs -31% IRR under dollar-cost strategy. These happened when investing in 9/1/1929 and 6/1/1927 respectively. Looking at the data since, the maximum drop in 5 years were -6% IRR in lump sum, vs -6% in a dollar-cost strategy, both of which resulted in respectable 15 year IRRs of 8%.

So whatever strategy you pick you need to be able to stomach a possible short term loss. So once again a horizon of 10 to 15 years is critical.

Next post

In the next post, we’ll look at how market timing might have made a difference in both strategies by looking at investing at decade highs, lows and averages.

Lump Sum vs Dollar Cost Averaging — Part 2 was originally published in Mostly Business on Medium, where people are continuing the conversation by highlighting and responding to this story.

Read enough about investing and you’ll undoubtedly come across the strategy of Dollar Cost Average. The strategy is simple: divide the total sum you wish to invest into the market into equal parts and invest in the market at regular intervals.

I set out to do a study of the results to see how the strategy would have done historically if one were to have started investing a set sum over the course of three years with different starting in each month beginning in 1920.

For example, assume you had $108,000 to be invested over three years in the sum of $3,000 a month in the SP500. The study looks to see what if you started investing in Jan of 1920 until Dec of 1922? Or Feb 1920 until Jan of 1922? How does that compare if say you started investing in March of 1921 until Feb of 1923? And so on.

I then recorded the 5 year, 10 year and 15 year returns for each starting month.

Results

Full spreadsheet of results

Histogram of Returns

Best 5 Year Return since 1990

Start investing in April 1994:

• 5 Year Returns: 29%
• 10 Year Returns: 10%
• 15 Year Returns: 5%

Worst 5 Year Return since 1990

Start investing in March 2004:

• 5 Year Returns: -11%
• 10 Year Returns: 7%
• 15 Year Returns: 8%

Best 10 Year Return since 1990

Start investing in Jan 1990:

• 5 Year Returns: 10%
• 10 Year Returns: 20%
• 15 Year Returns: 11%

Worst 10 Year Return since 1990

Start investing in March 1999:

• 5 Year Returns: -2%
• 10 Year Returns: -4%
• 15 Year Returns: 5%

Best 15 Year Return since 1990

Start investing in May 1992:

• 5 Year Returns: 21%
• 10 Year Returns: 13%
• 15 Year Returns: 11%

Worst 15 Year Return since 1990

Start investing in November 1997:

• 5 Year Returns: -7%
• 10 Year Returns: 4%
• 15 Year Returns: 3%

Summary

Like most investment strategy, dollar cost averaging is a long term game. Short term 5 year results fluctuate but the longer term 10 or 15 year returns are positive with a high probability of getting a return over 7%.

Next post

Lump Sum vs Dollar Cost Averaging): a comparison of Dollar Cost Averaging vs investing in one big chunk.

Historical returns of Dollar Cost Averaging — Part 1 was originally published in Mostly Business on Medium, where people are continuing the conversation by highlighting and responding to this story.

There’s been a lot of talk about United States billionaires recently, mostly about their money, taxes and giving — should they be taxed differently? and how? Are they philanthropic enough? And so on.

I was interested in something else — how did they acquire their wealth?

Billionaires in US

1. ~600 billionaires in the United States [Forbes, Bloomberg]
2. 43 new additions in 2018 [Forbes]

Macro Stats

• How did they become a billionaire?

• For those that founded companies: what was the industry?

• For those that got through Investment, what types?

New Billionaires in 2018

• How did the 2018 additions become a billionaire?

• For those that founded companies: what was the industry?

Anything Surprising?

A few items stood out to me:

VCs

• There were only 9 venture capitals on the list. They generally got billions because they were smart (or lucky?) enough to have invested early on very large winner, like Google or Facebook.
• The list: John Doerr (Kleiner Perkins w/ Google), Douglas Leone (Sequoia Capital w/ Google), Mark Stevens (Sequoia Capital w/ Google), Ken Langone (w/ Home Depot), Michael Moritz (Sequoia Capital w/ Google), Jim Breyer (Accel w/ Facebook), Peter Thiel (w/ Facebook), Kavitark Ram Shriram (w/ Google), Chris Sacca (Lowercase Capital w/ Twitter, Uber).

Inheritance

• The percentage of inherited is much higher than I had expected, especially for newly minted billionaires which was 36%.
• How should inheritance play into the policy decisions being made regarding taxes and inheritance?

