The Human Element in Quantification

I enjoyed Felix Salmon’s piece in Wired titled “Why Quants Don’t Know Everything.” The premise of the piece is that while what quants do is important, the human element cannot be ignored.

The reason the quants win is that they’re almost always right—at least at first. They find numerical patterns or invent ingenious algorithms that increase profits or solve problems in ways that no amount of subjective experience can match. But what happens after the quants win is not always the data-driven paradise that they and their boosters expected. The more a field is run by a system, the more that system creates incentives for everyone (employees, customers, competitors) to change their behavior in perverse ways—providing more of whatever the system is designed to measure and produce, whether that actually creates any value or not. It’s a problem that can’t be solved until the quants learn a little bit from the old-fashioned ways of thinking they’ve displaced.

Felix discusses the four stages in the rise of the quants: 1) pre-disruption, 2) disruption, 3) overshoot, and 4) synthesis, described below:

It’s increasingly clear that for smart organizations, living by numbers alone simply won’t work. That’s why they arrive at stage four: synthesis—the practice of marrying quantitative insights with old-fashioned subjective experience. Nate Silver himself has written thoughtfully about examples of this in his book, The Signal and the Noise. He cites baseball, which in the post-Moneyball era adopted a “fusion approach” that leans on both statistics and scouting. Silver credits it with delivering the Boston Red Sox’s first World Series title in 86 years. Or consider weather forecasting: The National Weather Service employs meteorologists who, understanding the dynamics of weather systems, can improve forecasts by as much as 25 percent compared with computers alone. A similar synthesis holds in eco­nomic forecasting: Adding human judgment to statistical methods makes results roughly 15 percent more accurate. And it’s even true in chess: While the best computers can now easily beat the best humans, they can in turn be beaten by humans aided by computers.

Very interesting throughout, and highly recommended.

Nassim Nicholas Taleb on Role of Luck

Nassim Nicholas Taleb has a new short paper titled “Why It is No Longer a Good Idea to Be in The Investment Industry” (PDF link). The concluding argument is:

To conclude, if you are starting a career, move away from investment management and performance related lotteries as you will be competing with a swelling future spurious tail. Pick a less commoditized business or a niche where there is a small number of direct competitors. Or, if you stay in trading, become a market-maker.

Felix Salmon weighs in and argues the opposite:

The professions you really want to avoid, after reading Taleb’s paper, are not financial but rather creative. Where do you find millions of people all trying to succeed against the odds? Just look at how many bands there are, how many aspiring novelists, how many struggling artists. Nearly all of them think that if they create something great, that will improve their chances of success in their field. But given the sheer number of people they’re competing against, and given the fact that the number of breakout stars in each field is shrinking rather than growing, the fact is that just about everybody with massive success will have got there by sheer luck.

Sometimes, the luck is obvious: EL James, by all accounts, is an absolutely dreadful writer, but has still somehow managed to become a multimillionaire best-selling author. Carly Rae Jepsen has a catchy pop tune, but is only really successful because she happened to be in the right place at the right time. Dan Colen might be a fantastic self-publicist, but not particularly more so than many other, much less successful artists. And so on.

Salmon is strong in his conviction that every successful musician, artist, novelist became successful mainly because of luck. I don’t agree with that premise entirely: I believe there are things you can do to sway the chances of luck helping you along the way. But that doesn’t mean hard work, confidence, and talent should be discounted.

You Can’t Explain the Market

Chao Deng, in his piece “Memoirs of a Market Reporter,” gets it (mostly) right about analysts/reporters trying to explain the short-term movements in the market:

[The] drudgery of writing the market-close story—stocks up on this; stocks down on that—began to make me wonder whether chasing the inevitable day-to-day ups and downs of markets was worth anyone’s time. Some critics say markets reporters must suffer from A.D.D., because short-term fluctuations in stock indices really don’t matter much in the long run. They say it’s absurd to pin a single narrative on spot news involving countless individual decisions, many of them made by robots. Too often, coverage favors one slant if stocks are up and another if stocks are down when, in fact, nobody really knows.

The depressing part is that markets beg for an explanation, and the public desires one. As if an explanation can assuage our fears:

[A] volatile turn in the markets simply begged for an explanation, sending thousands of extra readers my way.

