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Entrepreneurs: Ajo and His Startup Quant Price

Friday, January 15th, 2016

Quant Price logo

Yesterday I described how I came to start my company Quant Price. Today is the story of what happened after that decision.

I first did the Founder Institute program that helps entrepreneurs create companies. They introduced many concepts that are hard for first time founders to grasp. Things of HUGE importance ranging from talking to potential customers to validate the idea to seeing how buying decisions are made.

There are many things that can make a startup fail. Each of these factors are risks. A successful startup has avoided each of these pitfalls in succession.

There is a step by step process to developing the idea and de-risking it. The founder Institute program helped me think through them.

One shortfall of the program was that it has a cookie cutter view to creating startups. It requires that everyone fit into a mold. This may not serve every startup well. I’d probably have taken it to completion if I were not “terminated” for having a hard time getting a sufficient number of video interviews.

Though to be rational, I’ve to admit that it’s also possible that I just have a very bad idea or am not really cut out for this. I may only know very late because “I’m drinking my own Kool-Aid”.

The risks are huge. There are a lot of things that matter to a startup being a success. There has to be value in the product. There has to be a way to reach a big chunk of the market. There has to be a way to convert all those gains into money. People have to believe in the dream and be willing to contribute for free for the duration that the cash flow doesn’t exist.  It takes a lot to keep a startup together.

It was very hard to find my first customer. I didn’t even have my marketing material when I went to interview Katherine Krug the founder of Getbetterback.

Partially because I didn’t realize that I was supposed to bullshit my way through such meetings and, frankly, partially because I didn’t know how to bullshit about it if I had to.

Fortunately, Katherine is one of those people who tests things like prices. I think she was lucky to not have a mentor who had a strong opinion about pricing. (I still can’t believe that people don’t test their prices.)

Katherine first did a price test with Optimizely. Unfortunately, Optimizely is not really geared to do price tests. Additionally, putting Optimizely code on your web page makes it load a lot slower for the end consumer. That itself reduces conversion rates.

It made me wonder if people don’t know or just don’t care about the impact this has on the browsing experience.

Optimizely targets conversion rates, so once Katherine was done with the test it told her how many people had converted to buy at different prices. Obviously at the higher price, fewer people converted.

But the real question was which price lead to better margins?

And was the test significant?

That is when she realized she needed Quant Price.

I salvaged the Optimizely results to guess what the next prices for the next test should be.

We used our pricing engine and did an A/B test. It turned out that seemingly identical prices $49 and $59 were over 26% different from a revenue perspective.

We also realized that changes to the web design and the holiday season could change the optimal price. So much so that at some point $69 was 22% better than $59 because of the Christmas buying spree.

Hidrate, my second client, was easier to find after we put up a video interview with Katherine.

With Hidrate, we seemed to run into some bad luck. The $59 price for them was identical to $49 from a profit perspective. But as luck would have it, they were running out of inventory. Now, at the $49 price they were burning through 45% more inventories to make the same amount of money as at $59.

Once we told them about it, they raise their price to $59 to save inventory. They kept their customers happier for longer AND made money to buy more inventories without losing the company to investors.

Here are details from our first two clients,

We did all this by using technology developed for finance. Quants in the financial industry are usually tasked with pricing securities worth trillions of dollars based on market data. There are multiple factors that affect the “fair” price of a security.

I learned how this valuable task of pricing can be automated incorporating available data.

Many companies now quote prices and sell exclusively online. Computers can be used to make pricing decisions based on price sensitivity of individual customers, business specific parameters, such as inventory availability and market conditions and the current season.

Airlines and Amazon already do this on a massive scale and are very profitable as a result.

SaaS companies and large-to-medium scale retail operations could be next in line.

Fortunately, our market is easily defined. We are looking to help companies with more than 300 distinct customers. This is desirable because with more data we can get statistical significance on more complex models.

We are looking to help SaaS companies that want better pricing models. For them, we have a solution that reduces churn and increases revenue at the same time !

To justify building a company-specific solution, we need to be able to service a pool of revenue of over 10M$/year.

Quant Price’s free app Qbot is available to smaller companies in the Shopify app store.

