...and domination of nature, but we are not strong enough compared with nature. Ishmael clearly realized that and he said: “So have I seen Passion and Vanity stamping on the living magnanimous earth, but the earth did not alter her tides and her seasons for that.” (Herman Melville, 1999:232) Stubb had the same idea with Ishmael. He said to Starbuck:” The sea will have its way. Stubb, for one, can’t fight it. You see, Mr. Starbuck, a wave has such a great long start before it leaps, all around the world it runs, and then comes the spring.” (Herman Melville,1999:494) Therefore, in the fight between man and nature, temporary triumphs may be achieved; but finally man must be the loser. This can be seen in the end of the book. “Ahab, Queequeg, Tashtego and the rest of the Pequod’s crew (excepting Ishmael) are sucked by the sea, perhaps in the punishment for their pride in contesting against nature.”(Michael P. Branch and Scott Slovic, 2003:197) What causes the tragic end? Actually, Melville has already given us the definite answer in Moby-Dick. We can see that it is not the white whale, but the selfishness of human beings that causes the tragedy of the whaling ship, Pequod, led by Captain Ahab. In the last chapter, Starbuck thought Ahab had “heart of wrought steel” (Herman Melville,1999:553)and said to Ahab, “Moby Dick seeks thee not. It is thou, thou, that madly seekest him!”(Herman Melville, 1999: 556)Melville, through the mouth of Starbuck, reveals that human’s avaricious......
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...1. In question 1, I have assumed its only the Tashtego that makes the trip of Balik to Singapore and back. I have also assumed the relevant cost is the cargo cost only. Therefore, profit contribution of carrying I ton of tapioca from Balik and Singapore: Expected revenue $5.10 Less freight cost (0.25+0.56) 0.81 Profit Contibution 4.29 From Singapore to Balik: Expected Revenue $2.70 Less freight cost (0.16+0.32+0.14) 0.62 Profit Contribution 2.08 2. Total contribution of Tashtego for round trip is: From Singapore to Balik=(2.08*3150)= $6552 From Balik to Singapore=(4.29*3950)= 16946 Total contribution 23498 If we assume same contribution profit as Tashtego, then big vessel total contribution is: From Singapore to Balik=2.08*6850)= $14248 From Balik to Singapore=(4.29*6850)= 29387 Total Contribution 43635 3. Incremental trip costs of sending Tashtego on a round trip between Singapore and Balik is: Tashtego Trip cost Note: Tashtego take 2.5 days in balik and 1 day in singapore ...
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... In the novel Moby Dick, by Herman Melville, a microcosm lives in the Pequod. Throughout the story, the microcosm is apparent in the control and superiority of Captain Ahab, friendship, religion, and the struggles of good and evil. The Pequod symbolizes the views, actions, thoughts, and the various types of people in the world. Ahab’s power and authority show that he is the leader in this small world. He conjures allegiance and fear out of the crew. Dagoo, Tashtego, and Queequeg are the minorities on the ship(for obvious reasons) and represent the minorities of the world. They band together when one is in danger. Starbuck is very religious and portrays the devout of the world. His faith and reverence keep him sane during the long journey. The rest of the crew depicts the average people of the world. They show how gullible and vulnerable we can be sometimes. To win over the crew, Ahab uses his knowledge of human nature to coax them into helping him with his vengeance. The first thing he does is nails the gold doubloon to the mast and promises it to the first man to see Moby Dick. By doing so, he makes them remember what their reward will be when they see the whale. Next he gives them rum to reach the gluttonous side of man. This shows that we are weak and give in to pleasure. After that he cuts his palm, squeezes the blood out, drips it in the rum and tells them to drink it. This shows Ahab trying to get to the religious aspect of man by having them drink his...
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...CASE STUDY Tashtego Advanced Topics in Management Accounting and Control The purpose of this paper is to analyze the economic situation of the company Macedonian Shipping and give a recommendation whether the company should use the motor vessel Tashtego as a freight tender beween Dar-es-Salaam and Zanzibar in East Africa or as a tapioca ship between Balik Papan and Singapore in the East Indies. Fundamental to all these considerations are measurement issues. Financial measures, in particular, cost measures, are needed to evaluate alternate strategies on whether to introduce a new product or service line, to determine the appropriate sale price and the consequent market position for the firm’s product. Question 1) “Contribution” represents the portion of sales revenue that is not consumed by variable costs and so contributes to the coverage of fixed costs. To compute profit contribution that can be earned by carrying 1 ton of tapioca from Balik Papan to Singapore, dock to dock, and 1 ton of general merchandise goods from Singapore to Balik Papan only cargo costs were considered as relevant. Cargo costs of both ports have to be considered as each freight has to be reloaded at one port and unloaded at the other. Therefore, profit contribution of carrying 1 ton of tapioca from Balik and Singapore is Expected revenue $5.10 less freight cost 1,43 = $ 3,67 and from Singapore to Balik: Expected Revenue $2.70 less freight cost 1,43 = 1,27. 1. Contribution/t dock...