Here’s the kicker: there is no good explanation for why the markets are down today(a must-read piece by Felix Salmon):

As a general rule, if you see “fears” or “pessimism” in a market-report headline, that’s code for “the market fell and we don’t know why”, or alternatively “the market is volatile and yet we feel the need to impose some spurious causality onto it”.

This kind of thing matters — because when news organizations run enormous headlines about intraday movements in the stock market, that’s likely to panic the population as a whole. They think that they should care about such things because if it wasn’t important, the media wouldn’t be shouting about it so loudly. And they internalize other fallacious bits of journalistic laziness as well: like the idea that the direction of the stock market is a good proxy for the future health of the economy, or the idea that rising stocks are always a good thing and falling stocks are always a bad thing.

Trying to put a reason behind short-term fluctuations is ultimately useless. Remember: you can’t time the market. And don’t believe anyone that tells you they can.

Thoughts on the New York Times Paywall

Last week, the New York Times announced its paywall, after many months of deliberation and development:

Beginning March 28, visitors to NYTimes.com will be able to read 20 articles a month without paying, a limit that company executives said was intended to draw in subscription revenue from the most loyal readers while not driving away the casual visitors who make up the vast majority of the site’s traffic.

Today, the paywall went live. If you’re not familiar with the NYT paywall, take a look at the subscriptions page, and ponder for a minute the split among the three subscription options:

  • NYTIMES.COM + SMARTPHONE APP   — $15 every four weeks
  • NYTIMES.COM + TABLET APP   — $20 every four weeks
  • ALL DIGITAL ACCESS   —  $35 every four weeks

My immediate gripe upon seeing that breakdown: why discriminate between an iPhone app and the New York Times iPad app? I don’t have an iPhone, but I do have an iPad; is the experience going to be significantly better on the tablet than it is on the phone? I doubt it.

Secondly, why is there no stand-alone subscription to nytimes.com? This is absolutely baffling. In fact, the whole pricing strategy gets weirder when you do the math. Let A = cost of access to nytimes.com. Let B = cost of access to the smartphone app. Let C equal cost of access to the tablet app. We then have:

A + B = $15 (1)

A + C = $20 (2)

A + B + C = $35 (3)

Plug in equation (1) into equation (3), namely that A+B = $15, so equation (3) becomes $15+C = $35, or that C=$35-$15=$20. Then from equation 2, A + C = $20, and we see that A = $20-$20 = $0!

Does this make sense to you? It doesn’t to me. But from reading across the Web, I think I know why the New York Times devised such a pricing strategy. If you read the subscriptions page, you’ll notice that you get full access to New York Times so long as you subscribe to (paper) home delivery. You can subscribe to the Sunday New York Times for something like $13 per four weeks, which is significantly cheaper than the $35 all-access pass for four weeks. Thus the goal of the Times: to increase paper subscriptions, but more importantly, to ensure that current subscribers renew their subscriptions.

So, today is day 1 of the unveiling of the paywall, and I’m pretty sure I’ll hit my 20-article quote in the next few days. Take a look at the number of article’s I’ve read last month, broken down by section:

This number doesn’t include the articles I’ve read via the New York Times iPad app. Do I think the digital subscription is expensive? I have to agree with Felix Salmon — the digital subscription is expensive:

The NYT has decided not to make the paywall very cheap and porous in the first instance as people get used to it. $15 for four weeks might be cheap compared to the cost of a print subscription, but $195 per year is still enough money to give readers pause and to drive them elsewhere. And similarly, 20 articles per month is lower than I would have expected at launch.

However, I disagree with Felix Salmon on one point here. The paywall won’t drive me elsewhere for the news and in-depth reporting that I consistently rely from the NYT. I believe I will be able to find the articles I want to read via blogs and social media (especially following links via Twitter). If you’ve been paying attention to this blog over the last year or so, you know that I’ve linked to dozens of New York Times articles. The paywall will NOT change my blogging behavior. However, I think the paywall will change my browsing/reading behaving while I am on nytimes.com. How? I typically tend to browse articles by sections, and then click through anything that looks interesting enough to read. So, for instance, in an evening I may read five stories in the Business section, then proceed to the Science section and read a few articles there. With the paywall, I won’t have this ability/luxury, but I know I’ll find a way to access the articles I want to read.

