Olympic gold medals contain only 1% gold — would cost $25,000 if pure


You know, someone invented the XIV ETN. And someone invented the VIX, and VIX futures. And when you read the technical specifications for all of those things, it is clear that they are not trivial feats of engineering. Teams of marketers and traders and quants and technologists and lawyers put many hours into getting them just right, so that they would work as intended. They are technologies, highly engineered tools designed to help customers do things that they couldn’t have done before. They are financial technologies, built not out of screens and circuit boards but out of formulas and hedging strategies and legal documents, but that is what you’d expect: Financial firms ought to innovate in financial technology.

Yesterday Goldman Sachs Group Inc. Chief Executive Officer Lloyd Blankfein presented at the Credit Suisse Financial Services Conference, and his presentation is kind of a weird read. The running theme is that Goldman is doing technology stuff to win business. “Engineering underpins our growth initiatives,” says a summary page, and it doesn’t mean financial engineering. In fixed income, currencies and commodities, engineers are 25 percent of headcount, and the presentation touts growth in Marquee (its client-facing software platform) and “systematic market making.” In equities, Goldman touts its quant relationships. In consumer banking (now a thing!), the centerpiece is Marcus, Goldman’s online savings and lending platform. And in investment banking, “Engineering enhances client engagement through apps, machine learning and big data analytics.” […]

Instead of developing new financial technologies, Goldman is developing new computer technologies for its financial clients.

{ Bloomberg | Continue reading }

related { Hedge-fund mediocrity is the best magic trick. Never have so many investors paid so much for such uninspiring returns. }

lithograph { Ellsworth Kelly, Camellia III, 1964–65 }

The June snows was flocking in thuckflues on the hegelstomes


There are 1,036 virtual currencies out there, from Bitcoin to — no joke — BigBoobsCoin. The price of almost every single one was down Friday morning.

{ Bloomberg | Continue reading }

Mermaids have more fin


Stock trading strategies: competition is so stiff that there are only two ways to succeed: (1) insider trading, e.g. you try to obtain job interviews with small publicly traded companies, then based on information glanned during the interview, perform trades and (2) use trading strategies that professional traders will never use, e.g. stay “all cash” for several years on your trading account, and when the right event occurs, massively trade major indexes for a couple of days, then go dormant for another few years. You need sophisticated statistical models to succeed in this, with good back testing, walk-forward and robustness based on state-of-the-art cross-validation.

{ analyticbridge | Continue reading }

art { Rochelle Goldberg, The Cannibal Actif, 2015 }

Do you know she was calling bakvandets sals from all around, nyumba noo


Two hedge fund “quants” have come up with an algorithm that diagnoses heart disease from MRI images, beating nearly 1,000 other teams in one of the most ambitious competitions in artificial intelligence.

{ Financial Times | Continue reading }

Qi Liu and Tencia Lee, hedge fund analysts and self-described “quants,” didn’t know each other before they won the competition, beating out more than 1,390 algorithms. They met each other in a forum on the Kaggle site, where the competition was hosted over a three-month period.

{ WSJ | Continue reading }

Holzwege proved a disarmingly difficult title to translate, or even understand: Holz means “wood,” and were means “paths.” Thus: “Paths in the Forest”—but Holzwege are not just any paths. They are paths made not for the forest but the trees; paths for finding and carrying wood (back to your hut), not for getting from point A to B. And when you are on one, you are, proverbially, on the wrong path.


The mantra of Wall St hedge funds was once “only the strongest will survive.” It may now have to change to “the geeks will inherit the earth.”

Hedge fund “quants” who use computer systems to trade financial markets earned more money than some of the industry’s most famous stockpickers, who posted large losses in 2015.

The most prominent among the quants was string theory expert and former code breaker James Simons of Renaissance Technologies, who earned $1.7bn, putting him in joint first place.

He was joined in the top 10 earners by former Columbia University computer science professor David Shaw of DE Shaw who made $750m and John Overdeck and David Siegel of Two Sigma who made $500m each.