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...appear from below the ship. No one else has seen these men the whole time they were on their journey. Ahab readily admits to smuggling them on. They were an experienced group of harpooners, led by Fedallah. Ahab believes that Fedallah is a prophet and will help them better catch Moby-Dick. As the Pequod comes upon other vessels, Ahab demands summaries from the other captains, hoping to get information on Moby Dick's whereabouts. On one of these ships is a prophet named Gabriel who foresees death for anyone who threatens the great white whale. The crew grew worried knowing other men died coming up against Moby-Dick. Later another harpooner, Tashtego, begins to drain oil from a sperm whale's head and he suddenly falls into the head, which begins sinking into the ocean. Queequeg jumps into the ocean, cuts into the head of the whale and saves Tashtego. The crew's bad luck continues. Pip, the Pequod's cabin boy, goes crazy from being left behind temporarily on a whaleboat. The ship also comes upon Captain Boomer, who has lost an arm to Moby Dick. Unlike Ahab, Captain Boomer is simply happy to have survived his encounter with Moby Dick. He has no desire for vengeance. Queequeg falls ill but recovers. Fedallah’s prophecies provide a summary of Ahab's death. In his prophecy, Ahab will be killed by a rope made of hemp. Ahab just assumes he will die on land, not at sea. After a typhoon hits the ship Starbuck, the ship's first mate, wants to kill Ahab, believing he is going to get......
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...BOOKS ABOUT TASHTEGO CASE ANALYSIS Rdiana.com TASHTEGO CASE ANALYSIS Updated: 02/26/2015 DISCLAIMER: RDIANA.COM uses the following Tashtego Case Analysis book available for free PDF download which is also related with TASHTEGO CASE ANALYSIS Tashtego Case Analysis can be easily downloaded from our library. Don’t you believe? It is completely free. You just have to register on our site – click on the link below and answer simple questions. It will provide you for free access to Tashtego Case Analysis and other eBooks. We ask you to pass a registration because of hard hackers’ attacks that knock out of service our library and prevent our users from downloading Tashtego Case Analysis as well as other books when it is necessary. When pass the registration, you can be sure of free and unlimited access to Tashtego Case Analysis and lots of other PDF data. Files can be downloaded on your device when you want. Therefore, if you still need Tashtego Case Analysis and cannot download it from other sites, register on our site and get a free access to a rich collection of eBooks right now. Save your time and eﬀorts. PDF FILE: TASHTEGO CASE ANALYSIS Rdiana.com BOOKS ABOUT TASHTEGO CASE ANALYSIS PAGE: 2 TASHTEGO CASE ANALYSIS RR.DVI INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE An Average-case Analysis of the Gaussian Algorithm for Lattice Reduction Herve Daude , Philippe Flajolet , Brigitte Vallee N 2798 Fevrier 1996 PROGRAMME 2...
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...The purpose of this paper is to analyze the economic situation of the company Macedonian Shipping and give a recommendation whether the company should use the motor vessel Tashtego as a freight tender beween Dar-es-Salaam and Zanzibar in East Africa or as a tapioca ship between Balik Papan and Singapore in the East Indies. Fundamental to all these considerations are measurement issues. Financial measures, in particular, cost measures, are needed to evaluate alternate strategies on whether to introduce a new product or service line, to determine the appropriate sale price and the consequent market position for the firm’s product. Question 1) “Contribution” represents the portion of sales revenue that is not consumed by variable costs and so contributes to the coverage of fixed costs. To compute profit contribution that can be earned by carrying 1 ton of tapioca from Balik Papan to Singapore, dock to dock, and 1 ton of general merchandise goods from Singapore to Balik Papan only cargo costs were considered as relevant. Cargo costs of both ports have to be considered as each freight has to be reloaded at one port and unloaded at the other. Therefore, profit contribution of carrying 1 ton of tapioca from Balik and Singapore is Expected revenue $5.10 less freight cost 1,43 = $ 3,67 and from Singapore to Balik: Expected Revenue $2.70 less freight cost 1,43 = 1,27. 1. Contribution/t dock to dock | | | | | | | | | BP-SP Tapioca | | SP-BP M. goods | | | |......
