StreetEYE Blog

Quantitative Fun With Fund Names

Word cloud

There are a number of hard problems in investing, for instance:

    1) Finding alpha.
    2) Finding clients and assets — especially if you can’t 1) consistently find alpha.
    3) Finding an awesome name for your fund.

The investing blogosphere is all over the first two. Now, for something completely different, we help you with the last one! Inspired by Sloane Ortel’s post, we’ll run some analytics on a dataset of investment firm names, culminating in our very own algorithmic fund name generator.

Assembling data from various sources, scrubbing and deduplicating, we built a set of about 20,000 names.

As a warmup, here are the most frequent words found in company names:


The most frequent bigrams or 2-word combinations:



Word2Vec is an algorithm which, given a corpus of text, maps words to vectors of floating-point numbers, magically distilling syntactic and semantic attributes of each word.1 Vector representations of words are used for machine translation, sentiment analysis, intelligent personal assistants like Siri and Alexa, and other natural language processing applications. Word2Vec word vectors can be uncannily accurate in representing meanings and relationships between words.

We could train our own vectors, but this is not a large corpus, and there are many pre-trained vector sets based on the Web, Wikipedia, different languages and corpora. Let’s load the set of vectors trained on Google News, map our frequently used words, and cluster them.

Cluster 0 (522 words)
[‘management’, ‘partners’, ‘co’, ‘services’, ‘global’, ‘international’, ‘research’, ‘new’, ‘national’, ‘mutual’]
Cluster 1 (444 words)
[‘inc’, ‘sa’, ‘hong’, ‘kong’, ‘de’, ‘al’, ‘deutsche’, ‘nv’, ‘ma’, ‘adv’]
Cluster 2 (545 words)
[‘life’, ‘fidelity’, ‘golden’, ‘royal’, ‘legacy’, ‘millennium’, ‘beacon’, ‘fortune’, ‘republic’, ‘heritage’]
Cluster 3 (336 words)
[‘capital’, ‘investment’, ‘asset’, ‘wealth’, ‘investments’, ‘holdings’, ‘fund’, ‘financial’, ‘company’, ‘ag’, ‘funds’, ‘trading’, ‘markets’, ‘investors’, ‘managers’]
Cluster 4 (180 words)
[‘pacific’, ‘north’, ‘creek’, ‘river’, ‘west’, ‘sun’, ‘south’, ‘northern’, ‘summit’, ‘ridge’]
Cluster 5 (150 words)
[‘eagle’, ‘tiger’, ‘lion’, ‘falcon’, ‘wolf’, ‘arrow’, ‘peregrine’, ‘owl’, ‘fur’, ‘fox’]
Cluster 6 (223 words)
[‘street’, ‘hill’, ‘estate’, ‘park’, ‘property’, ‘square’, ‘spa’, ‘lane’, ‘bridge’, ‘road’]
Cluster 7 (656 words)
[‘asia’, ‘uk’, ‘singapore’, ‘canada’, ‘pvt’, ‘japan’, ‘india’, ‘morgan’, ‘europe’, ‘australia’]
Cluster 8 (725 words)
[‘limited’, ‘holding’, ‘the’, ‘first’, ‘real’, ‘point’, ‘us’, ‘blue’, ‘one’, ‘old’]
Cluster 9 (237 words)
[‘alpha’, ‘amp’, ‘matrix’, ‘quantum’, ‘meridian’, ‘sigma’, ‘dimensional’, ‘constellation’, ‘symmetry’, ‘parametric’]
Cluster 10 (106 words)
[‘china’, ‘rock’, ‘stone’, ‘silver’, ‘kg’, ’emerald’, ‘steel’, ‘gold’, ‘diamond’, ‘mill’]
Cluster 11 (207 words)
[‘oak’, ‘tree’, ‘brown’, ‘wood’, ‘cypress’, ‘pine’, ‘harvest’, ‘grove’, ‘cedar’, ‘maple’]
Cluster 12 (1413 words)
[‘llc’, ‘ltd’, ‘lp’, ‘pte’, ‘pty’, ‘corp’, ‘gmbh’, ‘shanghai’, ‘hk’, ‘ubs’]
Cluster 13 (108 words)
[‘harbor’, ‘compass’, ‘banca’, ‘marine’, ‘spinnaker’, ‘anchorage’, ‘shipping’, ‘port’, ‘motor’, ‘mariner’]
Cluster 14 (276 words)
[‘advisors’, ‘group’, ‘advisory’, ‘private’, ‘corporation’, ‘trust’, ‘associates’, ‘counsel’, ‘consulting’, ‘advisers’]

We distinguish clusters related to countries, geographical features, animals, trees, minerals and materials, nautical concepts, scientific and financial concepts, positive metaphors like ‘fidelity’ and ‘heritage’.

Plotting popular words from each cluster, and connecting words that are frequently co-located in the same firm names, we get


We can explore related words using Google’s Embeddings Projector, which generates 3D images of word relationships that look like this:

Embeddings projector

  • Click on the link for the embeddings projector, wait for it to load the data.
  • Start entering a word at top right to search for it
  • Select the word you want in the list that gets populated
  • Click “Isolate data points”
  • Drag the image around with your mouse to see related words
  • When you’re done, hit “Clear selection”

It’s a bit like taking a word and algorithmically free-associating similar words that are used in fund names.

Finally, we can train a machine learning algorithm to automatically generate realistic-sounding new names based on our corpus! Use this link or the form below to generate names based on a starting string (or leave blank).

Some names may be similar to existing names in the corpus, which are the property of their respective owners.

Other names are a bit random…use them for inspiration for your next corporate entity…or if you need to generate random realistic-looking text for testing purposes or to fool a spam filter. We make no representation about the regulatory compliance, appropriateness, or marketing value of generated names!

The code is here.

We hope this will free valuable time from the fund naming problem to let managers focus on generating alpha.

1 How does Word2Vec work? It’s like a Netflix movie recommendation system, but for words. The Netflix recommender maps each user and each movie to a vector. It tries to find

1. A vector to represent each movie and
2. A vector to represent each user such that
3. When you multiply those two vectors, you get a number that predicts how the user will rate the movie.

As users rate a lot of movies and the system trains and improves the vectors, different vector components start to represent movie features, like action-adventure, rom-com, scifi, etc.

Now to see how Word2Vec assigns vectors to words, substitute the statement ‘user u likes movie m‘ with ‘the word goldman frequently occurs in same context as the word morgan‘.

By using a large corpus to train vectors which predict what words arise in similar context, we arrive at vectors that represent a sometimes-shockingly complex knowledge about each word, bordering on understanding. For instance, we might find that the word vector closest to ‘Paris’ – ‘France’ + ‘Germany’ is ‘Berlin.’ In other words, Word2Vec in some sense understands that ‘Paris is to France as Berlin is to Germany.’ This post is a good intro.

2 Computer-generated names are generated as follows:

  • Split each firm name into all its initial substrings.
  • Identify the character following each substring. In other words, for “Wiley E. Coyote Investment Management”, generate pairs like
    (‘Wile’, ‘y’)
    (‘Wiley E. Coy’, ‘o’)
    (‘Wiley E. Coyote Investment Managemen’, ‘t’)
  • Use these pairs as a corpus to train a recurrent neural network to predict the next character following an initial fund name substring.
  • Get like 75% accuracy – RNNs are unreasonably effective, or language is surprisingly predictable.
  • To predict, seed the algorithm with a chunk or an empty string, predict the following character.
  • Add the predicted character to the end of the string, predict with the resulting chunk.
  • Get a large number of silly names that resemble the training corpus, with some randomness added.

The Bitcoin crash is coming

Bitcoin inventor Satoshi Nakamura closely monitors the launch of Bitcoin futures (photo via @vexmark)

In the land of milk and honey
You must put them on the table

You go back Jack do it again
Wheel turnin’ ’round and ’round
Steely Dan

I’m a bit of a Bitcoin skeptic. I think it’s a bubble and at some point the dancing stops and some folks get left holding a very very virtual bag. If you’re one of those who thinks the real bagholders will be the ones owning dollars in the ‘legacy financial system’ after the advent of millennial kingdom come, you can stop reading.

Nevertheless I’m very bullish on blockchain. Maybe we’ve barely scratched the surface and it will be as ubiquitous as the Internet.

Cutting to the chase, I think $10,000 is at the high end of plausible valuations. If Bitcoin is a manipulated market, which may be the case, this week’s launch of Bitcoin futures could very well pop the bubble and crash the market. Because for the first time, you can have real price discovery from smart money, that can bet big, go short in any size at any price where it can find a counterparty, and doesn’t have to worry about counterparty risk, custody w/cybersecurity etc.

Futures could also turn out to be a debacle with no institutional interest, no clean basis arb between ‘physical’ and futures, no arbs, no volume, shenanigans bringing the contract into disrepute (See also Craig Pirrong, the Streetwise Professor and Nassim Taleb).

But wouldn’t it be ironic if futures cost less to trade than Bitcoin on the blockchain with better liquidity, less risk? Maybe you actual need brokers, exchanges, central clearing, daily settlement, custody, credit, margin, in order to have a complete, safe market? Who knew?

Somehow, Bitcoin manages to be slower and more expensive to trade than ‘legacy’ trading venues, with none of the liquidity or mitigation of sundry operational risks. Not to mention that recurring staple of Bitcoin news, the record-breaking heist.

Turns out the devil is in the details of market structure. The magic of the blockchain notwithstanding, most Bitcoin trading may take place off the blockchain and look a lot like traditional financial markets.

If Bitcoin is not a manipulated market, maybe the bubble has farther to go. But how much farther, realistically?

If Bitcoin is a currency, then compare its current ~$300b market cap to pre-QE USD base money of ~$1,000b. Seems like a lot for a ‘currency’ that has minimal legitimate real-economy transaction footprint, vs. something that ran a then-$14t GDP economy backed by nukes and aircraft carriers. Actually, an order of magnitude more real-economy transactions throughout the production chain, plus a lot of black-market and foreign transactions that don’t show up in GDP, and never mind financial transactions.