Their success came in stark contrast to some of the biggest names on Wall Street who rely on human investment judgment rather than lines of computer code.

{ FT | Continue reading }

quote { Cabinet magazine | full story }

‘Nothingness haunts being.’ –Jean-Paul Sartre


It was an invitation-only party (crabs, cocktails and a D.J. on a moonlit dock) thrown by Jane Street, a secretive E.T.F. trading firm that, after years of minting money in the shadows of Wall Street, is now pitching itself to some of the largest institutional investors in the world.

And the message was clear: Jane Street, which barely existed 15 years ago and now trades more than $1 trillion a year, was ready to take on the big boys.

Much of what Jane Street, which occupies two floors of an office building at the southern tip of Manhattan, does is not known. That is by design, as the firm deploys specialized trading strategies to capture arbitrage profits by buying and selling (using its own capital) large amounts of E.T.F. shares.

It’s a risky business.

As the popularity of E.T.F.s has soared — exchange-traded funds now account for a third of all publicly traded equities — the spreads, or margins, have narrowed substantially, making it harder to profit from the difference.
And in many cases, some of the most popular E.T.F.s track hard-to-trade securities like junk bonds, emerging-market stocks and a variety of derivative products, adding an extra layer of risk. […]

While traders at large investment banks watched their screens in horror, at Jane Street, a bunch of Harvard Ph.D.s wearing flip-flops, shorts and hoodies, swung into action with a wave of buy orders. By the end of the day, the E.T.F. shares had retraced their sharp falls.

It is not only Jane Street, of course. Cantor Fitzgerald, the Knight Capital Group and the Susquehanna International Group have all capitalized on the E.T.F. explosion.

And as these firms have grown, so has the demand for a new breed of Wall Street trader — one who can build financial models and write computer code but who also has the guts to spot a market anomaly and bet big with the firm’s capital. […]

Here is a small sample of Jane Street’s main traders: Tao Wang (doctorate in philosophy and finance from the National University of Singapore), Min Zhu (master’s in chemistry, Columbia), Brett Harrison (master’s in computer science with a focus in artificial intelligence, Harvard) and Srihari Seshadri (bachelor’s in computer science, Carnegie Mellon).

{ NY Times | Continue reading }

oil on Masonite { Grant Wood, Birthplace of Herbert Hoover, 1931 }

‘History is the science of what never happens twice.’ —Paul Valéry


A recent Wall Street Journal/NBC News poll found that 49% of Americans still believe the U.S. economy is in recession, even though we are now in the sixth year of the recovery. […] If investing when others are skeptical has historically been a successful strategy, why don’t more investors do so? […] Taking advantage of the findings discussed earlier requires investing when the economy and market seem to be at their worst, and rebalancing when conditions appear to be the best. This is counterintuitive for many investors, who tend to wait for confirming evidence before acting. This is related to herd behavior, the tendency to follow the crowd with portfolio decisions. Investing when others are skeptical is emotionally difficult but, as we’ve shown, tends to be when rewards are the greatest.

{ JP Morgan Funds | PDF }

related { It is not possible for a human to know whether Bank of America made money or lost money last quarter. }

art { Jim Campbell, Ambiguous Icon #1 Running Falling, 2000 }

‘Nothing can come of nothing.’ —Shakespeare


Since The Fed’s extension of Operation Twist (and subsequent unveiling of QE3) in 2012, the stocks of “weak balance sheet” companies are up over 100%. In that same period, the stock prices of “strong balance sheet” companies are up a mere 43%.

{ ZeroHedge | Continue reading }

The last 5 days saw “strong” companies outperform “weak” companies by the most in 3 years - something appears to be changing.

{ ZeroHedge | Continue reading }

If you can look into the seeds of time, and say which grain will grow, and which will not, speak


A quarter of all public company deals may involve some kind of insider trading. […] The study [PDF], perhaps the most detailed and exhaustive of its kind, examined hundreds of transactions from 1996 through the end of 2012.

{ NY Times | Continue reading }

If at first you don’t succeed, skydiving is not for you


Long ago, stock trades were reported over ticker tape, and one type of manipulation was called “painting the tape.” Traders would enter orders to give the appearance of activity in a stock to entice others to buy shares, thus pushing the price higher.

Today, a slightly more sophisticated scheme is called “banging the close,” in which transactions are made in one market at the end of the day to benefit a trader’s positions in another market, say derivatives. Same scheme, different means. […]

The growth of high-frequency trading firms and transactions executed on alternative trading systems, called dark pools, have made it more difficult to police potential manipulative conduct. High-frequency traders buy and sell millions of financial instruments but rarely hold a position for more than a day. While such trading provides greater liquidity to the markets, helping to lower costs for all investors, it can also offer new opportunities for manipulating prices. […]

Manipulation can also involve benchmark indexes, which are incorporated into a wide variety of transactions, including mortgage interest rates. When an index relies on reports provided by rival market participants, the temptation to furnish false information to affect its value can be powerful because a small shift in value can affect billions of dollars. Several large banks have already paid billions in penalties for manipulation of the London interbank offered rate, or Libor, and investigations are gaining steam into how currency prices were reported in the foreign exchange markets.

{ NY Times | Continue reading }

Take but degree away, untune that string, and hark


High frequency trading. I won’t go into the details, but basically it has become an arms race of being a millionth of a second faster than the other guy. The exchanges (Nasdaq and NYSE) started offering co-location within their facilities and traders started fighting for the best physical real estate within the co-location center (ie. literally trying to be a few feet closer to the exchanges’ computers).  Some of the high frequency traders complained about how ‘unfair’ it was to be a few feet farther away.  The exchanges conceded and added ‘latency’, basically a few feet of cable, so everyone within the co-location center is equidistant. It baffles me financial progress is moving in this direction.

Prediction by ‘experts’/pundits. Why do people still believe in pundits and ‘experts’ on TV? If ‘experts’ could predict the future with any accuracy, they would be doing something else. They are not always wrong, they are simply not right consistently enough to provide meaningful value. I’m always surprised how confident and certain people sound on CNBC (I rarely feel sure of anything). Keynes got it right when he said, “If you must forecast, forecast often.”

{ Quora | Continue reading }

Elle Driver: [after getting covered with tobacco juice during her fight with the Bride] Gross.


On average, ATD made less than a penny on every share it traded, but it was trading hundreds of millions of shares a day. Eventually the firm moved out of Hawkes’s garage and into a $36 million modernist campus on the swampy outskirts of Charleston, S.C., some 650 miles from Wall Street.

By 2006 the firm traded between 700 million and 800 million shares a day, accounting for upwards of 9 percent of all stock market volume in the U.S. And it wasn’t alone anymore. A handful of other big electronic trading firms such as Getco, Knight Capital Group, and Citadel were on the scene, having grown out of the trading floors of the mercantile and futures exchanges in Chicago and the stock exchanges in New York. High-frequency trading was becoming more pervasive.

The definition of HFT varies, depending on whom you ask. Essentially, it’s the use of automated strategies to churn through large volumes of orders in fractions of seconds. Some firms can trade in microseconds. (Usually, these shops are trading for themselves rather than clients.) And HFT isn’t just for stocks: Speed traders have made inroads in futures, fixed income, and foreign currencies. Options, not so much. […]

By 2010, HFT accounted for more than 60 percent of all U.S. equity volume and seemed positioned to swallow the rest. […] For the first time since its inception, high-frequency trading, the bogey machine of the markets, is in retreat. According to estimates from Rosenblatt Securities, as much as two-thirds of all stock trades in the U.S. from 2008 to 2011 were executed by high-frequency firms; today it’s about half. In 2009, high-frequency traders moved about 3.25 billion shares a day. In 2012, it was 1.6 billion a day. Speed traders aren’t just trading fewer shares, they’re making less money on each trade.

{ Bloomberg | Continue reading }

related { Today’s Comforting Stat: Hedge funds are a trillion dollars in debt }