I hope that more of you come visit this blog in the coming months because I’ll still be linking to New York Times frequently, and you’ll be able to access the NYT articles that I link here without having to worry about adding to your monthly 20-article total.

What are your thoughts on the New York Times paywall? Will you pay? If not, why not? How will you access NYT articles if you’re a devout reader but aren’t willing to subscribe to the digital subscription? Do you think the NYT paywall will fail?

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Resources:

1) The Newsonomics of The New York Times’ Pay Fence [Nieman Lab]

2) New York Times Paywall: Built for the Digital Future? [Guardian]

The Top Ten Wired Articles of 2010

I subscribed to Wired Magazine (print edition) in December of 2009. I’ve read almost all of the feature articles over the last twelve months. The following is my list of top ten Wired articles which have appeared in print from January until December of this year. I highlight notable passages from each piece as well.

(1) “The Neuroscience of Screwing Up” (January 2010). Jonah Lehrer is one of my favorite science writers (do subscribe to his excellent blog, The Frontal Cortex), and his piece in the January edition of Wired is a good way to begin this list. The piece challenges our preconceptions of the scientific process and how we make mistakes in the scientific quest for answers:

The reason we’re so resistant to anomalous information — the real reason researchers automatically assume that every unexpected result is a stupid mistake — is rooted in the way the human brain works. Over the past few decades, psychologists have dismantled the myth of objectivity. The fact is, we carefully edit our reality, searching for evidence that confirms what we already believe. Although we pretend we’re empiricists — our views dictated by nothing but the facts — we’re actually blinkered, especially when it comes to information that contradicts our theories. The problem with science, then, isn’t that most experiments fail — it’s that most failures are ignored.

(2) “Fill in the Blanks: Using Math to Turn Lo-Res Datasets into High-Res Samples” (March 2010). I highlighted this piece in this entry, and it’s still definitely of the most interesting articles I’ve read this year, not least because the entire concept of compressed sensing was totally new to me:

Compressed sensing works something like this: You’ve got a picture — of a kidney, of the president, doesn’t matter. The picture is made of 1 million pixels. In traditional imaging, that’s a million measurements you have to make. In compressed sensing, you measure only a small fraction — say, 100,000 pixels randomly selected from various parts of the image. From that starting point there is a gigantic, effectively infinite number of ways the remaining 900,000 pixels could be filled in.

(3) “Art of the Steal: On the Trail of World’s Most Ingenious Thief” (April 2010). A fascinating piece about Gerald Blanchard, who has been described as “cunning, clever, conniving, and creative.” Incredible what he was able to accomplish during his stint:

Over the years, Blanchard procured and stockpiled IDs and uniforms from various security companies and even law enforcement agencies. Sometimes, just for fun and to see whether it would work, he pretended to be a reporter so he could hang out with celebrities. He created VIP passes and applied for press cards so he could go to NHL playoff games or take a spin around the Indianapolis Motor Speedway with racing legend Mario Andretti. He met the prince of Monaco at a yacht race in Monte Carlo and interviewed Christina Aguilera at one of her concerts.

(4) “Getting LOST” (May 2010). LOST is my favorite show on television (by far), so it’s with some bias that I select this piece into the top 10. This piece has outstanding trivia about the show, an interview with executive producers Carlton Cuse and Damon Lindelof, and really excellent infographics (my favorite is this one).

(5) “The Man Who Could Unsnarl Manhattan Traffic” (June 2010). Felix Salmon (whose finance blog I follow at Reuters; unrelated, but I also recommend Salmon’s excellent take on bicycling in New York City.) reports on Charles Komanoff, the man whose goal is to alleviate traffic in New York City.

[It is ] the most ambitious effort yet to impose mathematical rigor and predictability on an inherently chaotic phenomenon. Despite decades of attempts to curb delays—adding lanes to highways, synchronizing traffic lights—planners haven’t had much success at unsnarling gridlock. A study by the Texas Transportation Institute found that in 2007, metropolitan-area drivers in the US spent an average of 36 hours stuck in traffic—up from 14 hours in 1982.