Demand for a currency as a medium of exchange is a function of the real-economy transactions it enables.

Of course Bitcoin is the most obvious bubble ever. And the bubble makes it risky for real economy transactions. Everyone who ever spent 10,000 BTC to buy a cheese pizza is crying in their beer now. Until volatility settles down, people will be reluctant to transact with it and tend to hoard it. That’s what deflation does. If your currency will buy more tomorrow you won’t spend today. It’s great for a financial asset but terrible for an economy and a currency and a payment system. Modest, predictable inflation is indispensable grease in the wheels of an economy at the mercy of menu frictions and behavioral heuristics like loss aversion and money illusion.

It’s a catch-22. The volatility and constant rise in price make it unsuitable for real-economy transactions, which mean it can’t justify the ever-rising price.

The price has achieved escape velocity from reality.

I think people who say Bitcoin should go to $400,000 are either making simplistic arguments to get on TV or talking their book. They aren’t doing anyone any favors. Except maybe ICO con artists swindling their marks.

It’s hard to value Bitcoin as long as it’s untethered from the (legitimate) real economy. Have you ever seen someone wearing jewelry made of Bitcoin? Is Bitcoin going to fill your teeth or coat your windows or make your electronics corrosion-free? How much use will Bitcoin really be after the apocalypse? Outside of paying for contraband and malware ransoms and evading capital controls, what real use is it? Without any linkage to the real economy, why is the low single digits of financial wealth in gold the correct comparable to come up with $400,000 per coin, which would mean $8t total outstanding or 1/3 of US stock market cap?

In what ways is Bitcoin equal to, let alone superior to gold in liquidity and long-term reliability as a value store, linked to the real economy? Shouldn’t there be some discount in case a digital asset superior to Bitcoin 0.x turns up? Isn’t it some function of what real wealth alternatives are available, what their relative utility is for yield and risk expectations and real-world acceptance, how much the market demands of each?

What is an appropriate valuation metric? Let’s start with the novelty value. $10b is a round number. That’s order of magnitude for Beanie Babies or Pet Rocks, adjusted for inflation, and the more interesting experiments richer geeks can do with Bitcoin.

Add an appropriate valuation for the Bitcoin needed by black markets. This may vary widely over time, depending on adoption, depending on whether there has been a recent crackdown on the latest Silk Road / Alpha Bay, depending on current money laundering flows to/from capital controlled jurisdictions. But you can handle a lot of transactions in a year with each unit of Bitcoin. $100b of Bitcoin you could probably recycle through at least ~$1t of transactions per year with not much velocity-optimizing financial technology infrastructure.

Pulling a wild-ass guess out of my you-know-what, the largest market cap I can justify for black-market transactions is on the order of $100b. This is considering the size of black markets, what percentage of transactions might start to be done in Bitcoin in the not too-distant future, some reasonable velocity, comparing to the number of large-denomination USD and euro bills outstanding, the gold inventories that back financial instruments.

As a store of value, if you want to use gold as a comparable, you have to exclude gold that isn’t a private financial asset. You have to think about how the market will shake out between gold and Bitcoin if they are close substitutes. You can’t just assume Bitcoin replaces gold 1 for 1, or expands the market for ‘hard pseudo-currency store of value’ 2 for 1.

Bitcoin for black market transactions and as a store-of-value has issues: volatility, significant transaction lags and fees, the fact that it’s not as anonymous as you may think, the fact that authorities probably can and will crack down on it hard when it’s worth more to them dead than alive.

So you need to apply some discount for the possibility that cryptocurrencies will take only a small chunk of that market, or other alt-coins will come out on top. And maybe some premium for the likelihood of mainstream adoption in legit markets.

True, Bitcoin is more transportable than gold and can even be used for electronic payment. On the other hand the link to the real economy and long-term reliability as a store of value are weaknesses. Frequent flier miles, gift cards, and other forms of private electronic scrip are not an investable asset class. Scarcity value can be mitigated by other cryptocurrencies popping up.

I’m still a skeptic. If Bitcoin gains traction in the real economy, it has to be stopped, or highly regulated. Because governments rely on taxes. They don’t like giving up seignorage, management of economic policy, and use (abuse?) of the financial system for law enforcement, sanctions, foreign policy purposes. And China, for now, has shown that you can actually bring your entire Internet under state control. It’s technically feasible to stamp Bitcoin out or at least, repress it to within an inch of its life.

It’s also politically feasible. FDR banned personal ownership of gold, and he is nevertheless not generally regarded as a tyrant in circles that aren’t populated by rabid mouth-frothers. Politicians will cry that Bitcoin facilitates illicit drugs and international terrorism.

Governments will bring Bitcoin to heel if it challenges fiat currencies. So Bitcoin as a financial system outside state control is an oxymoron. Either it’s a marginal black-market construct, or it’s a tightly controlled appendage to government currency markets, like gold. It cannot be both mainstream and outside state control.

I could be wrong, but my wild-ass guess for the reasonable order-of-magnitude ‘terminal’ value for Bitcoin is in the $1000-$10,000 range (market cap of $20b-$200b, order of magnitude). I don’t have high confidence, maybe 50%. Visibility into the demand for black market activity and as a store of value is pretty limited. Maybe Bitcoin gets superseded or stamped out almost entirely. Or maybe there is something more to the store-of-value argument than I’m seeing. Aswath Damodaran wrote the book on valuation, and he says you can’t value Bitcoin. But his definition may be narrower than mine and surely you can place some order of magnitude limits on a plausible relative price.

I think Bitcoin valuation and prospects for mainstream adoption are overblown. I think the 2017 runup is due to bubble dynamics. It’s the most perfect bubble ever. There is no value metric, no intrinsic value, no PE, no interest to collect on it. If you think it supersedes the ‘legacy’ financial system, there is no valuation too high.

But let’s talk about why I love the blockchain.

Blockchain is a secure distributed database service. In the old days a database meant something like Oracle. Then the Internet came along, and because Oracle technology and pay-whatever-we-can-extort enterprise pricing didn’t work for something like Yahoo, we got open-source databases. Open source just means tech companies like Google, Facebook, all the way down the chain, develop standards and norms and software in areas where they don’t compete because competition would stymie progress and profits in the whole ecosystem.

Even competitors cooperate some of the time. Warring nations have conventions against chemical weapons or first use of nukes. If you violate them you may win the war but you may not have a planet to live on.

Buying Microsoft or Oracle software and giving them a big vig and strategic power is a nonstarter. Every company building their own proprietary stack of OS, database etc. is also a nonstarter. So they support efforts like Web standards, Linux, Apache, and MySQL and share the technology around them, which is not very strategic, and focus on competing further up the value chain.

MySQL is a funny case. Because MySQL was bought by Oracle. Even in the open source world, you cannot escape a principal-agent problem. You back an open-source software project, the developers and the managers of the legal entity can sell you out. Now you still have a software license but you have an exit/voice decision, where exit means forking the project. (Anybody remember CDDB? The most blatant fencing of digital commons to date, privatizing something people built as a public good.)

Blockchain takes the open-source paradigm to a meta level. In ancient times, suppose some folks started an open-air market for securities under a buttonwood tree. They develop ways of doing business, they eventually find the need to invest in infrastructure, to document and formalize practices. They create a legal entity and build a nice building with a pediment and a frieze. Now you potentially have a principal-agent problem if the board and folks who run it can make big bucks and run it for their own benefit or a club of insiders.

Software is eating the world, and blockchain is how it eats this sort of coordination problem. You enshrine the rules of the exchange in peer-to-peer software which every exchange member runs and which uses a common blockchain distributed over all members’ computers.

Now you don’t need an exchange floor, and you don’t need a rules committee, or much of an organization at all, the rules are enshrined in the software, and the members run all the IT. Now, no matter what political shenanigans ensue, no one can change the rules unless everyone agrees to run new software. If only some of them switch, you have a fork, and effectively two exchanges competing until one wins. The exit-voice problem is turned on its head. In order to change the rules of the game, you have to get everyone to agree to run the new software.

If you were starting an exchange, or any kind of market design today, frequent-flier miles, Wikipedia, organ transplants, would you rather enshrine the rules and data in a legal form, in a central organization, or in software?

For many collective action problems, software is just better. Not necessarily because it works better, but because it’s transparent and has built-in resistance to shenanigans. (Here’s a good explainer.)

Does it eliminate shenanigans completely? No, you still have governance, politics. But it moves everything into the software and the blockchain where it’s transparent, and no one can unilaterally change the deal. This is has potential to be a proverbial Big Deal, a game-changer.

Is blockchain better in every way? No. Anything that can be done on the blockchain can be done much more simply, much more efficiently in a centralized database. But that database is a nexus of principal-agent problems. It can be hijacked. Blockchain is a CAP tradeoff to perform very well in terms of availability and surviving network outages, but poorly in that consistency is potentially very eventual when it’s under strain. When the database is distributed among the users, it’s highly resistant to shenanigans but not necessarily highly performant.

How much does performance and efficiency matter? Communists made the argument that capitalism is not very efficient. Capitalists spend enormous resources on advertising to get people to consume, you have dozens of varieties of corn flakes, you have four gas stations competing on four corners of an intersection. What a waste!

But capitalism is extremely effective at giving people incentives, at innovating, at searching the solution space for best practices. In other words, at evolving.

As Darwin said, “It’s not the strongest of the species that survive, nor the most intelligent, but those that are the most responsive to change.”

Sexual reproduction wastes a huge amount of energy that could possibly be better put to use acquiring food and resources for survival. But it allows the species to rapidly mix and match features, to evolve rapidly.

In a similar way blockchains may be quite complex and inefficient in computational resources, but they may be a catalyst to allowing many institutions to evolve, to rapidly test a large number of new organizational models and incentive structures.