The [United] State[s] of Billionaires was originally published in Mostly Business on Medium, where people are continuing the conversation by highlighting and responding to this story.

I was in the email marketing industry for over 13 years as the founder of StreamSend (founded in 2004, acquired 2017) — I saw, first hand, a story of David vs Goliath.

I have a lot of respect for Ben Chestnut, Dan Kurzius and the MailChimp team (founded in 2001). Ben and I had similar origin stories — immigrant parents, SMB exposure, email marketing coming out of consulting. So how could I not have admiration and respect? They used creativity, and lateral thinking, to not only kick our rear ends, but they also managed to get a public company delisted!

Once upon on a time….

In 2006 Constant Contact had $28M in revenues. [*] Mailchimp had a fraction of those revenues, low single digit millions by my estimate.

After many years they managed to surpass the long time dominant player: Constant Contact (founded in 1995).

Today, MailChimp is the dominant company in SMB email marketing (and moving into a broader category of marketing) — having revenues of $700M and continuing to grow at~15% annually [*]. They never raised a round of capital.

Constant Contact has revenues of $410M in 2018, up 2% from 2017. [*]

If we rewind the clock we’ll see a very different world, one where Constant Contact was a dominant force.

How did this change of fortunes happen? Wouldn’t one expect by all accounts that such a large, well funded incumbent should still rule supreme?

I researched this piece to better understand the Strategic moves that helped MailChimp succeed by using Hamilton Helmer’s 7 Powers framework. [*]

Strategic Power Law Decisions

Did MailChimp execute well? Yes. Is that the sole reason for their success? No. I believe many other players executed just as well.

MailChimp, however, made several strategic decisions, well over ten years ago, that set them on their path of dominance. These decisions, because of their impact, were power-law decisions, or what I would call Power Moves.

A little history

Here is a bit of a history of both companies, followed by a graph from Google Trends. It’s easy to spot the impact of the Power Moves.

ConstantContact:

• Founded in 1995
• Revenues of $8M in 2004
• Revenues of $28M in 2006
• IPO in 2007
• Revenues of $129M in 2009
• Delisted by Endurance in 2015
• Revenues of $410M in 2018

MailChimp:

• Founded in 2001
• Releases API in 2008
• Develops Idea for Freemium in 2008 [*]
• Launches Freemium in 2009
• Creates Integrations in 2009
• Creates Project Omnivore (for abuse) in 2010 [*, *, *]
• Launches $1m Integrations fund in 2010 [*, *]
• Revenues to be $700M in 2019

Power Moves

There are two high level strategic decisions, combined, that led to super growth and sustaining Power for Mailchimp: 1) The Freemium decision, and 2) Integrations.

Freemium

The Freemium decision provided Counter Positioning for MailChimp vis a vis Constant Contact. Constant Contact’s main segment and source of revenues was from customers paying $30 a month for 2,500 email contacts. MailChimp started offering free service to customers in this tier in 2009, thereby rendering Constant Contact helpless.

It would be interesting to see the Constant Contact executive team’s reaction. Just imagine: you’re running the meeting, you have $129M and you’ve heard that this little company comes out with a free offering targeted to your segment. What would you do?

How could Constant Contact respond? Well, they don’t respond, nor did they really have any good options.

They could try to create their own free tier? Well if they did, what would happen to their revenues? Their business would decline. Why would management want to even consider that — just think about the impact on stock price and their personal compensation! There’s a major agency problem — the incentive to respond in kind at the time is not there.

One could imagine the meeting going something like this: “Free email marketing plan? Ha. Silly. These Chimp guys are going to really get it, it’ll never work, and imagine how much spam they have to deal with. Let’s grab lunch.”

I personally remember seeing MailChimp’s announcement and my reaction was two fold: 1) I was very uncomfortable. I knew viscerally this was something significant, but not sure why, nor that it was a Power Move; 2) I immediately wondered: “how much energy and time would they have to exert on battling abuse?”

Spam and Abuse

The reputation of the email sending company is paramount when it comes to email marketing. For context: when an email is sent, it comes from an IP address that is owned by the provider, say MailChimp. The quality of content, and email addresses from one customer can either positively or negatively affect all other customers. One sender with email content that is spam, can cause legitimate emails sent by other senders to go to spam as well.

So providers are very careful to make sure that that “spam” is not sent from their platforms, else the reputation of the platform and IP addresses will suffer. Providers generally have a deliverability and abuse department that monitors, reviews, warns, and helps senders. Mostly people powered.

