angel investors as hybrid unifiers

Investors thrive on social validation and follow trends. Innovators thrive on social invalidation and create trends. How can such completely different mindsets meet in the middle and cooperate for a common goal? Leaps of faith? Heaps of information asymmetry? Well, the real answer lies in the existence of a hybrid class of creatures called the angel investors, the most successful of whom are usually entrepreneur-turned-investor types.

Social Decoupling

Since angels manage their own money, they can more easily decouple themselves from the societal expectations, make independent decisions and stay away from consensus driven homogeneities.

Lastly, consensus frequently kills the outliers. Within venture firms, there are countless examples of firms passing on seed-stage deals because they were crazy ideas and consensus didn’t exist, only then to watch them grow into unicorns. Nearly a decade ago, Atlas changed its approach to seed investing in that any individual partner could back a “seed deal” (size delimited) without consensus support. This empowered partners to take some risk. As those investments mature, we generally move towards a team consensus as capital intensity increases. But at the earliest phases of the decision process, when uncertainties are high and getting to consensus could prevent leaning forward into a “risky” seed, we think this approach works.

Bruce Booth - Biotech Startups And The Hard Truth Of Innovation

Contrarian Spirit

Since angels are usually tech entrepreneurs themselves (or were so in the past), they can more easily resonate with the early stage ambiguities and challenges facing an entrepreneur, and be generally more accepting and tolerant. For the same reason, they also exhibit the most contrarian behavior among the investor folks. In fact, they like the cutting edge so much that they actually stay away from the existing trends. They like being right while others are wrong. In other words, they care for a particular kind of social validation. General public does not have the intellectual sensibility required for the epistemological jealousy they are after, but the other angels do. That is why angel investing thrives only in communities.

From the outside, angel investing may look like it’s motivated simply by money. But there’s more to it than that. To insiders, it’s more about your role and reputation within the community than it is about the money… No one can really predict what startups will succeed or fail, no one can really predict what trends are real or illusions, to any genuine degree of confidence. But everyone has to get up every morning and put on a bit of a show: that you are perceptive, you are brilliant, you are contrarian, and you are right.

Alex Danco - The Social Subsidy of Angel Investing

Note that this is not about being contrarian per se. You need to be both contrarian and correct. So angel investing is a stressful affair. It is one of those jobs that most people would not do just for money. That is why angels are given almost the same heroic treatment as entrepreneurs.

Domain Knowledge

Since angels are not restricted by any investment mandates, they can freely explore the edge cases. More importantly, due to their past entrepreneurial experience, they tend to have deep domain expertises that generalist investors by definition lack. Their backgrounds and their networks allow them to significantly de-risk their positions.

Remember, risk is in the eye of the beholder. As a company matures its risk profile becomes more quantifiable, but at the very early stages, its risk profile is very qualitative and resistant to the formulaic approaches thought in business schools. The ideal investor profile required for each early stage company is actually different. That is why (again) you need a whole ecosystem of angels who can handle different types of investment theses and entrepreneur teams. (Personality match is also important.)

I like to picture the dynamics in the tech investment world as follows. There are certain individuals, called entrepreneurs, who are far ahead of the general public. The first tenuous link these people establish with the society is through angels who collectively act like an umbilical cord. As the company matures and passes the test of time, increasingly bigger and increasingly more conservative investors step in to help with the actualization process. Finally, at the very end, the risk profile of the company becomes ready to merge with the general public via an IPO. (Tech companies used to IPO a lot earlier but this was primarily due to the immaturity of the private capital ecosystem. I believe that it is financially more natural and morally more appropriate for these companies to meet the public later in their life cycles.)

blockchain and decentralization

As with every transformative technology, blockchain has started off a long creative destruction process. (Think of how invention of electricity changed everything.) This time around though, the destruction part is much more palpable than the creativity part. Blockchain's infrastructural nature makes it hard to predict what sorts of profitable business models will be built on top of it in the future, but its decentralizing nature has already planted fear into the hearts of some of the world's most profitable companies that have thrived by centralizing and gating certain aspects of ourselves. (Think of how Facebook is trying to own our social selves.) The reason behind the fear is that decentralization always equilibrates towards market structures with zero producer surplus. (Think of how yellow-pages got pulvarised as internet became more widely adopted.)

