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jerryking : signals   33

What meeting Bernie Madoff taught me about our inability to read others
October 2, 2019 | Financial Times | by Gillian Tett.

Books:
Talking to Strangers, by Malcolm Gladwell.
The Human Swarm, by Mark Moffett.

Malcolm Gladwell, the writer, earned fame — and fortune — by producing books such as The Tipping Point (2000) that popularised human psychology. In his new study, Talking to Strangers, he looks at our propensity to misread other people. It is an increasingly pressing question for our polarised, fake-news era.

How should we interpret the signals we receive from others? This matters when it comes to detecting fraud, of course......It also matters in other ways. Today more than ever, we all suffer if we misread the signals we receive from different social groups. It is human nature to assume our own culture is the definition of “normal”, and to use this lens when we view others.....even traits that we assume are ­“universal”, such as [jck: visual cues] facial expressions, can vary hugely between cultures — and, of course, within societies that speak the same language.

Gladwell describes, for example, how social interactions between black and white communities in America are regularly marred by misunderstandings, with tragic consequences. “[This] is what happens when a society does not know how to talk to strangers,” he concludes.......Moffett then advances two broader points. First, he argues that humans (like ants) need a sense of tribal identity and belonging, with specialisations clearly defined; but, second, he insists that the way humans develop this tribal identity is crucially different from other animals.

Among some species, such as chimpanzees, trust only emerges through face-to-face contact between individuals in small groups; in others, creatures only co-operate if they can be instantly identified as coming from the same species. Ants kill anything that smells different.....what is amazing about humans – albeit rarely celebrated – is how we generally tolerate outsiders ­without instantly needing to kill them.

“Being comfortable around unfamiliar members of our society gave humans advantages from the get-go and made nations possible,” Moffett writes. “Chimpanzees need to know everybody [to ­tolerate them]. Ants need to know nobody. Humans only need to know somebody [for society to function.]” This achievement deserves far more attention, since it only works in two conditions. First, humans must feel secure in their own group (which they signal with symbols and rituals); second, “strangers” can only be smoothly absorbed if everyone learns to read different symbols too....If we want to “talk to strangers”, we need to teach our kids (and ourselves) to try to look at the world through strangers’ eyes – even if we must also recognise that we will never truly succeed.
assumptions   Bernard_Madoff   books  character_traits   cultural_identity  deception Gillian_Tett   group_identity   lying   Malcolm_Gladwell   misinterpretations  misjudgement       psychology   psychopaths  signals  strangers  tribes  trustworthiness visual_cues  writers  
16 days ago by jerryking
How Spotify’s algorithms are ruining music
May 2, 2019 | Financial Times | Michael Hann.

(1) FINAL DAYS OF EMI, By Eamonn Forde, Omnibus, RRP£20, 320 pages
(2) SPOTIFY TEARDOWN, By Maria Eriksson, Rasmus Fleischer, Anna Johansson, Pelle Snickars and Patrick Vonderau, The MIT Press, RRP£14.99, 288 pages
(3) WAYS OF HEARING, By Damon Krukowski, The MIT Press, RRP£14.99, 136 pages

In April, the IFPI — the global body of the recording industry — released its latest annual Global Music Report. For the fourth consecutive year, revenues were up, to a total of $19.1bn, from a low of $14.3bn in 2014. Nearly half those revenues came from music streaming, driven by a 33 per cent rise in paid subscriptions to services such as Spotify, Apple Music and Tidal...... It is worth remembering that 20 years ago, the IFPI reported global music revenues of $38.6bn. Today’s “booming” recording industry is less than half the size it was at the turn of the century.....The nadir for the recording industry coincided with the first shoots of its regrowth. ....In August 2007, the British record company EMI — the fourth of the majors, alongside Universal, Sony and Warner — was bought by private equity firm Terra Firma (Guy Hands, the fund’s founder and chairman) for $4.7bn; a year later, a Swedish company called Spotify took its music streaming service public. The former was, perhaps, the last gasp of the old way of doing things — less than four years after buying EMI, Terra Firma was unable to meet its debts, and ceded control of the company to its main lender, Citigroup. Before 2011 was out, the process of breaking up EMI had begun...EMI’s demise was foreshadowed before Hands arrived, with a blaze of hubris in the early 2000s. Forde, a longtime observer and chronicler of the music business recounts the “disastrous and expensive” signings of that era......Handspreached the need to use data when signing artists, not just the “golden ears” of talent scouts; data are now a key part of the talent-spotting process.