Komanoff tracks ALL of this data in a massive spreadsheet, dubbed Balanced Transportation Analyzer (warning! .xls link, 5.5MB):

Over the course of about 50 worksheets, the BTA breaks down every aspect of New York City transportation—subway revenues, traffic jams, noise pollution—in an attempt to discover which mix of tolls and surcharges would create the greatest benefit for the largest number of people.

(6) “Secret of AA” (July 2010). Some 1.2 million people belong to one of Alcoholic Anonymous’s 55,000 meeting groups in the United States. But after 75 years, we still don’t know how it works. Fascinating:

There’s no doubt that when AA works, it can be transformative. But what aspect of the program deserves most of the credit? Is it the act of surrendering to a higher power? The making of amends to people a drinker has wronged? The simple admission that you have a problem? Stunningly, even the most highly regarded AA experts have no idea.

(7) “The News Factory” (September 2010). You’ve probably seen those videos from Taiwan recounting events of the moment through hilarious animated videos (see The iPhone Antennagate; Chilean Miners). What’s fascinating is that there’s an entire company working to create these videos. Next Media Animation (NMA) is a factory churning out  videos:

The team at Next Media Animation cranks out about 20 short clips a day, most involving crimes and scandals in Hong Kong and Taiwan. But a few are focused on tabloid staples in the US—from Tiger Woods’ marital troubles to Michael Jackson’s death. Seeing them filtered through the Next Media lens is as disorienting as it is entertaining.

How can they create such impressive (relatively speaking) videos in such a short period of time?

It takes Pixar up to seven hours to render a single frame of footage—that is, to convert the computer data into video. NMA needed to create an animated clip in a third of that time and render more than a thousand frames of animation in just a few minutes. A team spent two years wrestling with the problem, experimenting with one digital tool after another—Poser, 3ds Max, Maya. “It didn’t look good, and it took too long,” says Eric Ryder, a Next art director. “But Jimmy doesn’t want excuses.”

(8) “The Nerd Superstore” (October 2010). An excellent look into ThinkGeek, a site for nerds. ThinkGeek is a profitable company that carries an assortment of products:

Today ThinkGeek has 51 employees. Single-day orders occasionally top out at $1 million, and an astonishing amount of that product is caffeine. You can purchase it online or from the mail-order catalog in the form of mints, candy, gum, jerky, sprays, capsules, chews, cookies, and powders, as well as in lip balms, brownie mix, and soaps (liquid and solid). The company has thus far pushed more than 1 billion milligrams of the stimulant.

Where else could you purchase awesome sauce, brain freeze ice cubes, and an 8-bit tie all in one place?

(9) “The Quantified City” (November 2010). What can a hundred million calls to 311 reveal about a city? Steven Johnson uses New York City as an example where the collected data is quantified:

As useful as 311 is to ordinary New Yorkers, the most intriguing thing about the service is all the information it supplies back to the city. Each complaint is logged, tagged, and mapped to make it available for subsequent analysis. In some cases, 311 simply helps New York respond more intelligently to needs that were obvious to begin with. Holidays, for example, spark reliable surges in call volume, with questions about government closings and parking regulations. On snow days, call volume spikes precipitously, which 311 anticipates with recorded messages about school closings and parking rules.

The 311 complaints, visualized in an infographic, for one week in September (question for the reader: do you think population density matters here?)

(10) “Teen Mathletes Do Battle at Algorithm Olympics” (December 2010). Excellent piece by Jason Fagone about kids competing at the International Olympiad in Informatics (IOI). While the piece focuses on two students, it’s important to note how elite this event is:

China’s approach to IOI is proof of just how serious the contest has become and how tied up it is in notions of national prestige and economic competitiveness. To earn a spot on the Chinese team, a coder has to beat 80,000 of his compatriots in a series of provincial elimination rounds that last an entire year.

But what’s the downside of such intense training and competition? I ponder the possibilities with some personal reflections in this post.

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Notes:

1) For some of the titles above, I’ve used the titles presented in the print edition of Wired (the titles are usually longer on the Web).

2) If you’re a fan of Wired, what’s your favorite article from 2010? Feel free to comment below.