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jerryking : unconventional   11

Algos know more about us than we do about ourselves
NOVEMBER 24, 2017 | Financial Time | John Dizard.

When intelligence collectors and analysts take an interest in you, they usually start not by monitoring the content of your calls or messages, but by looking at the patterns of your communications. Who are you calling, how often and in what sequence? What topics do you comment on in social media?

This is called traffic analysis, and it can give a pretty good notion of what you and the people you know are thinking and what you are preparing to do. Traffic analysis started as a military intelligence methodology, and became systematic around the first world war. Without even knowing the content of encrypted messages, traffic analysts could map out an enemy “order of battle” or disposition of forces, and make inferences about commanders’ intentions.

Traffic analysis techniques can also cut through the petabytes of redundant babble and chatter in the financial and political worlds. Even with state secrecy and the forests of non-disclosure agreements around “proprietary” investment or trading algorithms, crowds can be remarkably revealing in their open-source posts on social media.

Predata, a three-year-old New York and Washington-based predictive data analytics provider, has a Princeton-intensive crew of engineers and international affairs graduates working on early “signals” of market and political events. Predata trawls the open metadata for users of Twitter, Wikipedia, YouTube, Reddit and other social media, and analyses it to find indicators of future price moves or official actions.

I have been following their signals for a while and find them to be useful indicators. Predata started by creating political risk indicators, such as Iran-Saudi antagonism, Italian or Chilean labour unrest, or the relative enthusiasm for French political parties. Since the beginning of this year, they have been developing signals for financial and commodities markets.

The 1-9-90 rule
1 per cent of internet users initiate discussions or content, 9 per cent transmit content or participate occasionally and 90 per cent are consumers or ‘lurkers’

Using the example of the company’s BoJ signal. For this, Predata collects the metadata from 300 sources, such as Twitter users, contested Wikipedia edits or YouTube items created by Japanese monetary policy geeks. Of those, at any time perhaps 100 are important, and 8 to 10 turn out to be predictive....This is where you need some domain knowledge [domain expertise = industry expertise]. It turns out that Twitter is pretty important for monetary policy, along with the Japanese-language Wiki page for the Bank of Japan, or, say, a YouTube video of [BoJ governor] Haruhiko Kuroda’s cross-examination before a Diet parliamentary committee.

“Then you build a network of candidate discussions [JK: training beds] and look for the pattern those took before historical moves. The machine-learning algorithm goes back and picks the leads and lags between traffic and monetary policy events.” [Jk: Large data sets with known correct answers serve as a training bed and then new data serves as a test bed]

Typically, Predata’s algos seem to be able to signal changes in policy or big price moves [jk: inflection points] somewhere between 2 days and 2 weeks in advance. Unlike some academic Twitter scholars, Predata does not do systematic sentiment analysis of tweets or Wikipedia edits. “We only look for how many people there are in the conversation and comments, and how many people disagreed with each other. We call the latter the coefficient of contestation,” Mr Shinn says.

The lead time for Twitter, Wiki or other social media signals varies from one market to another. Foreign exchange markets typically move within days, bond yields within a few days to a week, and commodities prices within a week to two weeks. “If nothing happens within 30 days,” says Mr Lee, “then we say we are wrong.”
algorithms  alternative_data  Bank_of_Japan  commodities  economics  economic_data  financial_markets  industry_expertise  inflection_points  intelligence_analysts  lead_time  machine_learning  massive_data_sets  metadata  non-traditional  Predata  predictive_analytics  political_risk  signals  social_media  spycraft  traffic_analysis  training_beds  Twitter  unconventional 
november 2017 by jerryking
Goldman breaks tradition with unconventional choice
December 17/ December 18, 2016 | Financial Times | Ben McLannahan.

His promotion to chief information officer in 2013 ― after a stint at Credit Suisse and Kiodex, an energy trading software company ― meant that he sat atop Goldman’s biggest division, accounting for about one-third of global headcount.

A big part of that job has been bringing down the amount the bank spends on maintaining old systems, which consume about one-third of Goldman’s annual $3bn tech budgets, according to estimates by Credit Suisse analysts.

He has also taken a page out of Google and Facebook’s playbook and started giving away some of the bank’s trading technology to clients via open-source software, inviting them to use it and improve it.

What sets Mr Chavez apart is “his ability to take decisive action based on what the world will look like in five to 10 years”, says Tom Farley, president of the New York Stock Exchange, who worked with him at Kiodex. “Other people may have a view of the future but they’re afraid to act on it.”

In an address to Goldman interns this summer, Mr Chavez told them that as a new graduate, he wanted to “get busy and do a bunch of things”. When he landed on Wall Street, he learnt that people called that attitude “optionality”.