* to qualify as having been listened to on Spotify, a song has to have been played for 30 seconds.
* hit songs have become increasingly predictable, offering up all their pleasures in the opening half-minute. Their makers dare not risk scaring off listeners.
* for all the money that the streaming services have generated for the music industry, very little of it flows back to any musicians except the select few who dominate the streaming statistics,

.......On Spotify, music consumption has been reorganised around “behaviours, feelings and moods” channelled through curated playlists and motivational messages......The data Spotify collects enable the industry to work out who its market is, where it lives, what else they like, how often they listen to music — almost anything, really. It’s the greatest assemblage of information about music listeners in history, and it has profoundly altered the industry: it has made Spotify music’s kingmaker......when an artist travels abroad to promote a new album, the meeting with the local Spotify office is more important than the TV appearances or the newspaper interviews. ...Spotify enables artists to plan their band’s set lists so they can play the most popular song in any given city.............So what? What does it matter if one model of music distribution has been replaced by another.....It matters because Spotify has profoundly changed the listener’s relationship with music....Older musicians often wax about how, when you had to buy your own music as a kid, you listened to it until you liked it, because you wouldn’t be able to afford a new album for another month. Now you simply skip to the next one, and probably don’t give it your full attention. Without ownership, there’s no incentive to study...........Faced with the impossibly wide choice of Spotify, it becomes easier to return to old favourites — easier than when flicking through your vinyl or CDs, because the act of looking through your own music makes things you had not thought of in years leap out at you. Spotify actually makes people into more conservative listeners, a process aided by its algorithms, which steer you towards music similar to your most frequent listening.....The theme of Krukowski’s book is that the changes in the way the music industry works have been about controlling and eliminating excess noise. That’s in a literal sense and in a metaphorical one, too. Streaming has stripped music of context, pared it back to being just about the song and the moment....but noise is the context of life. Without noise, the signal becomes meaningless......The world of the old EMI was one of both signal and noise; where myths and legends could be created: The Beatles! Queen! The Beach Boys! Pink Floyd! It was never all about the signal. The world of Spotify is one of signal only, and if you don’t appreciate that signal within the first 30 seconds of the song...all may be lost
abundance  algorithms  Apple_Music  books  book_reviews  business_models  curation  cultural_transmission  data  decontextualization  EMI  gatekeepers  Guy_Hands  hits  indoctrination  iTunes  legacy_artists  music  music_catalogues  music_labels  music_industry  music_publishing  noise  piracy  platforms  playlists  royalties  ruination  securitization  signals  songs  Spotify  streaming  subscriptions  talent  talent_scouting  talent_spotting  Terra_Firma  Tidal  transformational 
may 2019 by jerryking
What to Do When You’re Bored With Your Routines
March 29, 2019 | The New York Times | By Juli Fraga.