In order to make our technology more accessible we packaged it into APIs and apps, that help us expose this functionality to more companies.

Two final points.

  • We are looking for talented people  who can participate in the development of our product.

And if you have any questions or comments you can respond here or use the email address above.

 

Entrepreneurs: Ajo and His Startup

Thursday, January 14th, 2016

Ajo Fod

After I got my Masters in Computer Science and Optimization from USC,  I worked for banks for a while as a quant (people who do quantitative or mathematical stuff such as build complex models to evaluate financial securities, risk and reward).

Contrary to what most people would tell you about working for a bank, I found the work very interesting—not surprising, given my math background.

But much as much as I enjoyed my work, I was bitten by the entrepreneurial bug and wanted to do something original.

I’m an engineer at heart and I like inventing things that makes life better or improve what people are already doing.

Innovation seems to happen overwhelmingly in small to medium companies and then big companies usually buy the promising smaller ones.

Doing my own thing would also gave me the ability to try out new things at an amazing pace that makes the process of discovery a lot faster.

Initially I had the bright idea of trying to beat the banks at what they do best: price securities.

I invented a way of making models that could learn more from purchase data about pricing than conventional models do and put those models to work trying to outguess Wall Street computers.

Eventually, I realized that even though my algorithms were smart, the networks that were affordable to me were too slow to use this information for the strategy I developed.

Even though I could predict prices, I couldn’t get ahead of computers that were closer to the exchange to make the profitable trades.

I had to make a pivot or bet even bigger and buy access to the necessary networks.

I paused to think for a while and it occurred to me that the world is full of things that need to be priced.

So, why stick to the business of securities where so many quants and fast computers were concentrated in solving a problem with a lot of history?

Why not solve a Main Street problem?

I began looking for a niche where there was a significant problem that I could solve.

About that time I heard a story on the NPR money podcast.

Two sets of people were asked to guess the weight of a cow shown in a picture.
They first asked a bunch of experts what the weight might be and each gave a different answer.
They also gathered answers from a crowd of non-experts on a website.

The median value in the crowd of non-experts was much closer to the true weight of the cow than the group of experts!

That led me to think about how the wisdom of crowds could be used to help small companies make better decisions.

Of course, I wanted to monetize the information in the buying decisions that people make.

How about learning the perfect offer to make to shoppers at an online store?

 I’d recently built complex pricing models to value financial securities, so I knew I could do this.

I quickly noticed that small businesses were leaving a lot of profit on the table. They were essentially using rules-of-thumb, instead of measuring price sensitivity and making optimal offers for peak profit just like the airlines, Airbnb and Amazon are already doing.

How much of an advantage can optimization bring?

For example, the average retail store runs with a 5% net margin.
What  if the store could raise the sale price (after any discounts) of the average item by 1% without affecting demand?

That would raise their margin a staggering 20%!
And that is what happens with just a 1% change.

Imagine what can happen with a larger price change.

In our experiments with stores on Shopify, we noticed that they were so far off the optimal price that they were making less than 70% of what they could be making if they could tune into the crowd.

That is beyond a big deal!

So I began working on an app with the vision of using optimization to create better offer management strategies.

Over the last year I created the company, Quant Price. You can try our first app for free on Shopify.

Join me tomorrow for a closer look at what Quant Price does.

Entrepreneurs: Exploring FinTech with Ajo

Friday, December 4th, 2015

Ajo Fod

Ajo sent me an email about another conference he attended yesterday and I thought I would share it with you.

Hi Miki,

I attended the Future of Money and Technology Conference hosted by Brian Zisk .
I was invited to the conference thanks to an introduction by Dave Park who runs recombinantinc.com. Recombinant is interesting by itself because they can synthesize new music from a sample of old melodies from an artist using an AI algorithms.

The conference has a great attendance with many high powered people such as Jon Jeswald from the Federal Reserve, Sheel Mohnot from 500 startups and Arvind Purushotham from Citi Ventures.

One interesting line of development has been the use of Bitcoin technologies for DRM.

One of the issues that the music industry faces is that it’s hard to track the owner of the rights to a piece of music – through divorces, inheritance, etc. This is a big mess because even though people want to pay for the music they play, the owners of the rights often don’t get the money.