Technology seems to advance by alternately taking things apart and then putting them back together. We went from highly centralized and integrated mainframes to distributed PCs, back to cloud computing, which is an evolved mainframe model built on virtualized PCs emulated in software. (Predicting that in 1984 would have been a 1-way ticket to the loony bin.) We went from AOL and Compuserve to the unbundled, distributed Web and back to Facebook and Google walled gardens. Mammals replaced dinosaurs, and at each iteration capabilities improved.

Unbundled, modular, open systems evolve faster because we can rapidly add and improve individual parts, like Unix or an industry standard architecture PC with expansion slots. When we reach a point of diminishing returns, when we have fully explored the search space, when we have figured out best practices, we can usually improve it by building a highly integrated system, like an iPhone. Integration makes it possible to simultaneously optimize all the hardware and software components to work well together.

Eventually, technology will evolve again, and perhaps a more open system will regain an edge in mobile devices. But when a highly refined, integrated and optimized system works, it’s a thing of brutal beauty that destroys everything that competes with it. (I’m thinking of the old IBM, Microsoft Windows, and the iPhone).

More likely than something replacing these apex predators, they become commoditized and cells in higher-level, even more evolved organisms. (Artificially intelligent robot swarms coordinating peer-to-peer? Everyone living in a virtual reality matrix? Who knows what the next level of evolution may bring.)

I think Bitcoin and blockchain should be seen in the light of this dichotomy, this swing of the pendulum between open and distributed v. centralized and integrated. The pendulum has swung too far towards centralized cloud services and the ‘Fearsome Foursome’ of Facebook, Apple, Google and Amazon (maybe the ‘Frightful Five’ with Microsoft) owning our lives.

Over the next decade I foresee huge pushback against the Facebook/Google/Apple mobile/cloud model, and crypto, blockchain, peer-to-peer apps will be a big part of that.

The smartphone/cloud (and especially Facebook) is Huxley’s soma – we are addicted to notifications and ‘likes’.

The smartphone (and especially Facebook) is also Orwell’s telescreen. You carry it everywhere in your pocket and it monitors all your communications, everywhere you go, whoever you interact with, even in real life.

Some people buy cloud microphones for their kitchens and bedrooms and pay big tech companies to spy on them. Even Orwell wouldn’t have dreamed of that.

Big Brother uses AI to learn your greatest fears and desires and what to show you when, to optimize you for engagement and manipulate you into clicking.

The level of data collection is more than a risk, it’s a practical guarantee of totalitarianism. The only question is whether it’s techbros and rogue AIs who are going to watch everything you do and create the rules of the marketplace to determine what you see and watch; or the state; or thugs who hijack it to gain power.

And the drive for clicks drives extremism, because extremism = engagement.

The beauty of 30 years of open market free-for-all tech evolution and exploration is giving way to brutal centralization and integration. That’s why a free and open internet in the form of net neutrality is so important, and the need to resist authoritarianism in all its manifestations.

I think 20 years from now the Bitcoin frenzy may be looked upon as a fad. Bitcoin isn’t going to topple the financial system. Blockchain will be adopted as a sustaining innovation by banks and governments. To some extent, after the crash, Bitcoin might survive in various niches at a plausible market value, and slowly start a climb up the slope of enlightenment to the plateau of productivity.

But the frenzy also reflects a desire to challenge centralized power structures. People are dissatisfied with institutions. Wealth and power are centralizing and gaining commanding technological advantage over the individual. Blockchain and peer-to-peer crypto paradigms will challenge centralized power structures in unforeseen ways.

Imagine a boot, stamping on a Bitcoin symbol, forever.

God bless us, every one – Tiny Tim (and Andrea Bocelli)


OK, here’s a Sunday rant on guns.

I’ll start at the outset by saying I’m not a huge fan. I was a kid in New York City in the 70s when there were 5 murders a day. Being a city boy, and especially at that time, colors my reality. It’s not great to live in a town where most taxi drivers have a weapon under their seat, many bodegas have a weapon behind the counter, stray bullets are a risk to consider. Knowing there are a lot of crazies out there colors my reality.

There are some people who make the argument that a society where more people are armed is somehow better. I’ve seen it and it’s not. If you don’t understand that the point of politics and civilization is to not sort differences out with weapons, you can probably stop reading, if you somehow got this far.

The argument that ‘you can’t regulate evil, if you regulate weapons, only criminals will have weapons’ is absurd on its face. You criminalize the activity, and you also try to reduce harm. We try to minimize harm from all kinds of devices and activities, from Kinder eggs to Sudafed, even if it’s not 100% effective.

‘The only way to stop a bad guy with a gun is a good guy with a gun’ is also absurd on its face. Of course, the good guys, i.e. trained law enforcement and security personnel, should carry guns when necessary. And also, of course, if it’s possible to keep LV-style MacGyver automatic weapons out of the hand of the bad guy or crazy guy, you should try to do that.

‘Guns don’t kill people, people kill people.’ Yeah, people with guns. Do you want to keep nuclear weapons out of the hands of Kim Jong Un? Then you understand why I want to make it harder for my crazy neighbors to have guns.

‘Terrorists can kill people with knives or trucks, do you want to ban those?’ The old slippery slope argument…you’d have to ban sticks and stones too. Well, until a lone lunatic kills 58 and wounds 500 with a knife, that is the dumbest argument in the world. And maybe it would be a good start if we applied motor vehicle licensing, safety, insurance standards to deadly weapons. I have seen, with my own eyes, libertarians question the morality of having a DMV. Inexplicably, the same manifestly stupid argument gains credence when applied to managing the externalities and costs imposed on the innocent victims and on the public by deadly weapons.

If you live in a relatively safe city or suburb and you think a gun makes you safer, you’re almost certainly wrong. You’re much more likely to get shot if you own or carry a gun. You may think you’re a responsible, well-trained, level-headed gun owner, but probably so did every other parent who got shot by a toddler. You’re probably not as special as you think. On a bad day, normal people are susceptible to alcohol, murderous rages, depression and other mental illnesses, and guns don’t make any of those things any better.

The cost of easy access to guns is very high. This Las Vegas massacre is going to be 10 figures of direct costs for medical, first responders, lawsuits. Years of recovery from physical and psychological trauma for survivors. Then there are all the loved ones who will not have a spouse, a parent, a child. Then there is the fact that every cop who approaches a car has a risk of encountering a gun, the reality that their first responsibility is not to serve the public but to live through the day and go home at night, making trigger fingers itchy. Despite the fact that that society is less violent than ever, acceptance of police-state tactics is increasing. Places with fewer guns have fewer murders, have higher trust in law enforcement and in society generally.

That’s an example of what I tend to view as the fascist-libertarian nexus. Arguments in the name of liberty lead directly to and justify authoritarianism. As George Washington said, “Arbitrary power is most easily established on the ruins of liberty abused to licentiousness.” People make the strange argument that the Second Amendment is a check on tyranny. Strange, because the Second Amendment wasn’t put there to license war against democratically elected government, or treason, or rebellion. When a minority group protests, with some justification, that a tyrannical government is using excessive force against them, with bad shootings caught on video on a regular basis, the people who self-identify as pro-liberty seems pretty quick to label the protesters as terrorists. When it’s oppressed ranchers on Federal land, it’s one thing, but when it’s Black Panthers marching in the streets with guns, even Ronald Reagan and the NRA can agree that open carry is an act of violence. When the disenfranchised try to exercise freedoms, even to protest peacefully, it somehow becomes a huge problem. If you’re making freedom arguments which only apply to people who are already empowered, it bends toward fascism and feudalism.

Let’s face it, a Muslim does this, people go nuts. It’s a new 9/11. They hate us for our freedom! A black man does it, you’ll seem some colorful language on social media. White man does it, crickets. It’s the price of our freedom! You cannot tell me race, fear of the ‘other,’ latent prejudices, aren’t key factors driving the disparity in emotional and policy response.

The Second Amendment maximalist argument is, in my opinion, a complete red herring. The Second Amendment contains the clause, “a well-regulated militia.” It explicitly foresees regulation. The NRA conveniently omits that clause, perpetrating what Warren Burger called a fraud on its extraordinarily gullible members.

The Second Amendment came out of debates over desirability of standing armies, need for slave patrols, fears that the Federal government would ban slavery or otherwise intrude in the affairs of individual states. The ‘well-regulated’ clause is saying, the motivation of this amendment is that the Feds may not ban and assume functions of legitimate state and local armed militias, police forces, national guards, etc.

Of course it also bears on individual rights to bear arms. But at some level you have to draw a line and say people cannot have personal RPGs, machine guns, WMDs, or something. Machine guns and guns above .50 caliber seem like a pretty reasonable limit, which is currently enforced (with obvious loopholes, i.e. Las Vegas.). A system to keep guns out of the hands of known organized criminals, convicted felons, domestic abusers, mental patients, and people who could not be part of any ‘well-regulated militia’ seems both reasonable and falling clearly within the language and intent of the Second Amendment.

When you read any part of the Constitution, or any law, you need context. The First Amendment says Congress shall make no law abridging freedom of speech. But you have to read it, or any law, as “you shall not, other than to the extent reasonable and necessary to protect other rights and enforce other parts of the constitution.”

Many, many crimes are essentially speech: trademark infringement, fraud, conspiracy, child pornography. You cannot argue that the First Amendment means you cannot be convicted of fraud, or conspiracy to commit murder. Well, you can argue that but you will lose. Once the speech becomes the nexus of a criminal activity, it is no longer just speech. In order to preserve the other rights in the constitution, like patents, it becomes necessary to construct reasonable limits around what is considered protected speech.

These are common sense reasons why regulation around guns is unavoidable and explicitly Constitutional. That being said, I recognize that every place isn’t New York, people have strong views about guns, there are different cultures and realities on the ground. If you’re in a rural area with no law enforcement response within an hour, exposure to nearby drug and human trafficking, etc., the context is very different from being in a safe city or suburb. And even if not, there are just different cultures and views on the matter which should be respected in a democratic society.

I accept that people in Maine will have a different view of firearms than people in Boston, so for the most part, I would leave the gun question to states and local governments.