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...character to sustain a conflict with the harsh materialistic world supported by dogmas and based on sea tales. Now there surfaces the long interior conflict between natural respect for the past and his equal abhorrence of its cruelty. Only the feeling of the intense emotions and guilt could even begin to answer his struggle with himself over the past. As a symbol of tragedy this picture foreshadows difficulties and grievances in lives of the characters. For instance, a story of Moby Dick is the first sign of tragedy. It is mentioned that this whale took Ahab's leg and drove him crazy. He describes: “and his spout is a big one, like a whole shock of wheat, and white as a pile of our Nantucket wool after the great annual sheep-shearing; aye, Tashtego, and he fan-tails like a split jib in a squall. Death and devils!” (Melville Chapter 36). This description reflects Ishmael’s ideas of painting and gives some hints about possible death of a person. It is illogical, but the story of a whale emphasizes that human life depends upon natural phenomenon and sea much more than we think. The story about the Town-Ho and its conflict with Moby Dick is another unifying force which joins the painting to the rest of the story. Melville stresses that the hero, like other men, lacks self-preservation instinct. In contrast, a whale who has no great intellect and “knowledge” can easily survive in any circumstances. The story tells that “the widow of Radney still turns to the sea which refuses......
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The Spouter Inn
...to sustain a conflict with the harsh materialistic world supported by dogmas and based on sea tales. Now there surfaces the long interior conflict between natural respect for the past and his equal abhorrence of its cruelty. Only the feeling of the intense emotions and guilt could even begin to answer his struggle with himself over the past. As a symbol of tragedy this picture foreshadows difficulties and grievances in lives of the characters. For instance, a story of Moby Dick is the first sign of tragedy. It is mentioned that this whale took Ahab's leg and drove him crazy. He describes: “and his spout is a big one, like a whole shock of wheat, and white as a pile of our Nantucket wool after the great annual sheep-shearing; aye, Tashtego, and he fan-tails like a split jib in a squall. Death and devils!” (Melville Chapter 36). This description reflects Ishmael’s ideas of painting and gives some hints about possible death of a person. It is illogical, but the story of a whale emphasizes that human life depends upon natural phenomenon and sea much more than we think. The story about the Town-Ho and its conflict with Moby Dick is another unifying force which joins the painting to the rest of the story. Melville stresses that the hero, like other men, lacks self-preservation instinct. In contrast, a whale who has no great intellect and “knowledge” can easily survive in any circumstances. The story tells that “the widow of Radney still turns to the sea which refuses......
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It’s no secretthat, these days, a single post on social media can have a dramatic impact. Consider two days in January 2013 when a series of damning—but false—tweets sent two stocks plunging. Some of the posts claimed that a company called Audience was being criminally investigated for “rumored fraud.” A second set claimed that the FDA had seized clinical-trial records of Sarepta Therapeutics (SRPT) on suspicions the results had been “doctored.” Only later did many readers notice that the authors were not in fact the well-known short-selling firms Muddy Waters and Citron Research, but rather two fake accounts using similar names with misspellings: @Mudd1waters and @Citreonresearc. The stocks fell 28% and 16%, respectively.
But there’s a surprising coda to this anecdote. Despite fooling the market, the perpetrator managed to net only $97 from his deception. By the time he bought shares of each a mere 10 minutes after his tweets moved the market, it was too late. Other investors—some, no doubt, using their own social media tools—had figured out the ruse, and the share prices almost instantly bounced back. So says the Securities and Exchange Commission, which filed suit against the alleged social media scammer, a Scottish man, in November. The SEC’s case, which was accompanied by a federal criminal indictment, is the first to charge market manipulation via Twitter. (The accused has reportedly denied any wrongdoing.)
The episode reveals a lot about ways investors are using Twitter (TWTR) and the like to guide trading decisions. Increasingly, there’s a new technological race in which hedge funds and other well-heeled investors armed with big-data analytics instantly analyze millions of Twitter messages and other non-traditional information sources to buy and sell stocks faster than smaller investors can hit “retweet.”