Boredom isn’t a character flaw. It’s a state brought on by a behavioral phenomenon called hedonic adaptation: the tendency for us to get used to things over time. This explains why initially gratifying activities and relationships can sometimes lose their luster. “Humans are remarkably good at growing accustomed to the positive and negative changes in their lives,” Sometimes this is a good thing, like when “it comes to adversities like losing a loved one, divorce or downsizing,” .....“We adjust fairly well, but this same flexibility can be detrimental to how we respond to positive life events.”....Think about the last time you got a raise, bought a new car, moved to a new city or fell in love. At first these experiences bring about an immense sense of joy, but over time they all just become part of the routine. We adjust our expectations and move on, ready for the next thing that will excite us again — this is called the hedonic treadmill. It’s why your favorite songs, TV shows and restaurants can start to feel dull after a while.......hedonic adaptation serves an evolutionary purpose.....“If our emotional reactions didn’t weaken with time, we couldn’t recognize novel changes that may signal rewards or threats,” we’d overlook cues needed to make important, daily decisions about our safety, relationships and careers.....understanding the connection between hedonic adaptation and boredom can help us maneuver around this “stuck” feeling. Psychologists have found that adaptation is more common when interactions with situations, people and events remain unchanged......

(1) Eat lunch with chopsticks (metaphorically speaking, that is):
eating food in unconventional ways can make eating and drinking feel more novel....The takeaway: Approaching tasks in imaginative ways could prevent boredom from sabotaging your (metaphorical) lunch hour.
(2) Work somewhere fresh:
Spending too much time in the same environment, as we all can, can cause a boredom buildup. If you work from home, mix things up by working in a new place, like a coffee shop or a library; if you work from an office, try changing up the layout of your desk or work area.......Changes don’t need to be large to have an impact. Simply accessorizing your desk with fresh flowers or approaching a work project in a novel way can make a difference....
(3) Entertain at home:
Not only is boredom a buzzkill, but it can be toxic to our partnerships. “Boredom is a common relationship issue that can lead to maladaptive coping skills,” .......While apathy can cause marital discontent, it can be tricky to recognize because relationships that are O.K. aren’t necessarily engaging, “Mixing up our social worlds can strengthen friendships and romantic partnerships because evolving relationships keep things interesting.” Try going out on a limb by doing something creative, like organizing a group cooking party, a themed dinner or an old-fashioned tea party.
(4) Pose a question:
Instead of asking well-worn questions like, “How was your day?” or “Did you have a good weekend?” get curious about a co-worker, friend or partner by asking something personal. Two standbys to try: “What are you looking forward to today?” or “Is there anything I can help you with this week?” If you really want to grab someone’s attention, try something quirkier like, “What’s one song that describes your mood today?” Interpersonal curiosity reminds those in our social circles that we’re interested in who they are. Not only that, but discovering new information about friends and co-workers can revitalize conversations and bolster intimacy.
(5) Mix up your commute:
Monotonous tasks like commuting to and from work can end one’s day on a stale note.If you drive, take a different route home or listen to a new podcast. If you walk or use public transportation, greet a stranger or put away your Smartphone and do some old-fashioned people watching.

Whatever you do to quell boredom, keep things interesting by altering your behavior often. Variety can not only interrupt hedonic adaptation; it might just be the spice of happiness.
adaptability  boredom  commuting  co-workers  creative_renewal  curiosity  habits  happiness  howto  psychologists  questions  relationships  routines  signals  variety 
april 2019 by jerryking
How do hedge funds learn new industries quickly? - Quora
Quickly' is very subjective and remember funds(hedge,mutual,pension,etc) do not need to know everything about a industry only to understand the drivers of what moves the stock. That is a massive difference between how a student approaches learning and a analyst, analysts aren't trying to know everything only what can make them money.

Exceptional People
They are used to covering certain sectors some may come from the sell side and covered maybe 15-30 stocks or the buy side and covered 40-60 stocks. Regardless of where they came from they are used to tracking and getting alot of information very efficiently. They are also willing to put in long hours and read/study anything that is needed. After a while(if they don't burn out) they become masters are managing huge information bandwidth.

Tools/Data
For accounting and raw data there are plenty of tools. Bloomberg is quite widely used and with a few commands/clicks you can have a excel sheet with all the data you can want about a companies financials.

Sell side
If you have a large enough fund and relationships on the sell side then they'll do all they can to get you up to speed very quickly. The sell side will have a team of analysts covering a industry/sector your intrested in and if your a good client then they'll spend time and teach you want you want to know.