However with freedom of travel and commerce, you cannot effectively restrict guns in Boston if anyone can drive to Maine, walk into a store, buy firearms, get back in the car, and drive back to Boston. (or Chicago/Indiana)

Here is the approach that would make sense to me.

In order to enable state and local regulation, you must have Federal registration of all firearms. You want to own firearms for self-defense, hunting, sport shooting, you and your guns have to be in a national database. The gun’s ballistic signature is in the database. Your fingerprints are in the database. You want to sell or gift the gun, you have to make sure to update the database under penalty of Federal law. Whenever the cops pay you a visit, they get a popup noting what guns are associated with your address, car etc. A crime gets committed, the cops look up who has the weapon and what its chain of ownership was.

If you are a Boston resident, you buy a gun in Maine, the Boston PD gets a popup. They maybe pay you a visit, ask you where the gun is, remind you of the local gun laws. If it’s for skeet shooting at your place in Maine, that’s fine. Just comply with your local laws and keep the records updated.

Local regulation, which states and municipalities might wish to consider:

  • Safety and responsible gun ownership training.
  • How weapons may be stored, transported, etc.
  • Background checks.
  • Additional limitations for felons, certain violent non-felonies like domestic abuse accusations, subject to due process. Mental illness limitations.
  • Inspections. If you have a lot of guns, the government can inspect that they are being stored safely at the location they are registered to.
  • Biometric safety devices, so only authorized individuals can access or fire them; geolocation.
  • Insurance, financial responsibility if your weapon is stolen, misused.
  • Taxes on guns, ammunition to pay for the regulatory regime and the significant economic externalities of gun ownership.

This would be the American way, I think. Move the debate to the local level, so it’s not, Washington wants to take away your guns, and let local communities determine what common sense means to them.

We’re in a vicious spiral of loss of trust in government, institutions, each other. Americans support gun laws that would make a difference, but can’t get them passed, further eroding democracy and trust. They don’t trust the government to keep them safe (even though it’s hella safer than it used to be), so they buy guns. Then every argument carries the risk of deadly escalation, whenever someone reaches a breaking point there are potentially dozens of casualties. Then cops militarize and sometimes escalate unnecessarily, further worsening trust.

We don’t want to go back to the Wild West. Harsh local restrictions probably won’t make a very large difference in gun deaths. But a comprehensive approach would reduce gun deaths, the terrorism threat and irrational fears about it, and help restore trust in cops and democracy.

It’s probably going to get worse before it gets better. But it’s up to us to remake those institutions and that trust, or turn into Argentina with nukes, or worse.

A Google teachable moment, or the end of Western civilization?

This anti-diversity manifesto has been making the rounds, with calls to avoid “socially engineering” diversity in response to “veiled left ideology”, to “de-moralize diversity”, to “de-emphasize empathy”, to “prioritize intention”, and to “be open about the science of human nature” which is claimed to confirm a lot of right-wing priors and stereotypes.

I have questions for the author… Really? You don’t understand that a corporation is a form of social engineering for specific objectives? You don’t know that small effects at scale result in disproportionate impacts? You don’t realize that results matter as well as intentions?

And you don’t understand that, at Google of all places?

According to you, Google’s new motto should be, “Don’t do evil, but if evil is caused by our biases or actions, prioritize intention?”

If you don’t know that all companies, all engineering is social engineering, but especially Google, then you don’t know engineering, you don’t know society, and you really don’t know Google and aren’t doing your employer any favors.

You really think the rest of the world is going to look at this and say,“sure Google, go ahead and remake the world in the image of engineers like you? We’ll just be over here, blissfully watched over by your machines of loving grace?”

Immanuel Kant’s categorical imperative is a foundation of Western Enlightenment ethics: “Act only in accordance with that maxim through which you can at the same time will that it become a universal law.” It’s the Golden Rule taken to a logical extreme: Treat others as you would like to be treated. Think globally, act locally.

Is possible to act that way all the time? No. Not even if you’re some kind of saint. You have to be a little crazy to say, software should be free, so I’m only going to use free software because if everyone did that the world would be better.

Who can even say what the consequences would really be? It’s a foundation of ethics to think through the consequences of your actions and act accordingly, and yet, to predict the consequences of any universal law (or anything) is also an act of hubris.

The Ayn Randian view is that everyone should act for their own benefit. Government and even altruism is immoral. That’s even more extreme than Kant. It ignores the fact that humans do anything worthwhile in groups, not just as individuals, and organize into hierarchies with rules, enforcement.

A more enlightened Randian view is that everyone pursues his or her own self-interest, but does so strategically. Governments and charity can be social contracts that people enter into freely to promote the good of all.

Game theory, where everyone acts strategically in their own interest, is an antithesis to Kant. Treat others as you would expect to be treated. Think globally, strategically about how everyone else will respond, then act locally, in your own self-interest.

The synthesis, is how do we build a society of laws, institutions, corporations, and technology like Google, that lets imperfect humans, who are boundedly ethical and boundedly strategic, work together to survive and prosper?

If you’re human, you have intelligence. It’s the apple from the tree of knowledge. In no earthly religion or philosophical system do you get enlightenment or salvation based on good intentions. You have to think through the consequences of your actions. You are free to choose but not to escape the necessity of choice, and the consequences.

The sentiments expressed in the screed are, to be generous, immature. It’s what happens when a smart kid’s idea of the way the world should work confronts a reality where if you want diversity, you have to measure it, understand where and why it falls short, and take steps to fix it.

Is he even claiming that Google bends so far backwards for diversity that it damages the company’s ability to deliver products and attract great people, or just that it offends his sensibilities about how things should work? None of these abstract suggestions are going to make Google a better company.

Less generously, it feels like toxic social media drama by self-appointed culture cops, people making waves because they can and because it gratifies some impulse to make a dent in the universe.

Does he think it’s his job to determine Google’s values? Does he really think Larry Page and management are going to welcome criticism of their values as a constructive intervention, and it’s going to make Google a better place? Or is it just someone who lives in his own reality bubble with an inflated sense of his own importance, and/or thinks social media pot-stirring is normal in the workplace?

Lately it’s become acceptable to make anti-social statements against women, men, blacks, whomever. Some of the people who deride PC ‘snowflakes’ also generate a lot of outrage at any perceived slight, sometimes to the point of veiled threats. It’s a dangerous decline in norms of civilized behavior. We should be thinking carefully about who benefits, who is promoting it, and why, and how we defend freedom while at the same time defending ourselves against stupidity, and people who abuse their own freedom to take it away from others.

UBI, health care, welfare economics and asshole economics

People sometimes ask me what I think about Universal Basic Income (UBI).

TL;DR it’s just a name…I’m skeptical of any radical implications…what matters is the marginal rate.

There are societies that let people starve in the streets. We are not one of those. Voluntary giving is laudable, but it’s even more laudable for a society to say, everyone will contribute to helping the least fortunate who are too old or too ill to earn a living.

If you agree that we don’t just let people die and there should be some minimal safety net, the fair thing is for everyone to contribute. It’s people taking shared responsibility, today I help you, tomorrow maybe you help me.

Once you agree to some minimal safety net, you agree in principle to something like UBI, we’re really just debating how much, in what form, under what terms.

  • You can provide assistance in kind, like soup kitchens, homeless shelters, free clinics.
  • You can provide scrip that can only be spent on approved items, i.e. food stamps.
  • You can provide cash.

You can provide assistance to anyone who asks, or you can have people apply and determine whether and how much assistance they are eligible for, according to some need-based criteria.

When I think of UBI, I just think of some amount of unconditional cash, recouped by a tax from higher-income folks. So basically no-strings welfare.

UBI has advantages. No bureaucracy. No arbitrary determination of eligibility. No restrictions on spending. Just give people cash that they can freely decide how to spend. High freedom, low overhead.

A lot of people view those as features. Some people might view them as bugs, taking the view that only the ‘deserving’ should get assistance, they should have to work for it, they shouldn’t be able to spend social assistance on beer or Twinkies, etc. (Paternalism FTW? Government should stay out of people’s business…unless they’re poor?)

I have trouble generating strong feelings about it. Whether the safety net should be partly in the form of UBI is unimportant compared to the size of of the safety net and the marginal rate structure, i.e. how much you get to spend out of every additional dollar you earn.

I have strong feelings about two pet peeves. The first is the discussion tends to be mostly woodshedding. People get worked up about small pieces of the picture. It’s meaningless to say I like UBI, or food stamps, or don’t like sales tax or VAT because of the distribution implications. The only thing that really matters is the distributional effect of the whole system, i.e. the marginal rate structure. If a particular tax or benefit is efficient, you can always offset the distributional impact elsewhere. You can even have a progressive VAT. You can’t divorce a benefit like UBI from how you pay for it. You have to look at the efficiency and distributional impact of the whole system, not each individual component.

The second is, it’s pretty hard to be poor in this country. The system is built around the needs of the wealthy and middle class. In some countries you can be poor and have very little in material possessions, and you can manage, live, work, your kids have opportunities. In America, in a lot of places if you don’t have a reliable car, you can’t get to work, if you don’t live in the right place you can’t get a proper school, and don’t even get me started on access to minimal, basic medical care. People seem to think that’s part of being poor but it’s really not. There are countries where you can live with dignity on a low income.

It costs a lot to be poor in America, even at a level of income which would be middle class in most other countries. It’s practically a crime to be poor, there’s a war on poverty, but not in the sense LBJ meant it.

You could get lot of bang for the buck improving the supply side for poor people: cheap housing and transportation.

Personally, I think for sure there should be soup kitchens, free clinics, homeless shelters, a real rock bottom safety net.

And there should be a marginal rate structure without perverse incentives. We should ensure it really pays to work, if necessary subsidizing initial wages via the EITC, not taxing people 17.65% on the first dollar when they start to work. And especially we should avoid benefit cliffs, where you lose a lot of benefits when you reach a certain level and so it doesn’t pay to earn an additional dollar.

Those are the most important: A secure minimal safety net, and a rational marginal rate structure. People find meaning through work, taxpayers who work hard get cranky when people get benefits and don’t work. Welfare queens and rich panhandlers are media stock-in-trade. See Exhibits 1, 2, 3.