Irish research firm Eagle Alpha, for example, digested 7,416 comments on a Reddit gaming thread in October to predict that Electronic Arts (EA) would sell more of its new Star Wars videogame than it had projected; Electronic Arts soon raised its sales forecast, citing “excitement” over the game. Monitoring web traffic on Alexa.com this spring, the quant team at Goldman Sachs Asset Management noticed a spike in visits to HomeDepot.com (HD) and loaded up on the home-improvement stock months before the company increased its outlook and shares surged. “You have this explosion of other independent real-time sources. It’s a lot easier to get to [on-the-ground] truth,” says Matthew Granade, chief of the newly created data-crunching team at Point72, the reincarnation of Steven Cohen’s hedge fund SAC Capital Advisors. “Overall, I think this is a golden age for new investment data sources.”
Ted Bailey at Dataminr’s offices, with a display showing his company’s stream behind him.Photograph by Patrick James Miller for Fortune Magazine
That has meant a wave of demand for services such as Dataminr, which applies advanced analytics to the entire Twitter “fire hose” to detect events likely to move the market. Founded in 2009 by three former Yale roommates, the company now has roughly 75 financial clients—up from 50 a year ago—including the majority of big investment banks and at least half the top hedge funds, overseeing a collective $1 trillion in assets. (Dataminr’s customers also include Fortune 500 companies, media outlets, and government entities.)
“Dataminr feeds are like table stakes right now: Most hedge funds need to have it,” says Santo Politi, a founder of Spark Capital, a venture capital firm that was an early backer of Twitter and has a majority stake in a two-year-old hedge fund, Tashtego, that trades on signals from social media and other nontraditional data.
Whether or not they use Dataminr, hedgies are increasingly paying attention to Twitter and its ilk. “They’re just now starting to take advantage of what’s available through social media and this wisdom-of-crowds concept,” says Divya Narendra, founder of SumZero, a social network for pro investors. “That’s a new phenomenon.” But how to best take advantage of it—or even whether to do so—is a subject of sharp dispute.
When Dataminr launched six years ago, a billion tweets had been posted over Twitter’s history. Now that quantity is produced every two days. Dataminr founder and CEO Ted Bailey saw opportunity. His company became one of the first to buy direct access to the entire stream of tweets. Today it remains one of few companies that still have it; Twitter cut off the full feed for some companies in 2015 after acquiring Gnip, which resells social media data to analytics businesses and other clients. Access to the complete Twitter stream costs about $30,000 a month, with fees based on usage that can take the charges up to $1.5 million a year, according to people who have used the data.
A key reason for Dataminr’s prime position: Twitter owns a stake in it, according to Tom Glocer, another investor in Dataminr and a board member of Morgan Stanley (MS) (which is itself a client of Dataminr’s). That’s one of the service’s “big differentiating advantages,” he says. Bailey would only shrug when asked about the investment—or any of his company’s finances. Twitter declined to discuss its agreements or prices, but it says a growing number of hedge funds are buying its feeds directly.
Matthew Granade, who heads the data-crunching team at hedge fund Point72, the reincarnation of SAC Capital, calls this a “golden age for new investment data sources.”Photograph by Christopher Lane for Fortune Magazine
At 34, Bailey doesn’t lack self-assurance, though he may lack sleep—he’s got dark circles under deep-set eyes. Tall and with a grin just short of a smirk, he’s sitting in Dataminr’s headquarters in Manhattan’s Koreatown. Bailey expects to double his staff—currently about 200 employees divided among offices in New York City, Washington, D.C., London, and Bozeman, Mont.—over the next year. “At this time we are the leader, if not the only [company] that really has built these products and been successful,” he says. Bailey has lofty ambitions. He wants Dataminr to be “an industry-defining company that’s around for a long time, that’s a very significant, large company.”
Bailey sees almost limitless uses for his technology. “It’s pretty hard to come up with industries that would be happy knowing later, less, and not everything,” he says. “So if you think of it that way, the opportunity for Dataminr really is as big as the need for early information, more information, and full context on information and events around the world.”
Today, Dataminr specializes in identifying black-swan events, or “unknown unknowns,” as Bailey calls them, before the market reacts. It uses machine learning and cross-references 30 other data sets—from maps to triangulate users’ locations, to patent data, to stocks’ movement—to identify tweets and trends with impact, based on unusual patterns and “clusters” of similar tweets.
Using this method, Dataminr says it delivers early intel to its clients. Translating tweets from French and German, the service began alerting clients to the terrorist attacks in Paris five minutes after the first occurred outside the Stade de France, more than 45 minutes before the Associated Press tweeted the news. Dataminr revealed preliminary reports of Volkswagen’s emissions scandal three days before its stock price plummeted 30%. Oil and gas traders, Bailey says, received alerts about the death of the King of Saudi Arabia more than four hours before crude prices spiked on the news.