Reduce noise/Very focused:
Great analysts are masters are reducing the amount of noise that comes there way. They filter emails and calls like crazy so there are less distractions. If your ideas don't make them money they will ignore you(regardless of how smart you are). If they are really good they won't even open your emails if you have not proven you add value to them.
hedge_funds  ideas  discernment  filtering  learning_curves  noise  signals  Quora  new_industries  sell_side 
november 2018 by jerryking
Getting smarter, knowing less
March 16, 2018 | FT | by Robert Armstrong.

The point is that for me, and perhaps most people, the main barrier to being smart is not what we do not know. It is the masses of things we know and mistakenly believe to be relevant.

My wife and I have been thinking about the next stage of our kids’ education. Being central-casting middle-class professional types, we hired an educational consultant to talk us through a range of state schools. She provided briefings about each school, crammed with facts about test scores, teacher turnover, class sizes, and so on.

Feeling slightly dizzy, I asked which bits I should pay attention to. She responded — with glorious honesty for someone being paid by the hour — that there was only one piece of information that really mattered: how many students are late or absent on a regular basis. If a school is the kind of place where almost everybody shows up and shows up on time, then it is the kind of place where kids and teachers can achieve a lot together. The rest is noise.

That comment made me smarter, not because it was a surprising revelation but because it allowed me to clear a lot of junk out of my head — and avoid putting a lot more junk into it. What we all need is the cognitive equivalent of decluttering guru Marie Kondo, who can help us to go into our own heads and throw out all the beliefs that have outlived their usefulness.
decluttering  problem_framing  signals  noise  information_overload  questions  smart_people  incisiveness  education  schools  pretense_of_knowledge  pay_attention  what_really_matters  work_smarter 
march 2018 by jerryking
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
With 125 Ph.D.s in 15 Countries, a Quant ‘Alpha Factory’ Hunts for Investing Edge - WSJ
By BRADLEY HOPE
Updated April 6, 2017

The firm is part of the forefront of a new quantitative renaissance in investing, where the ability to make sense of billions of bits of data in real time is more sought after than old-school financial analysis.

“Brilliance is very equally distributed across the world, but opportunity is not,” said Mr. Tulchinsky, a 50-year-old Belarusian. “We provide the opportunity.”

To do this, WorldQuant developed a model where it employs hundreds of scientists, including 125 Ph.D.s, around the world and hundreds more part-time workers to scour the noise of the economy and markets for hidden patterns. This is the heart of the firm. Mr. Tulchinsky calls it the “Alpha Factory.”....Quantitative hedge funds have been around for decades but they are becoming dominant players in the markets for their ability to parse massive data sets and trade rapidly. Amid huge outflows, traditional hedge funds are bringing aboard chief data scientists and trying to mimic quant techniques to keep up, fund executives say.

Some critics of quants believe their strategies are overhyped and are highly susceptible to finding false patterns in the noise of data. David Leinweber, a data scientist, famously found that the data set with the highest correlation with the S&P 500 over a 10-year period in the 1990s was butter production in Bangladesh.
quantitative  Wall_Street  PhDs  alpha  investors  slight_edge  massive_data_sets  signals  noise  data_scientists  real-time  algorithms  patterns  sense-making  quants  unevenly_distributed  WorldQuant 
april 2017 by jerryking
To Be a Great Investor, Worry More About Being Wrong Than Right - MoneyBeat - WSJ
By JASON ZWEIG
Dec 30, 2016

The stunning surprises of 2016 should have taught all of us that the unexpected will happen. To be a good investor, you have to be right much of the time. To be a great investor, you have to recognize how often you may be wrong. Great investors like Warren Buffett practice trying to disprove their investing assumptions to determine whether they are correct.

Techniques to combat these cognitive biases:

Shun peer pressure from social media or the Internet. If you reveal your opinion to a group that has strong views, the sociologist Robert K. Merton has warned, the ensuing debate becomes more “a battle for status” than “a search for truth.” Instead, get a second opinion from one or two people you know and can trust to tell you if they think you are wrong.