Politically, I think UBI is a hard sell, because you have to reclaim the UBI from high earners to balance the numbers out. You give people something and then take it away, they feel worse than if you never gave it to them in the first place. And giving money for nothing to the poor, no work requirement, just annoys them even more.

It seems like a political loser, and raising UBI to a level where the ‘basic’ means everyone has basic needs met, no-strings-attached, seems to entail more redistribution than a lot of people want. It’s possible that in the future, robots and automation will make so much labor redundant that we will need more redistribution just to avoid mass poverty. The robot singularity is something we should keep an eye out for but might as well deal with it if it becomes a problem.

Ultimately I don’t see UBI as an anti-poverty game-changer. It could be part of that rational marginal rate structure.  I like the simplicity of UBI more than, say, food stamps and a hodge-podge of local and federal welfare programs with complicated administration, eligibility.

I just don’t think you can make UBI a complete substitute for in-kind assistance, then let the market deal with everything, food, health care, housing, education.

While I’m at it, I find it pretty inexplicable that Obama passed a health care plan that is basically private insurance for about 1/3 of the uninsured, while creating a multi-$100b+ bonanza for insurers, hospitals, doctors, and big pharma, and the GOP wants to reverse it, take away health care from 20-30m Americans. Asshole economics is too kind, it’s just politics to piss off liberals and most people who aren’t cray-cray.

Again, we don’t let people die in the street. So at some level society pays for that minimal care, the question is how. It’s extraordinarily expensive in human and cash terms to have EMS and emergency rooms deal with things that shouldn’t be emergencies. There are armies of people employed to push costs on other people, often in sketchy ways, getting in the way of doctors trying to provide the best possible treatment, and there are a lot of expensive, not necessarily helpful tests and therapies.

This is how I solve it, with a 3-level system:

Essential care: dedicated NHS-like facilities funded by a dedicated tax, like a 3% payroll tax. Free clinics and hospital beds. Tax proceeds go to the states to provide care, as long as it’s within guidelines. Services are going to be basic. Nothing non-essential. There are going to be waiting lists for surgery. You are not going to get a $1m liver transplant. If people make a fuss that it’s crap, then improving it means raising that dedicated tax. Social contract is, you aren’t going to die in the street, but if you want top care you will have to pay for it.

Normal care – something like Obamacare – everyone can buy a health plan on more or less a level playing field, whether they are corporate or not. And everyone who can should, in the sense that you get some subsidy if you do and some penalty if you don’t. If anything, there should be more teeth to the Obamacare penalties to prevent free riders. If you pay 28% income tax, and health care is paid by your employer out of pre-tax dollars, there is currently a 28% tax subsidy there. I think as a moral imperative we should apply that subsidy to everybody.

And then of course if people want more they can buy it on the free market.

I don’t see how you can reasonably reconcile, don’t let people die in the street outside the hospital, with anything short of a single-payer system at this point. Anything less seems cruel and perverse and actually endorsing a free-rider situation instead of a rational scheme for indigent care.

Anyway, I find the low quality of the debate distressing. We should be able to agree that we will not have people die over toothaches. We should be able to agree that the current system delivers poor care and enriches a few in strange ways. And it’s pretty messed up that you will basically go broke if you get sick, sometimes even if you have insurance. We can argue about what constitutes a minimal acceptable level of care and what is a fair way to pay for it. But a system where you exclude people arbitrarily, everyone has to fight the system for basic care, we have poor outcomes, and pay a ton of money, should not be acceptable to anyone and we should be talking about ripping it up and starting over.

Straight talk on Trump and Russia

We have now sunk to a depth at which restatement of the obvious is the first duty of intelligent men. – George Orwell

  • The report that taught me the most this week is this interview with Natalia Veselnitskaya. The Russians have decided Trump is worth more dead than alive. If that’s not the case this interview doesn’t happen. [Edit: Others also seem oddly talkative.]
  • Mixed reports on Veselnitskaya: Browder, who would know, says she’s Russia’s point person on Magnitsky Act sanctions; Bershedsky says she’s a nobody, more like an AG Schneiderman repping some local oligarchs than a Kremlin power broker; Ioffe says she’s connected.
  • Bottom line, if Putin doesn’t want her to throw Don Trump, Jr. under a bus, it doesn’t happen. She is in a position to know that interview serves her patrons.
  • Veselnitskaya went to Trump Tower, said Russia can help…But first, are you going to lift sanctions and let oligarchs move money around free from worries about seizure? That’s what Russia is talking about when they talk about adoptions and sanctions. (Edit: she brought along a Russian ex (?) GRU specialist in hacking dirty tricks.
  • So then what happened? Hardly likely that was the end of the matter, given subsequent events: multiple hacks; Trump harping on emails, being very solicitous of Putin; the untimely demised Mr. Smith tracking down hackers who might have had Hillary’s emails; meetings with Kislyak, VEB, the infamous backchannel through Russian communication facilities.
  • Trump’s problem is that having taken Russian help, and it being public, he is now no longer in any position to deliver them anything of value.
  • Maybe the source of the Don Jr. email was Russia: Manafort was on the email chain, given his Russian connections, he might (recklessly) have inquired about it with some trusted Russian who now has an interest in releasing, or he might be sending a message by releasing it now.
  • Maybe the Mueller investigation is about to bear fruit and the plan is to get ahead of it and try to pin it all on Don, Jr., and then have the president pardon him. So incriminating himself could be a feature, not a bug.
  • If it didn’t come from Kushner or Manafort, it would have to be someone they or Jr. forwarded it to, or someone who intercepted it, like a US or Russia three-letter agency, or a deep Trump organization mole (I would be tearing out walls Billions-like if I were the Trump IT guy, and it would make my day if a lowly IT guy went Snowden on Trump with an email dump.)
  • In any event, the Trump presidency is walking dead. It’s over, in terms of major legislation. Once you’re worth more dead than alive to both Vladimir Putin and Mitch McConnell, your days in office are probably numbered.
  • Even a hardened cynic can only be appalled at these events, at the people who still deny or excuse a Russian entanglement, think it’s somehow business as usual for presidential candidates to ally with the KGB/GRU, or that loyalty or expedience makes it worth defending. Or respond with propaganda that would make Goebbels proud, even if they can’t pronounce Goebbels.
  • If deference to Vladimir Putin, a man credibly accused of false-flag bomb attacks in his own cities to consolidate power, is the price of keeping the alt-right / tea party on side, and that’s not electoral poison, if not in primaries then in the general elections, maybe there is something to the idea that the West is unwilling to defend its values.

The Top 100 People To Follow To Discover Financial News On Twitter, May 2017

It’s been a year since we posted our last list of people to follow on Twitter for financial news. Time for an update!

I posted earlier about some of the trends in the financial Twittersphere.

  • More churn
  • Less growth
  • Politics (i.e. Trump) drowning everything else out

See below the table for a little technical discussion, and a fun interactive map.

Screen name Quality Centrality Frequency
valuewalk 10.00 1.97 9.04
JohnLothian 8.54 0.05 10.00
blakehounshell 8.28 4.55 6.63
lrozen 7.86 2.60 8.05
pdacosta 6.70 6.02 7.43
ClaraJeffery 6.49 2.60 5.94
HotlineJosh 6.42 0.77 6.32
fmanjoo 5.73 5.41 4.52
JohnJHarwood 5.69 3.48 4.49
mathewi 5.50 2.12 4.74
moorehn 5.47 4.64 6.47
activiststocks 5.45 0.41 3.81
niubi 5.26 2.13 4.32
michaelsderby 4.96 1.77 3.28
Frances_Coppola 4.92 2.69 3.71
acrossthecurve 4.79 1.07 3.03
TimOBrien 4.77 3.97 2.90
BruceBartlett 4.75 2.49 3.76
MarkThoma 4.74 5.49 3.05
dandrezner 4.64 4.24 2.89
mattyglesias 4.58 6.37 2.96
sdonnan 4.57 3.07 4.29
AmyResnick 4.53 2.71 4.59
kimmaicutler 4.52 1.70 3.06
crampell 4.51 6.52 3.24
davemcclure 4.50 1.31 4.02
WillauerProsky 4.40 0.65 4.16
kairyssdal 4.33 2.93 2.32
AdamPosen 4.26 4.39 2.88
gabrielsnyder 4.24 2.24 2.03
sarahcuda 4.23 1.23 3.36
DavidClinchNews 4.19 0.54 2.96
BobBrinker 4.16 1.11 2.73
Noahpinion 4.16 4.94 3.09
Susan_Hennessey 4.16 1.73 2.60
AnnieLowrey 4.10 5.48 2.21
ComfortablySmug 4.08 1.54 3.34
EpicureanDeal 4.07 2.68 2.40
brianstelter 4.06 5.51 2.91
kadhimshubber 4.00 1.50 2.22
LaurenLaCapra 4.00 2.03 2.49
hblodget 3.98 6.76 2.06
NickatFP 3.98 2.05 2.56
djrothkopf 3.94 1.99 2.71
TimDuy 3.94 2.57 1.95
ZekeJMiller 3.93 1.91 2.17
davewiner 3.88 0.79 3.65
JohnCassidy 3.87 5.08 2.29
FGoria 3.84 1.74 1.79
BarbarianCap 3.76 1.61 2.46
BaldwinRE 3.72 2.33 2.24
carlquintanilla 3.69 4.94 1.91
BrendanNyhan 3.66 3.34 2.19
jbarro 3.65 6.71 1.97
lizzieohreally 3.63 3.91 2.53
sspencer_smb 3.59 0.26 2.59
NKingofDC 3.58 1.91 1.69
MissTrade 3.58 0.00 4.66
JesseDrucker 3.58 1.96 1.90
jyarow 3.57 2.42 1.34
harrisj 3.56 0.71 2.46
ReformedBroker 3.53 6.26 1.68
markgongloff 3.50 2.21 1.72
MattGoldstein26 3.47 2.81 2.28
FlitterOnFraud 3.42 0.91 2.33
jeffjarvis 3.35 1.66 2.27
davidmwessel 3.35 6.59 1.55
raju 3.35 2.91 2.89
PekingMike 3.30 1.52 1.71
TonysAngle 3.29 1.20 2.31
NickTimiraos 3.28 3.85 1.43
ritholtz 3.22 6.44 2.03
GreekAnalyst 3.21 1.58 2.17
ObsoleteDogma 3.21 7.91 1.07
prchovanec 3.21 2.60 2.29
HBoushey 3.17 1.74 1.60
rationalwalk 3.11 0.03 1.98
karaswisher 3.07 4.39 1.72
jessefelder 3.06 1.03 1.46
BuzzFeedBen 3.02 5.59 1.55
edwardnh 3.00 3.30 1.70
RobertMackey 2.99 0.95 1.83
mims 2.98 4.31 1.46
TimAeppel 2.97 1.65 1.66
M_C_Klein 2.95 5.98 1.17
mekosoff 2.92 1.37 1.68
qhardy 2.90 1.99 1.55
jamessaft 2.88 1.55 1.44
davidjoachim 2.86 1.19 1.54
mbaram 2.82 0.58 1.48
alex 2.81 0.86 1.93
MikeIsaac 2.81 2.75 1.31
NoahShachtman 2.78 1.92 1.19
BCAppelbaum 2.77 8.05 0.81
mccarthyryanj 2.77 3.16 1.14
EddyElfenbein 2.76 2.64 1.64
NinjaEconomics 2.71 2.82 2.21
JHWeissmann 2.71 2.16 1.22
CarlBialik 2.68 0.72 1.60
inafried 2.66 1.30 1.74