So, many startups are working on different aspects of the bitcoin type blockchain technology to keep track of who owns these rights.

There are several companies that have similar but slightly different applications of the same general idea of keeping track of rights to digital assets using the blockchain algorithms for other types of assets. Blockstack.io headed by Peter Shiau was recently acquired by Digital Asset based on its success in using this technology in enterprise software.

Interesting world we live in.

Cheers,

Ajo.

Fascinating stuff, Fintech; one of the few areas that no matter how much I read I don’t understand — starting with bitcoin.

Entrepreneurs: Ajo at The Lean Startup Conference

Friday, November 27th, 2015

Ajo Fod

As you all know, or will learn the hard way, you need be sure there is a market, before you build your product or service.

That is a basic premise of Eric Ries’ Lean Startup methodology, so I was very excited to be able to attend the Lean Startup Conference this week. It was a great opportunity to learn new ideas and refresh old ones.

I got to the conference early to hear Ryan Hoover from Product Hunt who had a great idea for community-oriented scalable startups
–  “Go where you are loved. Give it away. Build a community around it.”

Startups within companies are apparently catching on as well. Bennet Blank from Intuit suggests that for internal startups, the idea is to show people how to do it rather than tell them what to do, i.e lead by example.

Specifically for internal starups, the idea is to use the company culture but to do things slightly differently. The key idea is to avoid scaring anyone that something might break.

Startups within government have got to be a breath of fresh air. There are 2 parallel efforts in the US government to create better software and openness: USDS and 18F.
Leah Bannon spoke of how the FEC.gov is trying out open git repositories for collaboration at

A startup is a way to solve new problems. The best way to learn of problems is to talk to people.
– Unfortunately, people are nice.
– They will make up problems to make you go away.
– What people do on the other hand is interesting.
– They create inefficient work-arounds.
– This is where a product may fit in.
-There is a difference between Needs vs wants.
– Needs are well defined by behavior.
– Wants on the other hand are what people say they need. It changes.

So, how to find people ?
– Post on groups that have a concentration of users.
– Use surveys that take a maximum of 1 minute to answer.
– This can create fast learning.

So, what to build?
– Make it small and useful.
– It should take as little work as possible.
– And be easy on first time users.
– Give them something easy to do.

Amir Shevat spoke of how he initially built a meditation app.
It was initially hard to find the button on the app.
It’s also hard for first-timers to meditate for 45 minutes!
I reduced the meditation time for much better results.
Here is the meditation app.

At lunch I met Eric Leppo from the Silicon Valley Software Group, who told me about an MVP calculator he built, which estimates the cost of creating an MVP based on various features of the app.

There is a focus on marketing people these day. Amanda Richardson from Hotelstonight.com may have a point redirecting focus to problems instead. It seems more relevant since you can only solve problems. In other words, you need talent to solve problems and market the solutions to people.

They built an app that solves the problem of the last minute booker.
Its an easy to use interface to be used on mobile.
If they just worried about hiring stars, they’d not get anywhere!

But I keep feeling people-light in my startup. Lots of skills are involved in building things.
So I’m not really clear about the importance of finding the best people and getting a massive cast of characters.
Also, I learned that I should reward small failures because they enable learning.

One of the ideas from the closing conversation with Eric Reis and Chris Dixon from Andreessen Horowitz was that too much money is a major problem.
Money gets spent in the same 18 months no matter how much.
If you don’t have product/market fit, it’s a waste and can lead to big losses.
Startup movement is about building things.
The important change in this generation is that entrepreneurship is a viable career path.
Business has become more democratic.

Lyft was initially Zimride for a long time. They had a carpooling app for long distances.
What they learned from that car-share experiment was that it had to be:
-On demand.
-Dramatically increased supply.
-Community: there is the idea that taxis were disgusting.

General startup algorithm is to find the best problem to solve.
– Develop the technology to solve it.
– A lean startup keeps risk low with fast iterations.
– Accurate bad news is better than inaccurate good news.
– Valuation is not a KPI.