Listen for signals you might be off-base. Use Facebook or Twitter not as an amen corner of people who agree with you, but to find alternative viewpoints that could alert you when your strategies are going astray.

Write down your estimates of where the Dow Jones Industrial Average, oil, gold, inflation, interest rates and other key financial indicators will be at the end of 2017. If you don’t know, admit it. Ask your financial advisers to do the same. Next Dec. 31, none of you will be able to say “I knew that would happen” unless that’s what the record shows.

Book reference: Keith Stanovich, Richard West and Maggie Toplak point out in their new book, “The Rationality Quotient,” rational beliefs “must correspond to the way the world is,” not to the way you think the world ought to be.
==================================
Commenter:

What investors need to do is focus on their own investments, their strategies for each particular holding, long-term, income-oriented, speculative, etc. and stick to their plan without being distracted by peers and press looking for big headlines.
Warren_Buffett  biases  confirmation_bias  investors  books  Pablo_Picasso  personal_finance  investing  Jason_Zweig  pretense_of_knowledge  self-awareness  self-analysis  self-reflective  proclivities  warning_signs  signals  second_opinions  peer_pressure  DJIA  assumptions  mistakes  personal_economy  surprises  worrying 
january 2017 by jerryking
Winton Capital’s David Harding on making millions through maths
NOVEMBER 25, 2016 | Financial Times | by Clive Cookson.

Harding’s career is founded on the relentless pursuit of mathematical and scientific methods to predict movements in markets. This is a never-ending process because predictive tools lose their power as markets change; new ones are always needed. “We have 450 people in the company, of whom 250 are involved in research, data collection or technology,” he says. That is equivalent to a medium-sized university physics department....Harding's approach to making money is to exploit failures in the efficient market theory...the problem with the EMT is that “It treats economics like a physical science when, in fact, it is a human or social science. Humans are prone to unpredictable behaviour, to overreaction or slumbering inaction, to mania and panic.”...The Winton investment system is based instead on “the belief that scientific methods provide a good means of extracting meaning from noisy market data. We don’t make assumptions about how markets should work, rather we use advanced statistical techniques to seek patterns in huge data sets and base all our investment strategies on the analysis of empirical evidence...Harding emphasises the breadth and volume of investments involved, covering bonds, currencies, commodities, market indices and individual equities. The aim is to exploit a large number of weak predictive signals, he says: “We don’t expect to find any strong relationships between data and the price of the market. That may sound counter-intuitive but if there are strong relationships, someone else is going to be exploiting those. Weak relationships are where we have a competitive advantage.” Weather strategies are one feature of Winton research, including analysis of cloud cover and soil moisture levels to predict the prices of agricultural commodities. Other important indicators, for which maths can uncover value not fully reflected in market prices, include seasonal factors and inventory levels across supply chains....When I ask Harding about the use of machine learning and artificial intelligence to guide investment decisions, he bristles slightly. “There is a sudden upsurge of excitement about AI,” he says, “but we have used techniques that would be described as machine learning for at least 30 years.”

Essentially, he says, quantitative investing, self-driving cars and speech recognition are all applications of “information engineering”....he heads off to a lecture by German psychologist Gerd Gigerenzer, who runs the Harding Centre for Risk Literacy in Berlin
communicating_risks  mathematics  hedge_funds  investment_research  financiers  Winton_Capital  physics  Renaissance_Technologies  James_Simons  moguls  quantitative  panics  overreaction  massive_data_sets  philanthropy  machine_learning  signals  human_factor  weak_links  JumpMath 
november 2016 by jerryking
Donald Trump Voters, Just Hear Me Out
NOV. 2, 2016 | The New York Times | Thomas L. Friedman.