Here’s our map of ~350 Twitter accounts, using a force-directed network. Everyone who follows an account or posts similar links pulls it toward them, so we see Twitter accounts arranged into broad areas: Asia, Europe, US markets, tech, media, econ, politics. People who are in the center are pretty equally followed by folks in all parts of the map, whatever their varied interests. Bigger labels represent people with larger followings.

Here’s a link to a fun interactive version.

How does this work?

We start with a network centrality analysis, building a graph of who follows whom and finding the people with the largest number of most influential followers. Those are probably people who will play an important role in transmitting important news.

Then we trim the list to people who are good curators: they post links to a variety of good content in a frequent and timely manner. We cull people who may be central, but don’t post a lot of good timely news links.

Who do we cull?

  • Non-relevant accounts. @DonaldTrump (the new champion!) and @BarackObama are widely followed, but the stuff they post is only occasionally a news link directly relevant to financial markets.
  • People who don’t curate, filter, and signal the most important things to read. @LHSummers is a good example. He’s a really important guy to follow but he only tweets out his own stuff, he doesn’t help people discover financial news.

We rank the quality of each account’s curation on how much financial news they tweet, how much of it gets picked up and generates a lot of buzz, and how early they post it. It’s a subjective, but hopefully useful formula. Everytime you tweet something, and your followers view it and retweet it, traffic flow downstream, more likely than not from the most central folks to the periphery, and whenever attention flows downstream, influence flows back upstream in a sort of Newton’s Third Law of social media.

And of course, see the most shared financial stories updated continuously on the StreetEYE home page, and follow us on Twitter.

A final P.S. and caveat: Like all such lists, it’s closer to a fun parlor trick than a definitive ranking. I’m delighted if people I respect get a kick out of it and even find it useful to discover new people to follow, but keep in mind that 1) I just used a small sample of Twitter data and 2) it’s just a simplistic formula. If you’re on here then you’re probably pretty widely followed, post a lot of timely and relevant financial news, that goes pretty viral. Let’s just say it’s inherently has a lot of bias and variance and tilts mainstream by design. I wouldn’t read much into why X is higher than Y or Z isn’t on here. Don’t take it too seriously!

Frequently asked questions:

  1. WTF is StreetEYE? Since 2011 we’ve tried to systematically find the best people to follow for financial news, and create a crowd-sourced front page of the financial Internet. You can read more here.
  2. Why isn’t <brilliant pundit or technical commentator> on the list? Assuming they are very widely followed, probably because they don’t share other people’s content very much. There are a lot of great people to follow, who only share their own original content, or that of their colleagues. They don’t add a lot of signal to help discover news, so they don’t meet the relevance bar. 
  3. Why isn’t ZeroHedge on here? Everyone knows they should be #1! ZeroHedge blocks our bot on Twitter. There are three accounts I would like to follow that block us. Maybe they hate being aggregated in this way. Maybe I said something snarky. I have been known to be a jerk. Sorry! Ask them.
  4. What about Drudge Report, Memeorandum, Techmeme, Mediagazer? Those are aggregators in politics, politics, tech, media respectively, the latter three in the great Gabe Rivera’s empire. They are fantastic and a lot of people follow them, I recommend you check them out. But even though by the numbers they rank pretty highly, they’re not specifically market-related and people thought they looked weird on this sort of list, so I took them off as not directly relevant, despite decent numbers.
  5. Why isn’t <other great account> on here. Maybe they are just below the 100 cutoff. I am the first to admit the formula is subjective and arbitrary. If they post a lot of timely relevant headlines, they are probably on our radar. If there is someone who is relevant and widely followed who is not on the list, we would like to know. Contact us! We love feedback.
  6. Can I see the whole list? Here are the top 300. If you want to see where others rank, or follow even more of them, go to town!
  7. If you have other questions, tweet at us at @StreetEYE or contact us via the contact form.

Rethinking the marketplace of ideas

I was recently listening to Fred Wilson and Howard Lindzon talk about, among others, news sources and curation, which is a topic dear to my heart. (Which I wrote about before here and here).

Curation is hard, people tend to fall into confirmation bias circle jerks, and we are in a crisis of media legitimacy. (More generally, the legitimacy of the establishment and objective reality.)

If you think the moon is made of green cheese, you have a problem. If a lot of people think the moon is made of green cheese, society has a much bigger problem. (Or that climate change is a hoax invented by the Chinese, or that vaccinations cause autism, etc.)

The marketplace for ideas is faltering. I’m not sure if it’s only the arrival of the unwashed masses, Facebook likes, adverse selection, filtering tools that aren’t fit for purpose, or manipulation and ‘fake news.’

What seems to have gone missing is the sharing ethic that existed when the blogosphere and Twittersphere and social bookmarking were young.

What works to surface quality content is human curation, like Memeorandum, Abnormal Returns, and an engaged community that actively promotes and shares quality and feels that it’s important… like AVC, Hacker News, the better subreddits, Open Culture, Arts and Letters Daily, Brain Pickings, etc.

Ray Dalio seems to think a new market design with some kind of regulatory component is needed. I don’t know what he has in mind, but one could imagine a self-regulatory body that agrees on journalistic standards like CFA ethics: clearly separating fact from opinion, having a reasonable basis for any statement of fact or conclusion, showing your sources and investigative processes, promptly correcting errors, etc.

And then people and media sources that meet those standards get a seal of approval, and it investigates violations, censures or even expels people and organizations that don’t meet the standard. Sort of a credit rating agency for journalists.

Government regulation of the press isn’t compatible with the USA’s Constitution and even press self-regulation wouldn’t be in line with American’s traditional sense of the free press. It’s not clear that the most prominent publications e.g. the New York Times and Wall Street Journal would submit to a regime like that or that it would have much sway without them.

But Dalio is not wrong either, we need better consensus on what we expect from journalists and tools to signal credibility and hold people accountable. If the New York Times wants to be credible, it can’t rely purely on prestige, it has to be open about its standards and practices and uphold what it means for something to be published in the newspaper of record.

David Siegel and Cathy O’Neil think personalization and big data are the problem.

Siegel frames the problem as one of micro-personalization. The picture I have is, in the old days everyone watched Cronkite and read the New York Times, and elite media institutions set the agenda. With the Internet and cable TV, the media fragmented. Everyone is more receptive toward media outlets that reflect their own values and point of view, and gravitates towards outlets that reflect them. But the more you hear mostly news and points of view that confirm your own biases, the stronger those biases get. And personalization and news recommendations are the ultimate silo or filter bubble. You only hear the news you like to hear. The end result is a singularity of polarization, where anything that doesn’t toe a narrow line triggers cognitive dissonance and a strong emotional reaction of ‘OMG mainstream media bias’/’fake news’.

Siegel’s argument as I understand it seems completely plausible. But the root issue is fragmentation, not algorithms per se. Eliminate algorithms and you still have the problem that some people get all their information from Democratic Underground and some from Free Republic. You can make an algorithm optimize for whatever you want, for instance try to surface quality from a variety of points of view. The algorithm genie is not going back in the bottle. To the extent there’s an algorithm problem, the answer is to improve the algorithm.

O’Neil’s “Weapons of Math Destruction” point is that any manipulation that can fool humans can fool the algorithms. We’re stuck with misinformation, and the solution is to turn to trusted sources. But what happens if sinister forces fool your trusted source, or make you think a source can be trusted when in fact they are bought and sold?

Furthermore, if I only believe stuff once it’s fully fact-checked and published on Bloomberg or in the New York Times, I’m ignoring a lot of potentially useful information and sources. It’s a bias/variance problem. I want a news filter that is sensitive enough to surface the viral story about United Airlines if I happen to own their stock, while being selective enough to bury hoaxes.

If the argument is that any signal a filter might use can be gamed by fake news information operations, that is generally true, but only up to a point.

Indeed, Goodhart’s law is in play, and any statistical regularity that let’s one filter fake news will tend to collapse once pressure is applied on it for control purposes and it starts being gamed.

But good predictors don’t usually collapse to zero. Even though just about anything can be faked with sufficient skill, museums are probably not mostly full of fakes, even though the incentives to manufacture forgeries are enormous. Our relative safety lies in the fact that it’s hard to commit a perfect crime. The entropy of reality is impossibly complex to forge. With enough fact-checkers, lies are generally detectable. With enough resources you can make anything go viral, but you can’t make anything withstand scrutiny. You can fool all the people some of the time and some of the people all the time, but you cannot fool all the people all the time. And (fake news alert!) Lincoln never actually said that.