Find the thing needed to be successful.
Innovation-options.com
– Brady Nagel had a great talk on using LinkedIn (the free part)
– Google is not bounded by LinkedIn’s rules that restricts search size.
– When you want to find problems you’ve to talk to strangers.
– LinkedIn is a database of strangers. It’s free!
– The goal should be to define the problem.
– So, don’t talk about the solution.
– Take out details about past positions in LinkedIn profile.
– to avoid biasing peoples answers.
– Find a group on LinkedIn.
– Promote events.
– Talk about problems.
– Look for relevant groups.
– Say that we are doing research if the group is moderated.
– Create a group on LinkedIn
– Invite people to participate.
-Other useful sites for meeting strangers:
Emailbreaker.com
Intel-sw.com
Voilanorbert.com
Connections
– Find alumni networks

Here is an idea on how to start a conversation with a stranger:
Send an opening email saying:
– I’m involved in a program or am a researcher on X.
– You are knowledgeable about topic Y
– Can I have few minutes of your time or someone you know.
– How about such time on Tuesday?
– Follow up 3 times. That is persistence, more than that and you’re a pest :)

Andrea Hill from ReadyTalk on spoke about internal startups:
The key here is to find early customers who are stakeholders, then measure the importance of stakeholders in terms of:
– Contribution. Legitimacy. Willingness. Influence.
– Contribution: have valuable info.
– Legitimacy: are they affected?
– Willingness to engage.
– Necessity of involvement.
– Understand their needs.
– What does success look like to them? For example with the CFO, the idea is “Don’t break existing cash flow!”
– Find a sponsor to support and be the face of the project to the rest of the organization. This makes it easier to work on the product rather than explain all the time.
– Create a clear 2 way communication channel with management; in exchange, be honest when something is wrong.
The tradeoff with internal startups is that you take less risk and get less reward.

I went to this interesting talk about an experiment in a kitchen. The talk was called: Caution Live Subjects: by Lauren Braun
It was about an experiment to test if a sub-menu of possible substitutions on a menu added value.
They created real “looking” experiments for data and measured real behavior.
The conclusion from the test was that the list of substitutions added too much friction to add value.

In conclusion, the Lean Startup Conference was an interesting place to me as an entrepreneur. I met a lot of great people and heard many new and interesting ideas.

I’m a quant, so when I started Quantprice I tested the market, because it seemed the logical thing to do.

Since attending the Lean Conference, I look forward to using more lean methodologies as I build Quantprice.

And in case you are wondering, Quantprice improves Shopify’s e-commerce store margins over 30% in the same way that larger retailers and airlines do by enabling them to manage their offers in real-time based on factors that are automatically learned from past consumer behavior using big data and AI techniques.

App Cost/Benefit Analysis

Wednesday, September 9th, 2015

https://www.flickr.com/photos/jasonahowie/7910370882/

A post I wrote after two researchers made headlines by hacking a Jeep and taking control of its vital functions focused on the idea that nothing would change until consumers voted with their wallets and demanded better security.

Until that hack, combined with several major data breeches in the last couple of years, the general public didn’t seem particularly concerned — and that nonchalance is especially prevalent in those who grew up wired.

In a comment on that post I wondered if consumers just didn’t care or didn’t understand, but there is another option.

I read a article about Conspire, a new site that helps find business emails and sent it to several people I thought could use it, including Ajo Fod, founder of QuantPrice and occasional contributor here.

Conspire uses your email account as the basis for a game of Six Degrees of Separation. Sign up, and it analyzes your email. Then enter the name of the person you want to search and it finds someone in your contact list to introduce you, examining that person’s social-media connections. It may even find multiple people to help introduce you. Then it will recommend the best choice.

Ajo joined and sent me an invitation. I haven’t accepted yet, because Conspire requires your email account information and password (plus my email uses POP3, not IMAP).

I asked Ajo if he was concerned about security and here is his answer.

Security is a concern,

… but benefits are a bigger.

… I’ve been hit before by a bad egg that decided to spam all my contacts.

… so, yes, I was worried when I gave out my email/password.

… In this case. I did some research and thinking and the potential seemed big.

I do worry about credit card numbers and identity.

… In my mind, the benefits outweigh costs.

People still send me phishing emails.

Perhaps, being an Indian security is a lesser concern to me than other people my age in the US.