No one knows for certain how we deal with this new race with and against machines, but I can assure you it’s not Trump’s way — build walls, restrict trade, give huge tax cuts to the rich. The best jobs in the future are going to be what I call “STEMpathy jobs — jobs that blend STEM skills (science, technology, engineering, math) with human empathy. We don’t know what many of them will look like yet.

The smartest thing we can do now is to keep our economy as open and flexible as possible — to get the change signals first and be able to quickly adapt; create the opportunity for every American to engage in lifelong learning, because whatever jobs emerge will require more knowledge; make sure that learning stresses as much of the humanities and human interactive skills as hard sciences; make sure we have an immigration policy that continues to attract the world’s most imaginative risk-takers; and strengthen our safety nets, because this era will leave more people behind.

This is the only true path to American greatness in the 21st century.
open_borders  Donald_Trump  Campaign_2016  Tom_Friedman  STEM  manufacturers  Hillary_Clinton  adaptability  empathy  life_long_learning  humanities  safety_nets  signals  warning_signs 
november 2016 by jerryking
A field guide to lies : critical thinking in the information age : Levitin, Daniel J., author. : Book, Regular Print Book : Toronto Public Library
Year/Format: 2016, Book , 304 pages

It's becoming harder to separate the wheat from the digital chaff. How do we distinguish misinformation, pseudo-facts, distortions and outright lies from reliable information? In A Field Guide to Lies, neuroscientist Daniel Levitin outlines the many pitfalls of the information age and provides the means to spot and avoid them. Levitin groups his field guide into two categories--statistical infomation and faulty arguments--ultimately showing how science is the bedrock of critical thinking. It is easy to lie with stats and graphs as few people "take the time to look under the hood and see how they work." And, just because there's a number on something, doesn't mean that the number was arrived at properly. Logic can help to evaluate whether or not a chain of reasoning is valid. And "infoliteracy" teaches us that not all sources of information are equal, and that biases can distort data. Faced with a world too eager to flood us with information, the best response is to be prepared. A Field Guide to Lies helps us avoid learning a lot of things that aren't true.
books  nonfiction  critical_thinking  infoliteracy  biases  lying  information_overload  TPL  Daniel_Levitin  engaged_citizenry  signals  noise  information_sources 
september 2016 by jerryking
Jeffrey Simpson: Slow growth now, no growth later - The Globe and Mail
JEFFREY SIMPSON
Slow growth now, no growth later
SUBSCRIBERS ONLY
The Globe and Mail
Published Wednesday, Jan. 13,2016

The population is aging. Commodity prices are low. Oil and natural gas prices are hitting rock-bottom. The Canadian dollar has plummeted. Most governments are in deficit, or heading into deficit (read Ottawa). Innovation and the commercialization of research lag that of other countries. Productivity, the country’s long-term bugbear, remains sluggish....all the green traffic signals have turned to yellow or red. Yet this slow-growth economy, which might persist for a long time, is wrapped in a political culture that seems to favour slow or no growth, or seems to think that government infrastructure programs, useful in themselves, will solve the long-run problems.....Everywhere, projects are blocked or delayed, because environmentalists, aboriginal people, non-governmental organizations or even provincial governments oppose them....Many of these blocked or delayed projects with large-scale economic spinoffs are natural resource projects, which the federal government says might be saved with more “robust” oversight. The government is kidding itself in this belief, since the opponents don’t care what the regulatory process is. They oppose development pure, simple and always.

Far beyond natural resource constipation, the contradiction arises between slow growth and the huge desire of citizens for more government services, without higher taxes. Of special concern is Canada’s persistent low productivity, to which no easy answer exists, except that a slow-growth mentality doesn’t help.

...Don Drummond, working with Evan Capeluck, recently explained the challenge in a paper for the Centre for the Study of Living Standards, which looked at productivity trends in all provinces. Projecting these trends forward, they said most provinces and territories will not be able to balance revenue growth with new spending demands (especially for health care) without higher taxes or spending cuts.