Dataminr is the biggest player in a nascent industry—call it alternative big data for big finance—that has exploded in the past six months: In March it raised $130 million from Fidelity as well as other investors, including former Citigroup (C) CEO Vikram Pandit, valuing the company at $700 million. (Since then, Fidelity, which owns 10% of Dataminr, marked down the value of its stake by more than a third. Dataminr declined to comment, but a person close to the startup contends the move reflects a change in general market conditions and not Dataminr’s prospects.)
Social Media Market Movers
These days, all it takes is a few words on Twitter to send a stock reeling—or climbing.
Immediate result: Mallinckrodt shares dropped by 25% before recovering.
Immediate result: Two top corrections-company stocks fell 6% and 4%, respectively.
Immediate result: Twitter shares jumped by 5%.
It’s tricky to determine how much funding is flowing to companies like Dataminr, but the amount appears to be rising. Financial technology (“fintech”) startups have received more than $11 billion in venture capital funding so far this year, 83% more than all of last year, according to CB Insights. Banks like Citigroup and Goldman Sachs (GS) (another Dataminr investor) have backed 15 of those companies in 2015, compared with nine last year. CB Insights doesn’t specify what portion of those investments were for data analytics but says it’s a “hot” and growing category.
Twitter is only one of many new hoses from which investors are guzzling. Whereas hedge funds once might have sent an analyst to count cars in retailers’ parking lots to inform their earnings models, they’re now deploying web-crawling bots to vacuum info from online job-listing sites, Amazon (AMZN) reviews, Wikipedia, Zillow (Z) home-value records, FDA patient complaints, and the remotest reaches of the Internet. Investors are “scraping” retailers’ online stores for prices and inventory, or nearly buying (then quickly canceling) tickets on Expedia (EXPE) to figure out how many seats are left on every airplane.
Even fintech startups that don’t specialize in analytics, such as SumZero, StockTwits, and Scutify, have begun fielding requests from hedge funds wanting to buy their data, such as what stocks their users are searching for, which is seen as a potential proxy for bullishness.
Dataminr doesn’t sell a product to individual investors. But social media input is starting to leach into even mainstream websites. For example, Fidelity in November added a “social sentiment” score from Dataminr rival Social Market Analytics to its stock research pages.
Not everyone is a believer in the investing value of social media. “There certainly is a lot of skepticism,” says Franklin Gold, senior vice president for research and education at Fidelity. Shanta Puchtler, co–chief investment officer at Man Numeric, a division of Man Group, one of the world’s largest hedge fund firms, with $77 billion under management, says his team hasn’t been able to glean actionable insights from social media. “There’s this romantic notion that Twitter tweets are investable and you can make lots of money if you jump on them,” Puchtler says. “You do have to ask yourself the question, ‘Where is the value?’ ”
For all their reach, social media analytics can misfire. One large quant hedge fund got stung when its algorithm confused sarcastic tweets about Lululemon’s (LULU) see-through pants debacle with positive sentiment, buying shares in the yoga-apparel retailer when it should have been selling. “At some point in time, everyone has gotten burned by something that happened on Twitter,” says Joe Gits, CEO of Social Market Analytics.
Early damage to the concept was done by a short-lived British hedge fund, Derwent Capital Markets, which announced it was launching the world’s first “Twitter Fund” to much fanfare in 2011, only to shut it down a month later. Derwent’s founder, Paul Hawtin, popped up again in the Caribbean in 2013 promoting a new firm with a similar strategy but fell off the radar a year ago.
Dataminr’s Bailey says his company is getting better at separating wheat from chaff. But one challenge is perpetual: the eternally changing nature of the crowd on social media. Twitter users join—then deactivate their accounts. They delete tweets. A pattern detected can abruptly disappear. It means that analytics companies must constantly adjust their algorithms and models.
Some early believers fear that Twitter data has become so pervasive that it no longer offers an edge. David Lewis, head Americas trader at $800 billion asset manager Franklin Templeton, for example, found out that Russia had invaded Crimea last year well before the news hit major media because he’d been monitoring Twitter. Since then, though, he says, the social media headstarts have narrowed, and he dropped a trial of a Twitter-based alert system. “News just travels a heck of a lot faster,” says Lewis. “I think those opportunities are becoming more difficult because this data is more widely shared or information is easier to get. No one really has a monopoly on information anymore.”