The crude manipulation of the form ‘Pope endorses Trump’ is straightforward for the top quartile of readers to detect and debunk. So it is feasible for algorithms to filter that out based on where the story originated, the ratio of credible sources spreading it, spam flagging. Just as Google filters spam, news algorithms can and should filter egregiously fake news.

Platforms like Facebook and Google are going to build algorithms, and it’s incumbent on them to build ones that can’t be fooled all of the time. To cry censorship is a bad-faith, burn-it-all-down argument. The answer to bad algorithms is better algorithms. There is no argument for letting people vote based on ‘Pope endorses Trump’-level news. Either participate in truth-based news and policy, or GTFO, because democracy needs to be nurtured, and the crude distortions of reality, reminiscent of Nazis and Soviets, herald the end of democracy.

Powerful forces will use big data and machine learning to manipulate you. But big data and machine learning algorithms are also very powerful tools to fight manipulation and help surface quality. And we should be doing that instead of decrying personalization, and building a market design which is more resistant to manipulation and provides tools to surface quality.

I think Cathy O’Neil is right in the sense that the process has to be connected to human curation. Giving the filtering process over to machine seems to result in a sort of clickbait fetishism, vaguely akin to Marx’s commodity fetishism, where fundamentally human relations and processes are abstracted and subordinated to relationships between commodities and markets. The value of true information gets buried by clickbait that triggers the reptilian brain, endorphin release, and bias confirmation.

I think if we could somehow build a pervasive ‘pay it forward’ karma and reputation ecosystem that rewarded people for sharing quality and burying fake news and garbage, and somehow get back some of the old sharing ethic, it would go a long way. That’s what I’d be thinking about if I were a VC or online community entrepreneur. Tools to let people signal quality, find data exhaust that separates spam, disinformation and noise from truth, build trust, and fight the noise machines.

If credible news organizations open their work, tag facts vs. opinions, open up source materials like interview transcripts, link to sources, then a crowdsourced fact-checking Wikipedia / Genius could do a pretty good job debunking stuff that’s complete garbage. Contributors recognized as fair fact-checkers could get karma and monetary rewards.

Something like WikiTribune seems like a promising approach. Maybe even an industry news integrity initiative.

It’s a huge problem and solving it is critical for democracy and free market capitalism.

That being said, if you have a large chunk of people who want to tear everything down, you’re not going make progress building trust and credibility.

And fish rots from the head. If you’re led by someone with a habit of lying, denying reality, and calling everything he doesn’t like “fake news,” you’re going to continue to have a crisis of legitimacy and reality-based institutions.

Come back Kelly Evans! We’ll be good this time! I promise!

A digressive rant on the rot in the financial Twittersphere in the Trump era

If we’d been born where they were born and taught what they were taught, we would believe what they believe. – attributed to Abraham Lincoln

(who also said, “The love you take is equal to the love you make”, but that’s another story)

Spring is in the air! On the East Coast, anyway.

Last week I was fortunate to get out to the West Coast, dodging storms on this side of the country and also over there. And this week I spent a little time sprucing up StreetEYE sources, deleting people who haven’t tweeted in a while, adding the popular, influential, prolific, and relevant new sources. Every year or so around this time I’ll do an updated ranking of the top people to follow.

So I’m in the frame of mind to step back and take a look at the evolution of the financial Twittersphere.

And what I see is not great.

  • Churn. Losing great people like Kelly Evans last summer.
  • Lack of growth. Churn has always been a factor, people fall in love with social media and burn out after a couple of years. But the all-stars like Kelly Evans are not being replaced like they used to be.
  • There’s a subset of influential FinTwit people who protect accounts, allow only approved people to follow them. Or who regularly delete all their tweets, so no one can start a shitstorm over something they said a year ago. Which hurts discovery. And discovery is hard enough. Which is one of the reasons I created StreetEYE, so I would have a way of systematically finding the top people to follow.
  • And the usual garbage troll accounts devoted to stirring up bullshit. Some of which are surprisingly popular. It turns out a judicious mix of clickbait bullshit and timely entertaining commentary is a good way to amass a huge following. (Even if following those folks is a money- and sanity-losing game).
  • And the elephant in the room is Trump. Politics is all people talk about, even in the financial Twittersphere. Those Trump posts are great for engagement, but they suck out all the oxygen for intelligent conversation about markets and economics. (And are possibly terrible for Twitter, if the non-hyperpartisans start tuning out. Ever-increasing vitriol and engagement, ever-diminishing reach.)

The relatively low quality of online discussion is the thread that brings all of those together. Tragedy of the commons, adverse selection, I guess.

Twitter is great. So why does it suck so much?

We generally think most people think more or less similarly to us. We are astounded when we encounter cargo-cultists, flat-earth believers, whole societies of magical thinkers.

When we go online, we find that while our own process of social construction of reality is pretty similar to other people’s, it takes us to very different places.

If we’d been born where they were born and experienced what they experienced, would we really believe what they believe?

It can be mind-expanding that social media takes you outside your bubble, brings opposites together, like some virtual A train to Times Square. But it leads to conflict.

Now, to me, it’s pretty obvious that women often get a raw deal from society. I follow some smart, funny women who are pretty feminist. And not gonna lie, even though my left brain mostly agrees with them, the nursing of a litany of petty grievances, the constant mocking of white male privilege, ‘mansplaining’, ‘manspreading’, and whatnot, can get really annoying.1

There are also some males who are into, shall we say, non-female-friendly male culture. Pickup artists, ‘red pill’ and whatnot. Immature maybe. Lacking self-awareness and empathy. Assholes.

When those two mindsets encounter each other on social media, they’re not gonna have a good time.

Cognitive dissonance arises. Sparks fly. Much heat is generated and little light. And both sides walk away with even more strongly confirmed priors, that men and women on the other side are mean and nasty and out to oppress or emasculate them.

I share an alma mater with Barack Obama, I was a freshman when he was a senior. He talks like me, thinks like me. Well, I wish, because he’s smart and cool and funny. I’m predisposed to like him.

That same intellectual approach apparently offends a lot of people who see it as condescending.

When Donald Trump sees Obama, clearly he sees something totally different from me. I take personal offense at the whole birther thing and view it as an original sin that can never be expunged. But clearly it resonates with a lot of people, to my disgust and amazement.2

And the Trump supporters confronted with what is apparently my sort of ‘condescension’ just dig in, double down, and reinforce their views.

I don’t really know why Trump supporters support him. As Pascal said, “The heart has its reasons, which reason cannot know.” Or JP Morgan, “A man always has two reasons for the things he does – a good reason and the real reason.” I really don’t really believe ‘liberal condescension’ is the reason. That sounds a lot like the cognitive dissonance someone without self-awareness might experience when untenable positions meet inconvenient facts and reason.

Like being virulently anti-Muslim, and at the same time not understanding why Christian fundamentalist values arouse opposition.

You can’t reason someone out of an opinion they didn’t arrive at through reason in the first place. The answers are more likely to be found in mass psychology, Gustave Le Bon, in Goebbels, in the inability of Hillary Clinton to construct a narrative with mass appeal, to run as a candidate of change instead of as a machine politician of the establishment, to do electoral math (just like in 2008 vs. Obama).

As the world gets smaller, the ability to put yourself in others’ shoes a little bit is more important. It would help if people dialed down the online vitriol, learned to roll their eyes and go about their business, instead of going bananas over a dongle joke or someone wanting to tone down the pubescent male fantasy world of video games.

But civility has to be a two way street. The online hate against Obama was really something. Aligning yourself with that, positioning yourself as the leader of that, and calling people who disagree with you ‘enemies of the American people’ sure isn’t going to help.

People say there’s a problem with social ‘filter bubbles’. The underlying problem is parochialism, intolerance. People go bonkers when they encounter anything outside their norms. Was there really less of a filter bubble 40 years ago, when different parts of America were even more like different countries, with different languages, foods, music, brands, and there were only 3 networks with anodyne non-culture that filtered out anything controversial?

Is social media making us worse people? Is it making us dumber?

I’ve written a little bit about ‘fake news’, since I think I know a little about news and machine learning.

Cathy O’Neil has made a schtick out of saying that big data is a ‘weapon of math destruction‘ and problems like ‘fake news’ can’t be solved by machine learning.

She’s mostly wrong…the ‘fake news’ we’re talking about, of the ‘Pope endorses Trump’ variety, is easily detected by the 20% of the informed, critically thinking population, and so it can also be detected by robots with much better information about where it came from and how it spread. Google does a good job with spam and it’s essentially the same problem.

Cathy O’Neil is mostly right that big data relies on patterns of human-created data, that data will reflect human biases (an even more appalling example), big data is garbage in, garbage out, and you can’t dispense with old-fashioned evidence-based critical thinking, gumshoe reporting, to prime that pump of evidence-based reasoning.

And also that it may concentrate winners and losers and wealth. (Same may apply to passive investing, machine learning-based investing).

There’s a classic bias/variance tradeoff.

If you say, I’m only going to use Bloomberg-vetted information in investment decisions, you’re going to be slower to respond to new information than if you react to every tweet and blog and market rumor.

You need a filter that is adaptive enough to surface good social media experts without necessarily waiting til they become Bloomberg pundits, while not trusting every source of flackery, disinformation, and idiocy.

If everybody followed Cathy O’Neil’s advice, no one would ever have started reading some obscure but clever blogger like Cathy O’Neil, who owes her career as a big data pundit to social media, and maybe some big data-assisted discovery like Google searches, Twitter’s recommendation engine.

You need both shoe leather and tech. You need to be selective in which sources you trust, and you need technology to deploy against the armies of bots and data scientists looking to spam, deceive, and manipulate you.

Social media can make you smarter and quicker. You need both, the Cathy O’Neils and big data.

If everybody just watches CNBC, everybody gets super herdy (bias). Everybody watches different social media filters, that’s less herdy, maybe inefficient and noisy (variance).