MailChimp decided to offer a free plan for up to 2,000 contacts. That’s enough of a list size to be a spammer’s paradise. A flock spammers did.

Enter Omnivore

I suspect all competitors large and small saw the Free idea, did some back of the envelope calculations and decided that they would not be able to profitably manage the abuse. They would need to staff an army of abuse staff.

As Ben said:

“The number of users shot up 240 percent to 290,000 within seven months. Emails sent soared from 200 million a month to 450 million. Spammers flocked to the free service, and abuse-related issues grew 354 percent. The staff to deal with abuse would have risen to 800 percent if not for technology.” [*]

That’s 8x more staff… if you had a help desk of 5 people (costing say $400K), you’d then need 40 people (costing $3.2M). That’s insane.

How did MailChimp do it?

They developed a tool called Omnivore.

They ran through 61 trillion data points which ultimately created software, called Omnivore (launched in 2010), that would send warnings, suspend and shutdown accounts. Omnivore made the unit economics work.

With Omnivore, Counter Positioning was complete.

Counter Positioning: Freemium Benefits & Barrier

Barrier

• Other small competitors couldn’t easily replicate the freemium at scale without developing their own Omnivore. It was a tough enough challenge that I’m not aware that anyone really tried. Part of the reason is the data problem — there needs to be sufficient data points to analyze. So a company would have to have been brave enough to first launch free, manage abuses manually, get data and then build their Omnivore. The proposition of opening the flood gates, not being able to handle the volume of spammers, then getting blocked by the ISPs was surely scary.

Benefits

• Low cost to acquire customers. Many decided to try Mailchimp, and quickly grew out of the 2,000 contact limit, then upgraded their plans.
• Exposure led to MailChimp becoming the de facto email marketing provider for SMB focused partners. Which leads us to the next topic: Integrations.

Integrations

Ben’s advice for founders:

“…integrate with some great companies with open APIs, and use their popularity to grow your own customer base. Then, before you know it, new companies will start integrating with you to leverage your customer base.” [*]

By 2008, MailChimp had developed an API and started creating a few integrations. Although back then the idea of having API’s and integrations wasn’t as common place as it is today, I wouldn’t consider it a Power Move. What came next though, was.

The API, and some Integrations were launched in 2008. Freemium came in 2009. Freemium brought an explosion of users, and an explosion in revenues. The Takeoff phase had begun and with it the start of Scale Economies. Mailchimp all of a sudden got an influx of profits to spend and instead of a traditional approach, they spent it using some creative, lateral thinking: they created a $1m Integrations Fund. [*, *]

“Got an idea that could integrate with MailChimp’s delivery platform? Let us fund it.”

“We’d offer them a few thousand dollars to fund their integration, and tell them that if customers like it, we’d promote it more.”

MailChimp would pay a company to build an integration, and they’d promote it if their users seemed to like it (and we’re talking 300K users at the time). A great value proposition to other SaaS companies.

The amount of the fund was $1M, was a large fixed cost, but nominal on a per user basis for fast growing MailChimp. It was however, a sum too large for most other competitors, besides Constant Contact, to match.

As for Constant Contact, they seemingly were unknowingly Counter Positioned and grossly underestimating the circumstances.

From Scale to Network Effects

What started as a Scale Economies led to Indirect Network Effects. The $1M fund was only possible because of MailChimp’s size and scale. Then network effects kicked in as users grew and integrations grew.

A nice virtuous cycle was formed:

• Many SaaS companies started integrating, they promoted their integrations, their customers saw the integrations, these customers signed up with MailChimp as they needed email marketing.
• More developers saw rivals integrating with MailChimp, they then started integrating to MailChimp.
• MailChimp customers started asking their other SaaS providers about integrations. The providers started doing integrations (eventually a financial incentive from the $1m fund wasn’t needed)
• MailChimp customers saw certain integrations and selected SaaS solutions from the list of providers that integrated with MailChimp.

And the rest is history…

Today MailChimp is a force to be reckoned with.

They have the following competitive barriers:

Switching Costs. Most companies don’t want to deal with the hassle of changing email marketing providers because it would mean updating integrations, losing historic reporting data, and learning a new system. Email marketing switching costs aren’t as high as say a CRM (because many different departments, and people are engrained). They are, however, high enough that there would have to be a compelling value proposition for someone to wish to move.

Indirect Network Effects. MailChimp continues to have Indirect Network Effects because of the sheer number integrations partners — pick your favorite tool and I’d wager MailChimp has an integration, and chances are the SaaS provider built it.

Any Vulnerabilities?

With that said I think they are vulnerable in vertical segments because the barriers based on the number of integrations needed may not be that high, which negates the Indirect Network Effects.

For example, in ecommerce: integrations are mostly really needed for a handful of shopping carts.

A company entering such verticals could come up with a compelling enough value proposition, which, if left unaddressed, could gain momentum. Case and point being Klaviyo for ecommerce. They’ve managed to do quite well with real time data segmentation capabilities. [*] Mailchimp has yet to fully respond (and I wonder why?).

Or if a large number of customers are concentrated around a single integration partner, which is isolated from other integration partners. A strained relationship here could result in vulnerability. Again, for example, ecommerce really needs an integration into the individual cart and maybe a popup tool, Case and point being the strained relationship with Shopify, with the beneficiary being Klaviyo. [*]

To any founders reading this section: before you dive in and try to tackle the vulnerabilities, remember that you need a compelling, sustainable reason for customers to consider you. Sustainable being key — because if your reasons are features (and not a Strategy to develop your own Power), then plan for what happens when MailChimp adds those features. Or hope you’re lucky enough that they don’t.

P.s.

To Ben and Dan from MailChimp: congrats on the success. I’d love to buy you guys a drink.

Power in SMB Email Marketing — MailChimp’s rise, sustainability and ConstantContact’s decline was originally published in Mostly Business on Medium, where people are continuing the conversation by highlighting and responding to this story.

I’ve recently read a great book: “7 Powers: The Foundations of Business Strategy” by Hamilton Helmer.

The Powers discussed are the “set of conditions that create the potential for persistent differential returns”. Said another way, they help create competitive moats that help a company grow and sustain differential margins.

I think strategically considering Power can be especially powerful for startups and early investors. As Hamilton said: “your first step is invention: breakthrough products, engaging brands, innovative business models. The first step, yes, but it can’t be the last step.” There has to to be Power for a firm to be able to create long term business value.

Investors learn a framework to analyze a firm ex ante, helping to spot the Powers that are being development, thus understanding the true value of firm. Strategists can begin thinking of Power development to ensure sustainability.

“7 Powers” helped me better understand the trials and tribulations I personally experienced in super competitive markets. I now, more clearly, see how a firm can develop conditions for persistent growth and returns by escaping competitors. (I’ll outline the Powers developed in the email marketing SMB industry in a future post).

7 Powers

For each Power, I’ve noted:

• Benefit: how it helps the firm
• Competitive Barrier: how it holds competitors at bay
• Exclusivity: is it the only company in a market that can have the Power?
• Phase: which phase of the companies development does the power get established. The phases are Origination (before rapid growth), Takeoff (explosive growth), and Stability (less than 30% annual growth).
• Getting it (how it is developed)
• Example (a quick example of the Power).

Powers:

1. Scale Economies: The quality of declining unit costs with increased business size

• Benefit: Reduced Cost
• Competitive Barrier: Prohibitive Costs of Share Gains
• Exclusive? No, a similarly sized firm could have the same cost benefit.
• Phase: Power established during Takeoff.
• Getting it: You must simultaneously pursue a business model that promises Scale Economies (industry economics), while at the same time offering up a product differentially attractive enough to pull in customers and gain relative share (competitive position).
• Example: Netflix’s smaller-scale streaming competitors offer the same deliverable as Netflix, similar amounts of content for the same price, their P&L will suffer. If they try to remediate this by offering less content or raising prices, customers will abandon their service and they will lose market share.

2. Network Economies: A business in which the value realized by a customer increases as the installed base increases.

• Benefit: Higher prices than its competitors
• Barrier: Unattractive cost/benefit of gaining share
• Exclusive? Yes, winner takes all.
• Phase: Power established during Takeoff. Maybe planned during Origination.
• Getting it: you must simultaneously pursue a business model that promises Network Economies (industry economics), while at the same time offering up a product differentially attractive enough to pull in customers (competitive position).
• Example: A lot of value would have to be offered to Facebook users to leave the platform to another platform.

3. Counter Positioning: A newcomer adopts a new, superior business model which the incumbent does not mimic due to anticipated damage to their existing business. Must pass tests: 1) idiosyncratic (peculiar), 2) Non-arbitraged (resource not acquired by fully arbitraged price), 3) transferable, 4) ongoing, 5) sufficient (other compliments not needed)

• Benefit: Biz Model with Reduced Cost and/or Higher Prices
• Barrier: Reaction will lead to Collateral Damage to current biz model
• Exclusive? No, others can have same business model.
• Phase: Power established during Origination.
• Getting it: You pioneer a new, superior business model that promises collateral damage for incumbents if mimicked.
• Example: Netflix charging no late fees where late fees made 50% of Blockbuster revenues. Blockbuster couldn’t respond.

4. Switching Costs: The value loss expected by a customer that would be incurred from switching to an alternate supplier for additional purchases. Types of costs: financial (implementation, migration), procedural (staff training, process updates, errors) and relational (new support, emotional bonds)

• Benefit: Charge current customers higher prices for equivalent follow-on products or services. No impact on potential new customers.
• Barrier: Unattractive cost/benefit of gaining share because competitor can set or adjust prices in a way that puts their potential rival at a cost disadvantage.
• Exclusive? No, others can have similarly high retention rates
• Phase: Power established during Takeoff. Maybe planned during Origination.
• Getting It: you must first attain a customer base, meaning the same new-product requirements demanded of Scale and Network Economies factor in here as well.
• Example: Moving away from Salesforce CRM has high switching costs. Integrated add-ons such as marketing automation systems can demand higher prices.

5. Branding: The durable attribution of higher value to an objectively identical offering that arises from historical information about the seller.

• Benefit: Elicits good feelings about the offering (affective valence) and peace of mind that offering will be as expected.
• Barrier: A long period of reinforcing actions (hysteresis) and a long investment runway with no assurance of an eventual path to significant affective valence.
• Exclusive? No, others can also have Branding.
• Phase: Power established during Stability.
• Getting It: Over an extensive period of time, you make the consistent creative choices which foster in the customer’s mind an affinity that goes beyond the product’s objective attributes.
• Example: Hermes, Gucci, Tiffany

6. Cornered Resource: Preferential access at attractive terms to a coveted asset that can independently enhance value. Must be unique, non-arbitrated (e.g. fee not corresponding to value), transferable, ongoing, and sufficient on its own.

• Benefit: Many fold include: reduced costs, higher prices, or preferential access to a valuable resource offering unique benefits.
• Barrier: Some kind of decree, e.g. legal , that blocks others access to resource
• Exclusive? Yes, the resource is, well, cornered.
• Phase: Power established during Origination.
• Getting It: You must secure the rights to a valuable resource on attractive terms. This often comes from having developed that resource in the first place and then gaining ownership of it, the most common avenue being a patent award for research developments.
• Example: A patent

7. Process Power: Embedded company organization and activity sets which enable lower costs and/or superior product, and which can be matched only by an extended commitment.

• Benefit: able to improve product attributes and/or lower costs as a result of process improvements embedded within the organization.
• Barrier: these process advances are difficult to replicate because of complexity and opacity. They can only be achieved over a long time period of sustained evolutionary advance.
• Exclusive? Yes, the same process, if providing Power, is exclusive.
• Phase: Power established during Stability.
• Getting It: You evolve a new complex process which renders itself inimitable within a reasonable period and yet offers significant advantages over a longer period of time.
• Example: Toyota Production System process

7 Powers — competitive moats was originally published in Mostly Business on Medium, where people are continuing the conversation by highlighting and responding to this story.

I’ve been digging into the math behind the VC or Angel investments. This post is a summary.

Success Measure: IRR Returns

A key measure of success for investors is IRR. So it’s important to first understand IRR and the inputs. IRR is the Internal Rate of Return. IRR in it’s basic form is basically the compound annual growth rate of return that an investment got. The simple inputs are:

• Time (e.g. years)
• Multiple of the amount invested (e.g. 10x back from my $1K investment = $10K)

The below charts show the IRR% based on those two inputs. If one invested 5 years ago and got a 5x return, then the IRR would be 38%.

Target IRRs

Investors are shooting for 20%+ IRRs.

VC IRR Returns vs Other Strategies

Are they getting 20% returns? The below table shows VC returns compared to other investment strategies. What’s interesting here is that on average, the VC investments are not providing better returns than the S&P 500.

… but there’s the story of the Power Law

The below table shows that VC returns are incredibly skewed. The difference between the Top versus Median and Bottom quartiles are very significant. The Top VC Elite firms are offering massive returns.