That’s naive, counters Gene Ekster, a consultant who helps hedge funds implement alternative data strategies. “There is no way you’re going to arbitrage the alpha out of Twitter data,” he says. “It’s crazy to think. You can analyze it in an infinite number of ways.” Still, aware that investors might view it as losing its leg up, Dataminr just launched a custom product—which funds can use to blend its algorithms with their own to get alerts that their rivals won’t have.
How should an investor make use of social media data? Here, too, there is disagreement. Those who invest for the long term argue vehemently that, at most, Twitter data is one small piece of a much bigger mosaic. But plenty of momentum-oriented short-term traders seem to be buying and selling purely on social media.
Witness, for example, the way tweets from the real Citron Research recently pounded shares of pharma firms Valeant (VRX) and Mallinckrodt (MNK) . (Says Citron’s Andrew Left: “It’s like I’m a Kardashian. People are actually following my tweets. Crazy.”) And within a span of six weeks this fall, Hillary Clinton caused a drop in biotech stocks with a tweet calling for greater regulation of drug prices, then single-handedly tanked stocks of private-corrections companies when she tweeted about prison reform. Then there was the “hash crash” of 2013, when the Dow dropped 145 points in two minutes after someone hacked the Associated Press’s Twitter account and posted, falsely, that explosions in the White House had injured President Obama. “We’re starting to call it the dumb money, because these algos are reacting on the basis of some really stupid stuff,” says Leigh Drogen, CEO of Estimize, which crowdsources corporate earnings estimates.
Still, the studies that have examined this new field so far have largely supported the notion that analyzing social media can be useful in investing. Sentiment as surmised from social media correctly predicted which way the Dow would move three days later 87% of the time, according to a 2011 study by Johan Bollen, an associate professor at the Indiana University School of Informatics and Computing. In July, Eli Bartov, a professor at New York University Stern School of Business and two other researchers found that “aggregate opinion” from tweets before earnings announcements could predict earnings surprises as well as market reactions for individual stocks, leading to outperformance of 5% to 10% per year.
Bollen recently started a company, Guidewave Consulting, to sell the patented signals he describes as “sensing the zeitgeist among investors.” He says those signals have produced the highest returns when computers trade on them automatically, without the second-guessing of a human being.
Web scraping and other alternative data collection practices are already fueling debate over what constitutes nonpublic information and insider trading—and whether investors can misuse information even when it’s public and legally obtained.SumZero, for one, discovered that one of its users attempted to scrape all the research published by investors on its site, violating the startup’s policies.
Certainly, using technology to gather web data seems innocent compared with, say, cybertheft. But data miners and analytics companies say it’s a finer line than investors often realize; consultant Ekster, for example, says investors can receive cease-and-desist orders for scraping publicly available data. The website for Harvest Exchange, another online investor community, slowed because an algorithm in Florida was checking multiple hedge fund managers’ profiles every 10 seconds to see if they had posted any potentially market-moving ideas. (The site banned the offending IP addresses.)
The SEC set up its own data-mining unit a few years ago to help it catch market fraud. Social media has complicated that task. “In a world where information travels very, very fast and through different media, figuring out whether information is public or not is challenging,” says Daniel Hawke, the former chief of the SEC’s market abuse unit, who recently joined Washington, D.C., law firm Arnold & Porter.
Perhaps the most poetic example of the power of social media mining occurred in April. That’s when a startup called Selerity, which plumbs the web for earnings reports, detected results for Twitter itself. The information had accidentally been posted an hour early. Within three seconds, Selerity’s bots synthesized the report into less than 140 characters and tweeted it out; four seconds after that the market was moving. Many people accused Selerity of hacking or having been leaked the data (which, according to Nasdaq, was available for only 45 seconds before it was taken down). But Selerity insisted it had merely visited Twitter’s website. CEO Ryan Terpstra points out that anyone with a web browser could have accomplished that: “Just keep clicking ‘Refresh.’ ”
A version of this article appears in the December 15, 2015 issue of Fortune with the headline “Trading on Tweets.”
For more features from Fortune’s Investor’s Guide, click here; for more online Investor’s Guide coverage, click here.
Editor’s note: This article has been updated to reflect the debate surrounding public vs. nonpublic information more completely, and to more precisely describe the website issues Harvest Exchange experienced due to a scraping algorithm.
For more on Twitter, watch this Fortune video: