Category Archives: Venture Capital

LP 101: Intro to investing in venture funds

I’ve had the opportunity to recently talk to a few folks who are considering investing in a venture fund for the first time. While there are lots of resources for new angel investors, I’ve found there isn’t as many for new LPs.

#OpenLP is a great movement to get the voice of LPs into the market, and Origins by Notation Capital is a great podcast where they interview LPs. I highly suggest both of these, and there are other great resources out there, but they seem to focus more on providing LP insight into VCs.

I thought I’d share some articles that might help those considering investing in a venture fund for the first time. By no means do I guarantee these are the best resources, but it’s a good start – and I’ll keep adding.

For those who are very unfamiliar with venture capital, 16 Definitions on the Economics of VC on A16Z’s blog is good to get familiar with some of the terminology.

I’d then dig into VC Funds 101: Understanding Venture Fund Structures, Team Compensation, Fund Metrics and Reporting, which covers… a lot of stuff, as it says in the title.

For understanding expectation as an LP, Funding Math by @homanyuen is a good article that provides some data point around expected returns as an LP, and the power law dynamic at play in the underlying portfolio. To summarize:

  • LPs want to see 2-5x return (6%-15% annualized) depending on stage of investments.
  • 65% of startup investments see 0-1x.
  • 10% of startup investments see 5x+.

This Twitter thread by Benedict Evans has some great graphs that go further into explaining the power law of returns at the portfolio level and their impact on fund returns. To summarize:

  • Across the board, about 6% of deals done produce 60% of the returns.
  • For the best performing funds (that do >5x), ~20% of their deals produce 10x returns, providing ~90% of the fund returns.

For those who want to dig in further on return expectations, this Twitter thread is a fairly biased thread that makes a great case on investing in venture capital. To summarize:

  • At the top quartile, VC has historically outperformed other asset classes (like PE, RE).
    • Note: VC is the most volatile, so this makes sense.
  • Even median funds in the 2009-2012 vintages are showing 9%-21% returns depending on vintage year.
  • VC has low top negative correlation with other major asset classes.
    • Specific to the S&P 500, VC returns have negative correlation.
  • On liquidity:
    • Avg time to M&A transaction: 5.5 years
    • Avg time to IPO: 8.5 years
    • Avg time to exit: 6.5 years

Slightly different, but if you want a better understanding of how many startups VCs meet before investing – while just one data point – Satya Patel at Homebrew was kind enough to share some of their metrics around this in their blog post: Homebrew’s 1%: The VC Metrics Behind Investing in One of Every 100 Companies We Meet.

How to find Angel Investors using LinkedIn

I found a way for founders to find angel investors in their network using LinkedIn, and since sharing this with a couple founders and getting feedback – I’m excited to tell you – it works (for some, at least).

It’s simple.

Go to LinkedIn. Search for “angel investor”, and filter down to “people” who are within 1 or 2 degrees with you.

Depending on your network, this could be a huge list (mine shows 31,205). It’ll have noise, because this includes people who work with angels investors, etc.

Alternatively, you can remove the keyword search, and search for folks who have or have had the role “angel investor”. You can find this in advanced filters.

If the search result is too large, you should filter down to locations close to you so you can fundraise with minimal travel.

The key here is your mutual relationships with these angels.

At this point, I suggest setting up an Airtable. As much as I love Google Sheets, for what I want you to do, you’ll need the “Linked Table” feature from Airtable.

First, you’ll create the table “Angel Investors”. First column will be their name. You’ll then create a “Linked Column” titled “mutual connections” and create a new table called People. This is where you’ll put people in your mutual relationships.

As you go through the search results in LinkedIn, look at the profile of each search result and determine whether you feel they are worth reaching out to. Part of this is looking at the mutual connections and seeing if you know them well enough to ask them to forward an email along.

(I’m not going to go into forwardable emails here. Read Alex Iskold’s post if you’re not familiar with it)

If they seem like a fit, and you have good mutual connections, add them to the “Angel Investor” table, and in the “Mutual Connection” column, add the person or people you might try to reach them through.At the end of this exercise, you not only have a big list of angel investors in your network, but have tracked your mutual connections with them. You can then look at your “People” table, add a column that counts “Angels” they know – and sort by it. Now you know that Susan who you volunteered with happens to know 5 angel investors in your city.