Angel IRR

Finding information on angel investor returns is difficult. The Halo Report says that IRR is between 22% to 29%. The numbers are a far cry higher than the data shared above. One reason could be that VCs time to exit is longer (. Or could it be that the research methodology here is focused on the Top angel investors? It seems hard for me to believe that all angel investors are getting such massive returns.

I haven’t been able to find any quartile reporting for angel investments, would love to see it if someone has it.

The Decile Elites Need Massive Hits

Let’s assume the top 10% of investors 35% IRR. That’s a 20X multiple….

So Decile Elite fund that has say $100M needs to return $2B in 10 years! And an angel with $2M will want $40M.

A 20x multiple makes a huge impact when selecting companies in a portfolio.

Angel & VC Investment Returns was originally published in Mostly Business on Medium, where people are continuing the conversation by highlighting and responding to this story.

The TSLA stock has been on a wild ride lately, mostly because investors are concerned about the potential of running out cash — which they seem to remember whenever Elon Musk musk Tweets or does something odd.

So putting emotions aside: given Friday’s stock price, is the stock price favorable based on future business outlook?

Emotions Aside…

So let’s forget about a) the genius of Elon Musk, and b) all other drama, including smoking pot or taunting the SEC.

I think right now there’s only three factors in pricing Tesla, both of which have to do with their vehicles: 1) Demand for cars (orders), 2) Delivery of cars (manufacturing) and 3) Margins for making cars (costs).

Tesla is an innovative company (it’s their moat), but I’m sure there are tons of great ideas for future enhancements and revenue from new products, like the truck, solar roofs, and so on… but given their cash position, they just seem to generate cash by producing lots of vehicles.

Demand has been strong.

I think the demand side is less of a concern. Tesla has a pretty sexy brand here in the US. There’s also a huge untapped opportunity in China, which will come with it’s own host of challenges. Reservations have been noted to be strong based on the company’s Q2 report (reported at 420,000, even though they’ve delivered very little cars).

Revenues need a lot more cars delivered.

I used Trefis to build a quick model that would support a $262 stock price. Revenues would need to increase to $16.9B in 2018 and $21B in 2019. Revenue for first two quarters of 2018 were $6.6B.

Tesla will have to produce a very significant number of new cars delivered. The majority of the growth is riding on the $35K Model 3. That’s about 200K Model 3’s in 2018 (they’ve done about 95K as of Oct 7th), 340K in 2019, and 440K in 2020. That’s a total of about 1M new cars over the next three years. (As a point of comparison, Ford sells 21M cars in North America each year across all their segments).

Margins have a ways to go.

Margins would need to reverse a downward trend to a steady increase to 26% over the next few years. Here’s what Musk said about margins at the end of Q2. Given the below, margins are somewhat tied to the production pains.

“…when it’s going up the production line, there are a tremendous amount of inefficiencies. There’s a lot of hurry up and wait, where some parts of the production line move well. Then, one part doesn’t and you have associates waiting around with nothing to do.

There are parts that we thought were right but then it turns out they weren’t right. We then send them back to the supplier. It’s just like the whole sort of giant machine. It just needs to kind of lurch into a high pace and there’s a lot of lurching, which is very inefficient.

So, you end up having super high labor costs per car and it just takes time to sort of spool up this giant machine. Basically, a production system is like a giant cybernetic collector and it moves as fast as the slowest part. So, as we address those slow parts and as we improve efficiency, gross margin and so the profitability per car just improves dramatically…”

If Tesla can’t pull off the above then their stock may very well not be worth the $262 it is today. Fixing margins will take time. Hitting production numbers could buy Tesla the time to work on the margins. The real bet is can production numbers continue to increase and beat the numbers above? Producing 340K Model 3s in 2019 is 7K a week, and then increasing to 8.5K a week in 2020. Seems doable? But can that be achieved without significant additional CAPEX? And improving margins?

We’ll see what the Q3 results shows. My guess: there’s been significant enough progress made to enable Tesla to meet demand.

Thoughts?

Pre-Mortem

• Market demand drops (small risk)
• Model 3 production cannot meet targets (medium risk)
• Margins cannot be improved (high risk)

The key risks appear to be all execution.

Buy a Ticket on the Tesla Rollercoaster? was originally published in Mostly Business on Medium, where people are continuing the conversation by highlighting and responding to this story.