Actually, Ajo gave it more thought than most people I ask no matter their age.

There is one more thing you should think about when doing a cost/benefit analysis.

Time.

What is the ROI for the time you will spend?

Is the new app a time saver or time waster?

Money can be replaced, but once time is spent it’s gone forever.

Flickr image credit: Jason Howie

Entrepreneur: TiECon with Ajo Fod

Friday, May 22nd, 2015

Ajo Fod

TiEcon has become a huge event for entrepreneurs all over the world. It helps educate the entrepreneurs and connect them to clients, mentors and capital.
They have many good programs for entrepreneurs like Mentor Connect, where people meet potential Mentors who are people with a lot of experience starting companies. They also have a Founder Connect program where people speak of their ideas and look for either founders or capital.
I met people and reporters from Australia, Japan, Nigeria and Brazil, apart from the usual countries. This has become a global event, because TiE serves a big need.
Saying “TiE is for South Asians” (Indians/Pakistanis) is like saying “the US is for Europeans”. The successes TiE and the US have accomplished require being open and inclusive.

Just like the underlying value of the US is the preservation of freedoms, TiE’s value is to nurture entrepreneurs and grow its community.

TiE’s organizers realize the value of being well connected to achieve its goals. They have succeeded in attracting large volumes of the right kind of attention.

At Mentor Connect, I met Seshan Rammohan and Siren Dutia, both veterans of the field. Typically Mentor Connect puts a single mentor with 5 founders looking for advice. Fortunately I got two mentors’ time and minds for the price of one.

The discussion was interesting because we heard about the problems that different founders face. The advice was very useful.

I went to a few talks, but I’ll cover three to keep it short.

~~~~~~~~~~~~~~~~~~~~~~~~~

One superstar at TiEcon was Steve Blank, who originated the methodology that launched the Lean Startup movement as described in Eric Ries’ “The Lean Startup.” The core message is to start small, get out and talk to your market and build what customers actually need and want.

Startups are not small versions of large companies. They are in search of business models that work. Large business on the other hand execute strategies.

Steve mentioned a book with pictures called “Business Model Generation” for people who want to build a startup. I’m curious.

In a startup you build things that get you the maximum learning. Before you fire execs, it is a good idea to fire the plan and try another.

Startups are under a lot of pressure. They think in terms of their burn rate and their runway.

Startups should ideally plan on discovering a businesses that works. An exit should be the last thing on their mind.
The reasons people acquire a startup are:

  • An existing product, e.g., whatsapp
  • P&L and good cash flow.
  • Technology: Oclulus
  • Acquahire — when they want the developers, but for something different.

Startups have a different culture. Assimilation into an existing business can wash out the productivity because the processes in place for execution are different from innovation, i.e., Key Performance Indicators (KPIs)

~~~~~~~~~~~~~~~~~~~~~~~~~

A panel discussion: How not to mess up the cap table

The cap table is the definition of who owns the company and their rights. It typically defines the stock holders, the debt holders and the liquidation preferences (who gets cash before whom).

A VC mentioned an interesting incident where he killed a company by asking who owned it. The founders got into a fight and decided not to form the company!

It is also a good idea to have a vesting schedule so that one of the founders doesn’t “… go to Brazil with his wife with his share of the company while the others work for their equity.”

20% of allocation of stock is usually based on role of people in past; the rest is about future.

Standard vesting for employees is 4 years.

Investors get preferred stock, because they want to get their money back first. This is changing with Y-Combinator’s SAFE and Founder Institute’s Convertible Equity ideas. Another reason to be careful is that option pricing would be set by investors if they take preferred.

The things to worry about in a funding round are:

Valuation: No one forgets this. Clearly, the higher the better.

Control: Who controls the board seats and voting rights. This is tricky because rights and seniority affect the way people think.

Rights: What special right do investors get, such as a board seat.

Seniority: Who gets their money first.

Founder rights: How can founders be removed from power? Typical statement is a felony., but you could ask for “willful and persistent gross negligence.” It is also important to negotiate severance as a part of this deal.

There is a difference between preferred and non-preferred stock. Preferred allows double dipping. Investors get their money back and then some more of the stock.

Usually investors own 25% after first round.

The difference between negotiation and begging is leverage. Get a few investors to land at the same time and you are in a much better negotiating spot.

An important decision is to file the 83b election within 30 days of getting equity. The founder will be required to pay taxes on the portion of equity that vests if this is not filed. This likely involves a cash flow mismatch because the founder may not have liquid cash when the equity vests. 

For more information read Founder’s Workbench 83 (b) Election

Other common mistakes startups make include:

… not having a clear focus.

… compensating people and getting clear ownership of code written for the company.

There are two options: the pain of disappointment or the pain of discipline.

~~~~~~~~~~~~~~~~~~~~~~~~~

EXITS

The best time to plan to exit is as early as possible.

Early thought can include, Are there going to be a lot of companies that will be interested. Is it a good IPO idea?

Ashmeet Sidana says there are two exit scenarios.

… Approached for an exit.

… Or things don’t work out.
A banker or a business relationship usually leads to an intro for these.

Lots of teams are typically involved in exits. The deal team will work on the deal. CPAs, lawyers and wealth managers are usually involved.

Then there is the question of what happens to the cash. Typically people use trusts to allow continued investment and avoid a steep tax. This also allows for a tax shelter for money designated for charity.

Exits are most intense periods. Cases where board meetings happen every 3 hours are common.

Think also of what to do next after the vacation at the end of the deal.

Where does the money get wired?
At the time the M&A term sheet is signed the probability of acquisition is 40%.
In contrast the probability of funding is 80% in VC rounds.

Time can kill deals in M&A. However clarity is important as well. A CEO once took time to work out every detail and the final deal was very close to the term sheet.

Ask what is the reason people are acquiring the company? Alignment is important. Avoid conflicts of interest at this critical time. Try to create a separation from noise in the markets.

Founders should negotiate to get some liquidity early to pay for costs.

Image credit: Alpha Sangha

Entrepreneurs: Lessons From Founder Showcase

Thursday, May 14th, 2015

Ajo Fod

Today I attended The Founder Showcase.

There are a tremendous number of companies looking for access in the space of early ventures. It is hard to compete against all the din.

This year’s Founder Showcase included a few dozen interesting companies at the booths. So it is not strange how even a very sophisticated and advanced companies can get overlooked.

So, what do venture capitalists look for?

Each level of the selection process for a startup is brutal in its selectivity and uses a different filter. The filter applied at the Founder Showcase was one of popularity. This induces biases that businesses and investors wouldn’t have.

One  start-up, Quarrio, was the only company using AI to solve a hard problem – one of making data in tables accessible using plain English. It is a usable and complete product relative to others at the showcase. It was filtered out of the pitch competition.

The pitch competition included a selected few companies:

  • Makerblok: Making educational electronics for children.
  • Ampl: A bag that can charge all your devices so that you don’t have to worry about charging each device. Is cool but is too heavy.
  • Theo: MLS quality data (much more accurate in price compared to Redfin). Also there is an argument that there are many features/amenities that Real Estate agents desire.
  • keepe: This is a startup based in Seattle offering handyman services guaranteed in 1 hour.
  • Trato: This company serves up customizable legal documents to make it easier for the masses to do business.

The members of the VC panel are listed here.

On the Problem: VCs generally want to know how much pain is there in the problem. Who faces the pain and how much the solution removes the pain. How big the market is. 

Solution: They need to know how the startup solves the problem. How credible the solution is. If there is a technical moat around the solution. Sometimes the moat is market share. If so the biggest advantage is swift execution.

Scaleability: Building connections one at a time is hard. There has to be a plan to reach people quickly. There is a lot of noise around. There should be a plan to get the business past the noise.

Capital intensity: The question here is how much money needs to be invested in the solution before it starts cash flowing. High capital requirements increase the risk.

Team: Investors look for teams when investing. Teams increase stability and credibility. A team with a background in their field of expertise is more likely to create a moat of competence. Similarly a team that has worked together for a long time is likely to work well.

Generosity: Kickstarter is another example of a generous startup that has succeeded by making many other people succeed.

A life-sciences called Suntowater was voted the best in this Founder Showcase event overwhelmingly by both the crowd and the judges. It solves the problem of clean drinking water from the humidity in the air using electricity generated by a solar panel. This innovation is considered generous because it is most useful to the underdeveloped world.

The general recipe for a successful startup is to relate to people, then promise a great future and connect the dots.

Chamath Palihapitiya, Founder of The Social+Capital Partnership, had great insights to share about the makeup of a wildly successful startup in the future. One source of information is the trend in the tastemaker in society.

In an earlier era individuals and companies paid a lot to get attention from consumers through selection by the tastemaker: companies such as AOL who rented their landing page for millions or radio stations that chose the music to be played.

Now the mechanism of taste selection has become “likes” on Facebook where everyone has a say. The downside of this mechanism is the noise. Facebook is likely to face creative destruction as the pendulum swings.

Chamath thinks that the next generation of companies will have multiple lightly curated channels either selected by humans or by algorithms. An example is Patrion, where people support the art they like, similar to Italy during the Renaissance.

Fixing education is an interesting problem. Linda frames education as a way of learning skills. This is more enlightened than the idea of education for its own sake. Startups that solve a problem can expect better reception.

In the past software giants like Microsoft and Oracle were dominant.

There has been a shift towards SaaS.

The next shift is expected to be towards outcomes as a service such as Uber.

For the investors, Warren Buffets letter to shareholders says that he sat on money for over 1/3rd of the time.

Chamath expects a funding hiccup in 2-3 years. Many companies are raising a lot of money in the current bubble. The easy money has to end at some point. 

Companies that don’t have a sufficiently good product to market fit will suffer. But it’s mostly their employees who have given up pay to get stock options who will lose big.

Chamath’s advice to entrepreneurs is to raise money when the going is good and sit on it till the company figures out a good product to market fit.

Did you know that Peter Diamandis didn’t have 10M$ when he announced the 10M$ prize? Nobody asked about the money since he cleared the line of credibility. He had astronauts and the NASA chairman beside him when he made the announcement. Strangely, the winning team spent about 30M$ to earn the prize.

So, where did the money come from?

Peter approached about 150 people who declined to fund the prize. That is a lot of rejection!

Richard Branson declined to fund twice. After a lot of insecure moments, they found that there is insurance against unlikely events that could cover this event.

A private company going to space was considered unlikely, so he was offered a $3M premium to insure against the outcome. He negotiated it down to a 50k/month premium. Then it was a question of finding people who would support the bet on a monthly basis.  This spreads the pain out, but it lasted for ever.

Richard Branson marched in weeks before the prize was won with an offer of $250m to commercialize the winning tech so that he could have his picture taken with the winners.

… and that is how Venture Capital works.

Image credit: Alpha Sangha

Entrepreneurs: FinTech at Trading Show West Coast 2015

Thursday, March 12th, 2015

FinTech, the wedding between finance and technology, is a hotbed of startups and innovation, especially in London. Now it’s lighting the fires of the investment community in Silicon Valley, so I prevailed on Ajo Fod, who knows the FinTech world well, first as a quant and now as an entrepreneur, to attend the Trading Show and share his observations with you.

Ajo FodI had the pleasure of attending Trading Show West Coast 2015: West Coast’s leading quant, automated trading and big data event last week. This is one of the most legitimate trading shows I’ve seen and truly geared to professionals.

The first thing that caught my eye, was the surprisingly large majority wearing business attire; I was expecting some confusion. Google tried to hold down the fort of casual-at-work and a few people were dressed in jeans, with long-sleeved shirts for good measure.

But finance won over West Coast causal even in San Francisco. My decision to dress in a brown suit and a tie was just the right measure down from full business dress.

I was impressed by the balance between different groups of professionals. Quants / traders / investors / hardware / risk management and students were all well represented.

Different scales of enterprise from startups to micro hedge funds to medium sized funds, such as AXA Rosenberg, to industry titans like BNY Mellon Financial and Blackrock were there, too.

The mix of speakers, from hardware tech providing fast access to markets to macro thoughts from Lex Huberts, was good, especially considering the audience.

Systematic trading and HFT is no longer about the fastest execution. The marginal advantage from trading faster needs to be weighed carefully against the cost of the infrastructure, while the ability to forecast farther into the future is significant.

Apparently, the fastest access to markets is provided by Algo Logic. They sell machines that race the path from tick data reception to placing trades in 1.2micro seconds!

They achieve this by storing the logic in hardware in FPGA (field-programmable gate array). They include trading logic and risk checks on the chip to achieve this kind of reaction time.

The speed is used to grab favorably priced orders before anyone else can. The winners at any speed tend to be the ones with higher algorithmic sophistication. The direction of development in this field tends to be about adding computing power to the FPGA.

The discussion on Co-location vs Cloud Servers focused on the tradeoff between speed and algorithmic sophistication.

Pravil Gupta of Quadeye Trading and Bert Shen from SuperMicro are both suppliers of HFT technology. The difference is that one is about more sophisticated but still very fast trading while the other is at the higher speed end of the spectrum.

Speed is not everything in the HFT world. The incremental speed edge costs significantly. While there will always be fast traders that grab obviously mispriced orders over a short time horizon, others will play the game of taking the not so short-term bet.

The roundtables covered a list of varied topics. As expected the round table audiences in the Bay Area were largely focused on state-of-the-art in Big Data and deep learning.

These technologies could be the future, but I don’t see as much profitable application of these technologies as there is hype.

FinTech startups seem to be numerous in data services for the finance industry. iSentium: works on estimating the sentiment of tweets. Another works on interpreting SEC filings. Strategies are being fed information faster to produce more efficient markets.

The past was a speed race. The future is going to be about more information used in smarter ways.

For example, Alpha Sangha, my startup, combines information from a variety of data-sources using complex models/algorithms that maximize profitability while filtering out noise.

Acronyms come and go, so here are three relatively new ones stay aware of.

BRIC : Brazil Russia India China
MINT : Mexico Indonesia Nigeria Turkey
ESG: refers to the three main areas of concern that have developed as central factors in measuring the sustainability and ethical impact of an investment in a company or business

Ajo Fod is the founder of Alpha Sangha, which helps companies optimize complex forecasting models or algorithms based on large quantities of past data while avoiding the common pitfall of noise. They can further increase profitability by mining for model/algorithm variants that are better fits based on historical data.

Ajo previously worked as a quant at BGI/Blackrock and Mellon. He has masters degrees in both Computer Science (AI) and Operations Research (optimization). He earned a BTech degree from the prestigious IIT-Madras.

Ducks in a Row: Retro Culture of Introductions

Tuesday, March 10th, 2015

https://www.flickr.com/photos/61215754@N05/10606798213

For centuries the most important information upon meeting someone new was where were they from and who was their family.

Once that was known the involved parties would be able to figure out how they were connected; crucial information in order to do business or move forward with any kind of relationship.

Then World War II and the post war automobile culture changed our social structure forever.

Strangers met, formed businesses, fell in love and married — all without the introductions and recommendations of family, friends or other associates.

Fifty-plus years later we have reverted to our previous attitudes regarding introductions — now based on professional/personal networks, social media and the crowd-sourced opinions of strangers.

After attending a fintech conference (see his upcoming post Thursday) Ajo Fod, founder of Alpha Sangha, left a comment on KG Charles-Harris’s post regarding the help that entrepreneurs really need.

The most effective resource at this point in my start-up is introductions to the right people. Meeting them directly doesn’t seem to have the same effect as an introduction.

Entrepreneur of not, what can you do to offset a lack of introductions?

Here is what I told Ajo.

You are right in your analysis that the best connections are the result of introductions and this seems especially true when it comes to investors.

Partly it is a function of trust, i.e., I trust you because I trust the person who introduced us, which is ridiculous as I wrote in Who Do You Trust? in 2008 and KG touched on a couple of years ago in If the Shoe Fits: Facing Reality.

Beyond repeating what you already know, such as working your network, finding connections, etc., I suggest that you put part of your focus on developing your peer-and-below network, not just those who can directly help, by reaching out and helping them. One way to accomplish this is by responding on forums like Quora.

Use your expertise to build your visibility, so that even with no intro you will be a more known quantity when they google you.

Not great, but you have to start somewhere.

Image credit: George Tims

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