Big data filters some of the noise, aggregators aggregate, Bloomberg goes and hires the Cathy O’Neils, that might eliminate some variance, bring back some bias, but maybe with an overall better level of discussion.

The noise level of the chattering and flaming on social media continues, occasionally something rises above the noise, gets picked up by aggregators, Bloomberg etc.

Big data isn’t inherently bad, in fact you need it on your side to to get maximum benefit from all the noise, to defeat the dark forces of spam and fake news. It’s an arms race, the forces of evil use the magic of big data and you need your own magic to counter their spell.

But it’s imperfect magic, when sophisticated, well-funded people finance CNS and Breitbart, and use sophisticated personalized marketing to raise them to a higher profile among their target audience than more balanced, fact-based sources, you need machine learning just to level the playing field a bit. And so much of the media is so self-serving and bought and sold by vested interests and you’re bombarded with so much garbage that there is no substitute for critical thinking.

On the whole these days, I’m probably more in agreement with Cathy O’Neil about big data tilting the playing field toward the forces of evil than I used to be, when it seemed everyone having access to all information anytime anywhere would be great for well-informed democracy.

Is the financial Twittersphere destined to be the Mos Eisley cantina of financial media? Does social media make participants more vile, primitive, and unhappy?

Facebook and social media are the McDonald’s of social interaction. Ubiquitous, convenient, enjoyable, not necessarily unhealthy if consumed mindfully and in moderation. But they are engineered to be highly addictive and appeal to most basic tastes and impulses.

The types of social interaction they favor are single-serving emo BS for ‘likes’. Extreme views. Comment wars. Trolling.

Sometimes there are positive viral movements like the Ice Bucket Challenge, petitions, GoFundMes for Jo Cox and Pulse victims.3

But often it’s pretty mean and nasty stuff.

One thing I think we should have learned is that Facebook’s real names work better than Twitter’s pseudonymity. (Which maybe Twitter is moving away from, gradually). Social media needs reputation management. People should be able to control whether random trolls can interact with them. Maybe people should need to accumulate reputation to post stuff, or for their posts to have reach, or people should be able to filter who can interact with them based on reputation. Maybe people should accumulate mod points to bump or bury others’ posts. But it should be transparent (which Facebook is not, at all).

Another thing we should have learned is, folks who spend their entire social lives in this highly engineered environment, are like people who only eat at McDonald’s, or never get off their couch from watching Fox or CNBC, or out of their cars.

It’s not just a ‘fake news’ problem. The whole social media ecosystem bias/variance tradeoff needs to be re-tuned for more quality and less noise.

Maybe social media would be better if there were mechanisms that encouraged people to limit their usage. Maybe it should cost reputation if you are constantly tweeting. Maybe there should be options to remind you if you’ve been online more than an hour a day, or to cut yourself off entirely when you hit your daily budget.

There are ways to optimize for quality over quantity both in what people see, and how they contribute.4

The reach and activity might go down a little, and the quality might go up a lot, paradoxically increasing reach and activity in the long run.

I don’t know how I feel about Zuck’s manifesto until it produces some real features and products (see here and here) but social media, like a mall, is a highly engineered experience, and it needs some intelligent design to not be terrible and not make the world worse.

Maybe there’s a happy medium between the Twitter free-for-all and more closed communities like SumZero and Value Investors Club. Where the worst noise is disincentivized and good stuff rises above the noise.

Social media gave us Trump. And Trump is shaping up to be a disaster. Ergo, social media is a disaster for civilization?

When I created StreetEYE, I thought social media, people freely sharing information, with the best information and the greatest people percolating to the top, was the way of the future. It hasn’t happened yet. The tools may need to evolve. It may take a new generation of platforms and tools. But it’s going to happen.

When we can give people like Kelly Evans the reason to come back.

On life’s vast ocean diversely we sail. Reason’s the card, but passion the gale. – Alexander Pope

Those who will not reason, are bigots, those who cannot, are fools, and those who dare not, are slaves. – Lord Byron

1 I can appreciate some gentle witty mocking, but to the more extreme women, maleness seems something offensive per se, while a dose of estrogen will excuse just about any misdeed. The black activist community picks battles judiciously by comparison. I’d go so far as to say most blacks are more judgmental about black lawbreakers than most white folks. Anyway, that’s one way I read those statistics showing white cops are less likely to shoot blacks than black cops. You pretty much have to kill an unarmed child to get a black protest movement going, whereas some women seem on the edge of violent uprising over a dongle joke or ‘manspreading’.

2 Blinding glimpses of the obvious: am not a Trump fan, and he’s a very weird guy, he’s outside the norms of politics, reality, decency. And not in the good way that shakes things up.

If a political opponent is going to say Obama may not be a citizen, or didn’t go to Columbia, or didn’t deserve his spot at Harvard, it doesn’t tell me anything about Obama, it tells me about the person who’s spreading that.

I have friends with personal experience with selecting editors of school newspapers, law review, etc., and your peers don’t select you unless they think 1) you’re one of the top people and 2) a decent guy they’re going to get along with. Anyone who says Obama was somehow undeserving or not legit is 1) ignorant, 2) of poor moral character, or 3) pandering to people in those groups. Which group do you think Trump is in?

One can not like Obama’s politics or as a human being but a lot of the conversation about him reflects very poorly on us as a country.

I get personally offended by people who promote the notion Obama was not legit, and Trump based his whole career off that. Where the f*** are Trump’s Fordham transcripts that somehow got him into Wharton? We know something about Ivy affirmative action for the rich too. Did Trump have the grades or scores to get into any grad school, let alone Harvard, let alone be President of Law Review? The guy doesn’t read books.

If Trump believes 10% of what comes out of his own mouth he’s 100% delusional. People really see what they want to see, and Trump is Exhibit 1 of that kind of crazy-ass magical thinking, and his supporters are in the same category … how do they not see he’s a promoter, has no deep interest in policy or ideology, knows practically nothing about economics or foreign affairs, cares about no principle or ethic beyond gratifying his ego and the chips on his shoulder, has angry, divisive views, indecent behavior that should have disqualified him, is supported by unabashed Nazis. He says stuff politicians don’t say, because when they say it and people believe it, it sinks us as a nation.

And yeah, seems kind of odd that he picks feuds with NATO, EU, Merkel, China, the Fed, the CIA, Mexico, but one country loves him and he has nothing bad to say about them…Weird! As someone once said, ‘there’s something going on there.’

He’s got the ‘B’ and ‘C’ string appointed to the Cabinet. I mean, can you even imagine Dimon or Blankfein or Paulson working for this guy? They wouldn’t even lend the guy a fiver. And on the foreign policy side it’s even worse, he has the entire national security establishment on his blacklist. And the guys who aren’t blacklisted are wary of working for him. I’m not even so worried about Trump because he’s a clown. He could start a war but I think the military and Congress wouldn’t let him. Unless there’s a dirty bomb in NY or DC and then all bets are off.

But when Trump craters, a lot of people are going to be very very angry, and I don’t think they’re going to turn to an establishment type, they’re going to turn to another candidate of change on the left or right. And I’m worried about stability in the rest of the world. If the US and the UK that had fairly rational economic policy are going populist, what the hell is going to happen in southern Europe in the next downturn? What about India, and Turkey, and the rest of the Middle East?

3 Viral memes giveth, and viral memes taketh away. Social media creates a Jo Cox murder or a Comet Ping Pong or a Dylann Roof, and then mobilizes to helps the family of the victims. Doesn’t quite even out.

4 Facebook has all the data, they can optimize for anything: duration of interaction on items, clicks through to items, people you frequently message, are tagged with, are in the same location with via your smartphone. They have an incentive to optimize for things that give them more ad revenue in the short run, but in the long run also for things that increase the depth and quality of interaction.


Some fun data-mining of StreetEYE headlines

Well, congrats to the Patriots and all my Boston homies. That was a catch and a comeback for the ages. Huger than Joe Montana back in the 80s, maybe GOAT. Y’all still should still learn to talk and to drive like normal human beings, but enjoy a legendary victory.

So, last year I did a word cloud of most common terms in 2015 StreetEYE headlines. Somehow I never got around to it around New Years this year. So here it is! (click to embiggen)

2016 StreetEYE Headline Word Cloud

Word cloud 2016

Interesting to compare … ‘Trump’ was yuge, and ‘Brexit’ was the other big one. ‘Greece’ was big in 2015, and faded like <cough> the Atlanta Falcons.

OK, while we’re clearing up unfinished business, here are the top clicked stories of 2016.

1. Economics on Buying vs Renting a House
2. A hedge fund has laid out why it is closing — and it is enough to set alarm bells ringing everywhere
3. Goldman Sachs Says It May Be Forced to Fundamentally Question How Capitalism Is Working
4. Trader exposes sexist horrors of the Wall Street ‘frat house’
5. FANG Is So 2015… BARF In 2016
6. With a single vote, England just screwed us all
7. Let Me Remind You Fuckers Who I Am, by @shitHRCcantsay
8. My very peculiar and speculative theory of why the GOP has not stopped Donald Trump
9. How Does This Hedge-Fund Manager Make So Much Money
10. Are US Stocks Overvalued?

Finally, if you’re REALLY into mad science…here’s a semantic analysis of > 1,000,000 headlines on StreetEYE (not just front page, everything that was shared by anyone on social media that we follow…this app does the analysis in your browser, so it will take a minute to download the data, and needs an up-to-date computer).

In the top right search, type a term, like ‘Trump’, then click on a completion, then click on ‘Isolate 101 data points’, and you’ll see something like the below (click to embiggen):

To try another search, choose “Show all data”, type in something new like “jpmorgan”, click on the completion, and you’ll see one like this.

What is the point? This is a way for computers to infer meaning of text based on context. Possibly it gives insight into how humans do it. A good representation of meaning can let us cluster related stories together. It can be used as an input to predict which stories will go viral, and improve the relevance and timeliness of headlines, or for other purposes like machine translation.

For the code that was used to generate the visualization inputs, see here.

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