You then ask your friends if they would mind looking through (or hearing) a short list of names, and if they know any of them well enough – if they could forward along an email to them.

The original list of angels you created will pare down fairly quickly, as you realize many of the LinkedIn relationships are not strong (eg “I don’t recall that name, must have met them at a conference”), but that’s part of the process.

I’m sure this will work better for some than others – if you try this, I’d love to know how it goes. You can leave a comments or just tweet me (@yoheinakajima).

The Role of Venture Capital

I like to view the world through different “lenses” to help me understand it. It’s a means to generalize the world and help me consider patterns. Thinking of the world simply as a collection of matter and space is what I call the “physicist lens”, a collection of incentives is the “economist lens”, a collection of energy is the “spiritualist lens”, and so on. Today, I spent some time thinking of the world as a collection of data, which I’ll call the “data scientist lens”.

Through this lens, I saw that human society is doing one big complicated data science project. It can be broken down into many smaller projects, but they’re intertwined as every piece of data can be connected to another through some series of nodes.

The process of a data science experiment roughly goes like this: you collect and store data, you process it (clean, merge, etc.), analyze the data, extract insight, create an action plan based on the insight, execute the action plan, reflect on the process, and repeat the process.

Similarly, in society, we’re constantly going through this cycle. We do this as individuals daily, as groups of people (companies, families, social groups), and as a society at large. Like complex organisms, society becomes efficient by allowing smaller groups within to specialize, in the type of data it deals with and in the phase of the process.

As a Venture Capitalist, our role is in the reflection phase of the process, specific to new data (social data, voice data, health data, etc.) and new processes (cloud storage, distributed ledgers, machine learning, etc.). We reflect on the past and allocate resources that human society has trusted in us to control – through a network of complicated financial institutions.

As individuals, we have the desire to both serve ourselves and serve society at large. As Venture Capitalists, our job is to see what’s working to create value (desired change in data – wealth, health, and happiness) for individuals, both people and business, and for society at large.

VCs are like Snowflakes

The most common fundraising question I get from founders is “what do VCs look for in a startup?” Aside from the obvious strong team, I tell them this:

Each one is unique.

When approaching VCs, this is important to understand. You should do as much homework as possible before approaching any VC. Here are a couple things you should try to find out if possible.


The first thing you should learn is what stage a VC invests in. Broadly, VCs invest in early, growth, or late stage. Specifically, they may invest only in Seed, Series A, Series B, and so on, but most will be interested in a couple of these.


Most VC funds have a thesis. Some as broad as B2B vs B2C. Some invest in one or more specific industries, like SaaS, Finance, Smart Home, Automotive, and so on. Within an industry, they may have specific areas of interest. This thesis may be driven by what they see as opportunity (good markets to invest in), their areas of expertise, or their network. Often the VCs communicate this thesis to their LPs, so they may invest strictly within their thesis, while others may be more open. In addition to funds having a general thesis, each partner in a fund will usually have their own areas of interest.

Round Size/Check Size/Ownership %

This is similar to stage, but worth noting separately. Many VCs have a range for a check size they’ll cut in a first investment (different from follow-on check size). They’ll probably have a general round size they’re interested in investing in. Combine these two, plus stage, and past investments, and they’ll get a sense of ownership %, which is also important to them.


VCs usually know how frequently they plan on writing checks. Active ones may write multiple checks a month, while less active ones may write only a handful a year. This frequency can be cyclical, based on their own fundraising status and amount of capital left in their current fund.

Decision Making Process

VCs vary in how they make investment decisions. At a fund with a single GP (often smaller funds), this is pretty straight forward. Most bigger funds have multiple partners, and this is where it starts to differentiate. Some funds need unanimous agreement amongst partners, some need majority, some might have a unique voting structure, and some only need one partner to want to invest. No matter the case, you’ll usually be working with one partner who is selling this investment internally. If you’re working with an associate or principal, it might be worth trying to understand how they fit into the process.

Due Diligence Process

Due diligence happens before decision making, and can vary by VC. It can include everything from multiple meetings, meeting you in person, having you meet the whole partner team in person, reference checks with references you provide, reference checks with references you don’t provide, checking in with expert colleagues, and a whole lot of other stuff (exit analysis, competitor analysis, market analysis, etc.).

Lead vs Follow

Quite simple, but some VCs will lead rounds (some prefer this), while others will only follow. The ones who lead rounds are setting terms, and the ones who follow will often look at who is leading the round as important data when making decisions.

Post-Funding Support

Some VCs are hands-off and don’t get too involved after investing in a company. Today, many VCs use their ability to support companies as their differentiator, earning them a seat in hot rounds. The ways in which VCs support their portfolio companies differ as well, from making introductions to emotional support to actually getting their hands dirty in some operational stuff.

Past Investments

This one should be relatively easy to find out (hint: Crunchbase). You should be able to extract some general ideas about thesis, stage, and maybe even frequency through studying their past investments. It’s also worth noting that VCs tend to have a bias toward or against patterns they’ve noticed in their own investments (ie. “I was burned once by an investment in a company selling to SMBs so…”).

There’s probably a couple important ones I’m missing, but the above should be a good list to get you going. Just remember:

VCs are like snowflakes, each one is unique.

The Role of Algorithms in Venture Capital

We first saw program trading, where computers were preprogrammed to execute a stock trade based on predetermined conditions, in the 1980s. Today, over 1/3 of stock trades worldwide and well over 1/2 of stock trades in the US are executed by algorithms.

Algorithmic venture capital investing is far from common place today, and many argue it never will be. However, it would be hard to argue that data does not play an important role in the industry.

Pioneers in this space already use algorithms to make decisions. Matt Oguz at Palo Alto Venture Science ($200M fund) looks at 13 different variables for each prospective company, like technology, IP, people/team, location, and competition (source). WR Hambrecht Ventures works closely with Thomas Thurton of Growth Science and combined predictive modeling with Clayton Christensen’s disruption theory (source). David Koatz and David Kienzle at Correlation Venture ($166M fund) weighs the track record of the entrepreneurs, investors, and advisors heavily (source). Google Ventures ($1.5B under management) looks at data from academic literature, past experience and due diligence of founders and startup. (source).

Looking at survivorship of companies after a 10-year period, Thurston says his algorithm has a 66% hit rate, but it’s still too early to know if these algorithms can consistently out perform humans, and if so, in which areas. It would make sense that this algorithmic approach works better for later stage investing where there are more consistent and comparable metrics to feed into the algorithm, as opposed to early stage companies where there are fewer metrics to feed into the algorithm.

Some might suggest that this algorithmic approach would work best for niche categories, allowing the algorithm to specialize. Circle Up a crowdfunding site for consumer packaged goods employs an algorithm to help help evaluate over 500 deals a month (source). Deep Knowledge Ventures appointed an algorithm to it’s board, capable of making investment recommendations of age-related disease drugs and regenerative medicine companies based on a companies’ financing, clinical trials, intellectual property, and past funding rounds (source).

While these algorithms can process more information and deliver results quicker, most (if not all) funds still employ some human element to screen results before making final investment decisions (source).

By making enough investments, it’s not difficult to see how an algorithm might help a fund outperform the average venture fund. It seems difficult, however, for an algorithm based fund to be a top-performing fund, whose returns come from outliers – which are by definition the most difficult to identify via an algorithm.

Perhaps the role of algorithms in venture capital investing is not to replace human decision making, but merely augment it.

Top 10 AngelList Syndicates You Want to Check Out


This post is for the rich wanna-be-passive-angel-investors out there. If you haven’t heard of Angel Syndicates, you should read up on this new service that AngelList recently started offering in private beta: Angels Get Carry for Helping a Startup Raise Money with AngelList Syndicates (TechCrunch).

What’s Equity Crowdfunding?

Equity crowdfunding is fairly new. It’s similar to the crowdfunding you hear about on Kickstarter or Indiegogo, but instead of rewards, you get equity. As of now, only accredited investors (read: rich people) can participate in an equity crowdfunding round. Sites for equity crowdfunding include AngelList, Crowdfunder, Fundable, and many more.

Where Do You Do It?

IMPO, as of now, AngelList is the only site you need to look at if you’re looking to invest in high-growth tech startups. You’ll find most major startups and angel investors from the tech world listed on there. (There are also niché sites, for example, like Quirky that focus on inventions).

So… Angel Syndicates?

Even with equity crowdfunding, however, a new angel investor might have difficulty filtering through the noise and doing the due diligence. That’s where Angel Syndicates come in.

Passive angels can now back Angel Syndicates, which operates much like a VC fund, except there is no management fee. Carry is comparable, and as of now the standard is being set to 15% (compared to the normal 20% a VC takes). The lead angel of a syndicate also has to cover, with their own money, 10% of however much they’re raising for the syndicate (aka: more skin in the game than a VC fund manager).

As a backer, you commit $1,000 or more per deal for X number of deals with a specific angel syndicate. Any time that angel is making an investment, you’re *automatically brought in on that deal for the amount you specified. (*you technically have 72 hours to opt-out, which you can only do under special circumstances – conflict of interest, etc.)

Why I’m So Excited About This

AngelList Syndicates are a great way for new angel investors to start investing in tech startups because they can hedge their bet across a large number of startups, and they can do this without doing due diligence on hundreds of startups, rather do due diligence on a handful of credible angels who have syndicates.

Making it easier and less-riskier for non-savvy rich folks to invest in tech startups leads to more total money available for tech startups globally. More money available for tech startups makes it easier for founders to raise money, and therefor allows them to focus on growing their companies and spreading their innovations.

Top 10 AngelList Syndicates

My methodology is quite simple. There are only 268 Syndicates currently listed, only 10 of them have 10+ backers. If you’re actually going to back a syndicate, I urge you to do your own due diligence. However, relying on a due diligence of others who are putting their own skin in the game is a great place to start (#CrowdsourceEverything).

*Stats from morning of 10/3/2013 – this is going to get outdated real soon…

Kevin Rose – 335 backers for a total of $1,461,100
It’s interesting to note that his carry is listed as 0%, perhaps why he has so many backers. What he’s signaling: that he’s in it not to make money, but to make more funds available for startups.
Confirmed investments on AngelList: 42

Dave Morin – 211 backers for a total of $923,800
Confirmed investments on AngelList: 68

Jason Calacanis – 173 backers for a total of $719,600
Confirmed investments on AngelList: 42

Brad Feld (FG Angels) – 119 backers for a total of $224,401
While it’s currently listed as Brad Feld, this is going to be a Syndicate by FG Angels (part of the Foundry Group). Read more about this on Brad Feld’s blog post here. With plans to invest in over 50 startups by the end of 2014, this is going to be one of the most active syndicates early on.
Confirmed investments on AngelList: 27

Betaworks – 49 backers for a total of $241,500
Confirmed investments on AngelList: 75

MG Siegler – 33 backers for a total of $162,000
Another Syndicate w 0% carry (like Kevin Rose). Probably worth noting that both MG and Kevin are Partners at Google Ventures.
Confirmed investments on AngelList: 46

Elad Gil – 29 backers for a total of $79,000
Confirmed investments on AngelList: 26

Naval Ravikant – 26 backers for a total of $175,500
In case you didn’t know, Naval is the Founder & CEO of AngelList.
Confirmed investments on AngelList: 107

Tim Ferris – 24 backers for a total of $253,000
His next book: 4-Hour Angel Investing. Probably not.
Confirmed investments on AngelList: 30

Andrew Chen – 18 backers for a total of $43,000
Confirmed investments on AngelList: 6

Sundeep Ahuja – 10 backers for a total of $44,000
Confirmed investments on AngelList: 7

For more opinions on AngelList Syndicates, check out this PandoDaily article: AngelList syndicates are changing seed investing whether VCs like it or not.

15 Notable Venture Capital Firms in Los Angeles


[Update 9/24] Added TenOneTen Ventures to the list, so now it’s at 16.

Whether you call in Silicon Beach, the LA startup community, or the Los Angeles tech scene, it’s pretty much one and the same. What fuels it? Money. Here are a list of notable local Venture Capital firms, links to find out more about them, where they’re headquartered, and some notable investments they’ve made.

*This list does not cover 100% of VCs in LA. Notable VCs and Investments are decided by the author based on factors including size of investment, recent activity, or notability in LA.

Come by Coloft anytime to hang out with me and work on resources like this :) I’m also currently working on breaking down which industries and stage they invest in so keep an eye out (or reach out to help! –

Sources: Crunchbase, The Startup Universe

A-Grade Investments
HQ: Los Angeles
Notable Investments:, SocialCam, Getaround, Couple
Website | Crunchbase | Startup Universe

Anthem Venture Partners
HQ: Santa Monica
Notable Investments: Beachmint, Scopely, SurfAir, BUZZMEDIA, Big Frame
Website | Crunchbase | Startup Universe

Baroda Ventures
HQ: Beverly Hills
Notable Investments: Science Inc, Surfair, Fab, Retention Science, Dog Vacay, Letuce, 20JEANS, Chromatik
Website | Crunchbase | Startup Universe

CAA Ventures
HQ: Century City
Notable Investments: 20JEANS, NuORDER
Website | Crunchbase

Canyon Creek Ventures
HQ: Santa Monica
Notable Investments: Amplify LA,, At the Pool
Website | Crunchbase | Startup Universe

Clearstone Venture Partners
HQ: Santa Monica
Notable Investments: The Rubicon Project, Glossi, At The Pool
Website | Crunchbase | Startup Universe

Crosscut Ventures
HQ: Santa Monica
Notable Investments: Docstoc, GumGum, StyleSaint, Lettuce, Eventup
Website | Crunchbase | Startup Universe

Karlin Ventures
HQ: Westwood
Notable Investments:, Amplify LA, ChowNow, PageWoo, Bitium
Website | Crunchbase | Startup Universe

New World Ventures
HQ: Chicago (LA Office: Westwood)
Notable Investments: Truecar, Beachmint, Big Frame, Eventup
Website | Crunchbase | Startup Universe

Palomar Ventures
HQ: Santa Monica
Notable Investments: Fulcrum Microsystems, ExteNet Systems, Predixion Software
Website | Crunchbase | Startup Universe

Rustic Canyon
HQ: Santa Monica
Notable Investments: Science, Docstoc, LoopNet, Chromatik
Website | Crunchbase | Startup Universe

Redpoint Ventures
HQ: Menlo Park (LA Office: Westwood)
Notable Investments: Twilio, PandoDaily, Machinima, Stripe, Path, Heroku, SocialVibe
Website | Crunchbase | Startup Universe

Siemer Ventures
HQ: Santa Monica
Notable Investments: Technorati, Vator, Ranker, Amplify.LA, Surf Air, Stack Social, 20JEANS
Website | Crunchbase | Startup Universe

Steamboat Ventures
HQ: Burbank
Notable Investments: Merchant Circle, EdgeCast Networks, GoPro, Photobucket
Website | Crunchbase | Startup Universe

TenOneTen Ventures
Notable Investments: Kaggle, Ranker, Nearwoo, Divshot, Surfair, Scopely
Website | Crunchbase | Startup Universe

Upfront Ventures
HQ: Century City
Notable Investments: TRUECar, Factual, Maker Studios, Adly, NuORDER, DailyLook
Website | Crunchbase | Startup Universe

Explaining the Rise of Accelerators/Incubators

For my senior thesis at Claremont McKenna College, I wrote about Angel Groups, who started investing in the space that VCs abandoned as they started investing in larger deals.

Over time, many angels learned the risk of investing in companies that were still pre-seed. The solution, which has recently caught on like wildfire, was the incubator/accelerator model, not only providing funding, but also providing mentorship. By pooling the money from groups of investors to start the accelerator and by bringing on a large group of mentors, they’re successfully hedging the risk of investing in pre-seed startups while also increasing the success rate of those companies.

In short, the recent growth in numbers of incubators/accelerators is only partially due to the growing startup economy, but it also signifies a fundamental shift in the way pre-seed investments are made.

Entrepreneur [Inspiration + Perspiration] + Accelerators/Incubators [Money + Mentorship + Community] = Success?