“You don’t know that these options are going to be worth something, but if you do the work, pay the premium, own a whole bunch of these options on a lot of different outcomes and you’re diversified enough, probably something will work out,” he said.
Goldman_Sachs  Martin_Chavez  CFOs  appointments  Wall_Street  unconventional  SecDB  databases  generating_strategic_options  forward_looking  CIOs  Hispanics  optionality  new_graduates  legacy_tech  playbooks 
december 2016 by jerryking
Wall Street’s Insatiable Lust: Data, Data, Data
By BRADLEY HOPE
Updated Sept. 12, 2016

One of his best strategies is to attend the most seemingly mundane gatherings, such as the Association for Healthcare Resource & Materials Management conference in San Diego last year, and the National Industrial Transportation League event in New Orleans.

“I walk the floor, try to talk to companies and get a sense within an industry of who collects data that could provide a unique insight into that industry,” he said.....Data hunters scour the business world for companies that have data useful for predicting the stock prices of other companies. For instance, a company that processes transactions at stores could have market-moving information on how certain products or brands are selling or a company that provides software to hospitals could give insights into how specific medical devices are being used......A host of startups also are trying to make it easier for funds without high-powered data-science staffers to get the same insights. One, called Quandl Inc., based in Toronto, offers a platform that includes traditional market data alongside several “alternative” data....
alternative_data  conferences  data  data_hunting  hedge_funds  insights  investors  exhaust_data  market_moving  medical_devices  mundane  private_equity  Quandl  quants  sentiment_analysis  unconventional  unglamorous  Wall_Street 
september 2016 by jerryking
Entering China: an unconventional approach
March 1997 | Harvard Business Review | Wilfried Vanhonacker.
If you're thinking about doing business in China, you've heard the conventional wisdom that the best way to enter China is through an equity joint venture (EJV) with a well-connected Chinese partner. China is changing, and so are the opportunities and challenges facing foreign companies that want to operate within its borders. Although EJVs are still necessary in some regulated sectors, and foreign investment is prohibited in others, there is a growing trend toward a new and possibly much more effective way of doing business in China - as a wholly foreign-owned enterprise, or WFOE. EJVs and WFOEs are substantially the same in terms of taxation and corporate liability. They also operate under similar foreign-exchange rules and comparable import and export regulations for licencing, quotas, and duties. Their only real technical differences are that WFOEs take less time to establish than EJVs, are not required to have a board of directors and are prohibited in some sectors in which EJVs are approved.
China  market_entry  howto  guanxi  HBR  unconventional 
january 2013 by jerryking
Spying as Networking: Alleged Spies Used Unconventional Methods - WSJ.com
JULY 1, 2010 | Wall Street Journal | PAUL SONNE, CASSELL BRYAN-LOW And APARAJITA SAHA-BUBNA
espionage  security_&_intelligence  Russia  unconventional 
july 2010 by jerryking
: The Politically Incorrect Guide to Ending Poverty
July/August 2010 | The Atlantic Magazine | By Sebastian
Mallaby. In the 1990s, Paul Romer revolutionized economics. In the
aughts, he became rich as a software entrepreneur. Now he’s trying to
help the poorest countries grow rich—by convincing them to establish
foreign-run “charter cities” within their borders. Romer’s idea is
unconventional, even neo-colonial—the best analogy is Britain’s historic
lease of Hong Kong. And against all odds, he just might make it happen.
noughties  poverty  economic_development  Paul_Romer  rules_of_the_game  neocolonialism  recolonization  analogies  unconventional  city-states  political_correctness  enclaves  Hong_Kong  economic  economists 
june 2010 by jerryking
New Economists Scour Urban Data for Trends - WSJ.com
APRIL 8, 2010 | Wall Street Journal | by CARI TUNA. New Ways
to Read Economy. Experts Scour Oddball Data to Help See Trends Before
Official Information Is Available. A growing number of economists and
urban planners [are] scouring for economic clues in unconventional urban
data—oddball measures of how people are moving, spending and working.
"Mr. Egan said he would like to build software to monitor Craigslist
prices for furniture, concert tickets, haircuts and other goods and
services to measure changes in local prices. The online classified-ads
site, he said, would give a quicker and more detailed read than the
bimonthly data from the Labor Department."

Broadway ticket sales are a favorite indicator for the chief economist of the New York City Economic Development Corp., Francesco Brindisi. He says they are a good gauge of city tourism.

In Jacksonville, Fla., community planner Ben Warner keeps tabs on calls to the city's 2-1-1 hotline for social services. Since late 2008, he has seen spikes in calls for help with food, housing, utilities payments and suicide prevention. It is "direct, real-time monitoring of the economic and social situation," he said.
data  urban  unconventional_thinking  economic_analyses  craigslist  Hal_Varian  hotlines  massive_data_sets  Freshbooks  economists  trends  pattern_recognition  measurements  real-time  forecasting  indicators  unorthodox  economic_data  metrics  Cari_Tuna  data_driven  unconventional  economics  non-traditional 
april 2010 by jerryking
How to Value the Advertising-Supported Internet - John Quelch - Harvard Business Review
John Quelch

10:15 AM Monday June 29, 2009 | Comments (13)

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valuations  performance_reviews  John_Quelch  unconventional  Haiti  HBR  motivations  social_media  advertising 
february 2010 by jerryking

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