But there is still a lot of hope for centralization fans! Just look at what happened at the currency front which turned out to be the killer (popularizing) application for blockchain technology. (Lighting was the killer application for electricity technology.)

• Bitcoin became by far the most dominant crypto-currency.
• Bitcoin mining operations are now concentrated in the hands of few producers.

How did these two centralization processes take hold? Was not blockchain supposed to liberate us from all centralizations? Well... We should not forget that the unfolding of a technology itself is an economic process subject to usual laws of economics. The above centralization processes took hold respectively due to network and scale effects. That is how removing one centralized node (central bank) in the network created new centralized nodes elsewhere.

In some sense, we are in a much worse paradigm today. At least when currencies were defined by national boundaries, we had many of them. Today we basically have one giant monolithic crypto-currency! 

What happened basically is that we reinvented gold in a much worse form. (Just like how Facebook ended up reinventing TV in an even more addictive form.). At least, the scale effects at gold mining operations had taken longer to crystallize due to the physical nature of the operations!

Bitcoin enthusiasts generally tend to be naive economists. They can not even see that fiat currency was actually one of the greatest inventions of mankind, giving us a previously non-existent control over the money supply. (For instance, increasing the money supply during times of crisis and decreasing it during times of exuberance help us ease the severity of business cycles.)

Blockchain itself though (the underlying technology behind Bitcoin) has unleashed a wave of great economic thinking (and creativity). People are getting wiser about economics. They are realizing that the notion of "value" goes far beyond "money", that a lot of seemingly non-economic transactions are actually economic in nature. Now all they have to do is to render the invisible trust tokens visible by launching blockchain startups.

structural flows and vertical integrations

Just like there is a deep relation between the network structure of neurons and the subsequent dynamical flow of information around them, there is a deep relation between market structure and profit flow. 

Think of each supply chain as a vertical stack where each stack manufactures the inputs used at one higher stack. For instance, one stack may have ten different type of inputs from the stacks below itself (in different supply chains) and each input may be generated inside either a monopolistic, an oligopolistic or a competitive market conditions. (Supply chains intersect at stacks where more than one input are used to generate a single output.)

Profit of the whole supply chain is capped above by the consumer value assigned to the final product and below by the total cost of production of the entire chain. Now think of the thickness of each stack as the amount of profit captured by that particular stack. Visually, what happens over time is that the whole chain dynamically flexes as the total amount of profit and its internal distribution evolve. These dynamics are mainly shaped by the (ever-changing) market structures at each stack. For instance, a monopolistic stack can easily suck profits from the stack above by charging a higher price for its output. (Of course, a higher price also results decreased demand but the monopolist has the luxury to optimize this trade-off.) A monopolistic stack can flex its muscle downwards as well if the output of a stack below is not utilized elsewhere in the economy.

Each company exists inside a supply chain and one reason why companies try to become vertically integrated is to minimize the uncertainties entailed by the ever-evolving profit distribution across the chain. Of course, in practice, most vertical integrations are done for the wrong reasons. For instance, companies often extend themselves into neighboring stacks that have long become commoditized and effectively stabilized into a no-profit equilibrium due to extreme competition. Also, generally speaking, the uncertainties are best addressed at the financial (investor) level rather the operational (manager) level. That is basically why investors like to conduct portfolio optimization with pure plays only. (Part of the uncertainty that can never be eliminated by portfolio optimization methods is called systemic risk in finance jargon.)

Companies routinely launch attacks against monopolistic stacks by funding open source projects, antitrust lobbying activities, meanwhile merging with other behemoths in order to become monopolies themselves. They also occasionally reach out horizontally across to the neighboring supply chains. For instance, in order to increase how much the stack above can pay for their output, they try to find ways to decrease the prices of the complements of their output. (Remember the stack above needs to combine several inputs, including your output. The less it pays for the other inputs, the more it can pay to you.)

When a pioneer startup is building an entire new supply chain from scratch, it has no choice but to own the entire chain since everyone else is far behind it in terms of understanding the contents of what is emerging. Of course, no single company can do a high-quality job at each stack in the chain. Sooner or later, other (more-focused) startups join the game by claiming certain stacks. The pioneer startup has the first-mover advantage of having visibility over which stacks are worth defending. (Of course, it is never easy to focus an already over-extended company.) As the new supply chain matures, the number of players at each stack proliferates and the robustness of the whole supply chain increases.

risk, luck and naiveness

If risk is what happens when you make good decisions but end up with a bad outcome, luck is what happens when you make bad or mediocre decisions but end up with a great outcome. They both happen because the world is too complex to allow 100% of your actions dictate 100% of your outcomes. They are mirrored cousins, driven by the same thing: You are one person in a 7 billion player game, and the accidental impact of other people’s actions can be more consequential than your own... Risk doesn’t care about how much effort you put into something, and neither does luck. Both just show up, unannounced, eager to humble you. The only difference is that risk humbles you as soon as it arrives, while luck humbles you down the road, once it vanishes, leaving you with only the memories you shared together.

Morgan Housel - Ironies of Luck

Let us define people who believe that all good outcomes come from good decisions and all bad outcomes come from bad decisions as naive. 

Naive and lucky people (people who are lucky but do not know that they are lucky) systematically overestimate the upside potential of their good decisions because they can not see that a portion of their good outcomes are coming from their bad decisions. Consequently they feel like they can take bigger risks. At some point their luckiness can no longer compensate for their increased risk taking and their returns collapse back to a state of normalcy where they either make big gains or big losses.

Naive and risk taking people (people who take risk but do not know that they are taking a risk) systematically overestimate the downside potential of their bad decisions because they can not see that a portion of their bad outcomes are coming from their good decisions. Consequently they feel unlucky. They scale back their risk taking behavior and their returns collapse back to a state of normalcy where they either make small gains or small losses.

So you need to know thyself and shed your naiveness away in order to sustain the positive returns due to luck or risk. (Remember that each person tends to be naive in a different way.)

belief, trust and finance

Fundamentals of finance are taught wrongly in schools.

• We do not trade future cash flows, we trade beliefs about future cash flows. (See the old blog post misconception of wealth) When beliefs are completely aligned and future cash flows assume an objective quality, it is no longer possible to make a profit and financial interest disappears.
• We do not operate in legal frameworks, we operate in trust frameworks. Only when the shit hits the fan does the legal framework surface, and when it does, you are no longer in the domain of finance.

herds and trends

Apparel retailers herd around emerging fashion trends in order to minimise their piles of unsold garments. Venture capitalists cluster around emerging technology trends in order to maximise their chances of catching extreme returns.

Both cases are driven by fear and uncertainty. Both result in sameness and competition. While retailers are shaken by the volatility of taste, investors are befuddled by the complexity of creation.

büyüme hırsı ve karaktersizlik

Yatırımcılar büyüme görmek isterler. Vizyon çok da umurlarında değildir. Rakibiniz büyüyor mu, şu an sizin de hemen büyüyüp ona yetişmenizi beklerler.

Twitter'ın ölümü bu baskıdan ötürüdür. Facebook gibi herkese hitap etmek adına ürün zamanla karaktersizleştirildi ve esas kullanıcılar platforma küstürüldü. Oysa Twitter sosyal medyanın belki de en değerli ve eğitimli kitlesine hitap ediyordu.

Sosyal ağlar da insanlar gibidir. Herkesi mutlu etmeye çabalayan biri hakkında ne düşünürsünüz? Ben şahsen karaktersiz olduğunu düşünürüm.

Snapchat'in çizgisini bozmamasını, yetişkinlere de hitap edeceğim diye çırpınmamasını son derece vizyoner buluyorum. Uzun dönemde sadece bu şekilde kitleleriyle ve duruşlarıyla ayrışan platformlar ayakta kalacaklar.

diversification reflex

Risk selection is not about blind diversification, it is about right kind of diversification.

At Urbanstat, once we geocode our clients' policies, the resulting geographical visualisation dazzles the risk managers who have been thinking in the tabular format for years. Rightly so, they feel as if they have been blind for years. 

Their first reaction often has to do with how the company can finally handle their diversification goals more accurately. Now that they can see everything on a map, they can modify their sales goals to create the perfectly-uniform geographic distribution they have been after.

Of course, this uniformity business is exactly the opposite of Urbanstat's thesis. The whole point of our geographical approach is to bring out the unseen non-uniformities and help insurers adjust their portfolio allocations accordingly.

Blind diversification works well only after all the known unknowns are factored out. Left with the remaining unknown unknowns, there is in fact nothing to do but to distribute all the bets evenly.

Everything else being equal, the density of bets in a certain region should be lesser than the one in a less risky region. After all why assume greater risk for the same price unless all the sale opportunities in the less risky region are exhausted?

search engine objectification

In financial markets, as the fund under your management grows bigger, it becomes increasingly harder to beat the market because you become the market itself. Of course, when you are the equation, analysis become impossible and loss of objectivity is immediate.

A similar observation holds for the search engine market. Google has become such a dominant player that now it is impossible to tell whether a site is inherently popular or popular due to Google itself. When internet browsing starts and ends with Google, Google ends up running its algorithms on itself and creates strong positive feedback loops.

There is another reason why search engine market is losing its objectivity. When you are as big as Google you can not keep anything secret. Google's search algorithms are under such an intense scrutiny that there is now a whole new industry that helps companies optimize their Google visibility. When you define success in a formulaic way, people will hire experts who engage in the dark art of fooling your metrics. There is no surprise in that...

There is only one hope to bring back objectivity to the search engine market: Give the power back to the people. Reputation and popularity are inherently social concepts... Just focus on the dynamics and semantics of social media exchanges, whoever does not will always be behind the curve.

the terminal broker

An arrow r from A to B indicates that B is in relation with A via the channel r.

Assume that our category is concrete. (i.e. each object is a structured set) Let the size of the set Hom(A,B) indicate the depth of the relationship B is in with A.

A broker has relationships with everyone. However, each of these relationships is as superficial as possible. (After all he only cares about business and has only a finite amount of time in his hands. Let us not forget that time is money!) Of course, client A may be delusional and thinking that his relationship with his broker B has some depth to it. In that case, the broker has done a very good job! (Is not the propagation of such a delusion the dream of every public relations person?)

Most successful broker is a person 1 such that Hom(A,1) is one element set and Hom(1,A) is bijective to A. In other words, he knows everyone "minimally" and is liked by everyone "maximally". Such a broker is not only a terminal object of our category, but also represents the forgetful functor from our category to the category of sets.

Such objects exist in categories like Set and Top, but algebraic categories have no tolerance for them. In algebraic categories, the terminal object is often the one-element algebra and the representing object for the forgetful functor is the free algebra generated on the one-element set. So these two objects differ... In some sense, algebraic categories have separation of powers: If you know everybody minimally, then you are not allowed to be liked by everyone maximally (and vice versa).

A jerk on the other hand is 1 such that both Hom(A,1) and Hom(1,A) are one-element sets. In other words, he knows everyone, but nobody really likes him. They avoid him as much as possible. Such a broker is called a zero object, a very suiting name indeed...