Put another way, unless long-term growth can be improved – a trend that will require productivity improvements – Canada is heading for a poorer future with fewer programs and/or higher taxes.
growth  Jeffrey_Simpson  economic_downturn  anti-development  natural_resources  economic_stagnation  megaprojects  productivity  Don_Drummond  slow_growth  low_growth  weak_dollar  signals 
january 2016 by jerryking
Successful people act quickly when things go wrong - The Globe and Mail
HARVEY SCHACHTER
Special to The Globe and Mail
Published Sunday, Aug. 02, 2015

Productivity

Pivot quickly to maximize success
Airplanes are off course 90 per cent of the time but incessantly correct their direction, . Similarly, successful people correct their course quickly when off-kilter. They also set short timelines, have small daily to-do lists and drop stuff that isn’t working. Lifehack.org

Branding

Learn from but don’t live in the past
It’s great to know your company history but senseless to live in the past,Your company’s history is valuable only if customers and prospective clients believe it defines your brand and success, and differentiates you from competitors. If it doesn’t, build a new history.

Leadership

Pre-empt attacks with regular audits
To pre-empt an activist investor’s attack, eliminate financial and operational underperformance. Conduct regular vulnerability audits, looking at factors such as how earnings per share, profit and price-to-earnings ratios in the past 18 months compare with peers. If necessary, create an aggressive turnaround plan. ChiefExecutive.net

Human resources

Ask potential hires where they’ll go next
It sounds weird, but LinkedIn asks potential employees what job they want to have next after they leave the company. Founder Reid Hoffman says it signals the intent to have a huge impact on the individual’s career, helping to develop them for whatever they choose, and invites honesty. Vox.com

Tech tip

Use phone’s camera as portable copier
Productivity blogger Mark Shead recommends using your phone’s camera as a portable copy machine/scanner when on the road, photographing paperwork, train schedules or other information. Many new camera phones have the resolution to provide readable copies. Productivity 501.com
branding  productivity  human_resources  leadership  Harvey_Schachter  character_traits  habits  pre-emption  course_correction  Reid_Hoffman  career_paths  beforemath  overachievers  affirmations  pivots  audits  signals  vulnerabilities  hiring  interviews  high-achieving 
august 2015 by jerryking
The Mind of Marc Andreessen - The New Yorker
MAY 18, 2015 | New Yorker | BY TAD FRIEND.

Doug Leone, one of the leaders of Sequoia Capital, by consensus Silicon Valley’s top firm, said, “The biggest outcomes come when you break your previous mental model. The black-swan events of the past forty years—the PC, the router, the Internet, the iPhone—nobody had theses around those. So what’s useful to us is having Dumbo ears.”* A great V.C. keeps his ears pricked for a disturbing story with the elements of a fairy tale. This tale begins in another age (which happens to be the future), and features a lowborn hero who knows a secret from his hardscrabble experience. The hero encounters royalty (the V.C.s) who test him, and he harnesses magic (technology) to prevail. The tale ends in heaping treasure chests for all, borne home on the unicorn’s back....Marc Andreessen is tomorrow’s advance man, routinely laying out “what will happen in the next ten, twenty, thirty years,” as if he were glancing at his Google calendar. He views his acuity as a matter of careful observation and extrapolation, and often invokes William Gibson’s observation “The future is already here—it’s just not very evenly distributed.”....Andreessen applies a maxim from his friend and intellectual sparring partner Peter Thiel, who co-founded PayPal and was an early investor in LinkedIn and Yelp. When a reputable venture firm leads two consecutive rounds of investment in a company, Andreessen told me, Thiel believes that that is “a screaming buy signal, and the bigger the markup on the last round the more undervalued the company is.” Thiel’s point, which takes a moment to digest, is that, when a company grows extremely rapidly, even its bullish V.C.s, having recently set a relatively low value on the previous round, will be slightly stuck in the past. The faster the growth, the farther behind they’ll be....When a16z began, it didn’t have even an ersatz track record to promote. So Andreessen and Horowitz consulted on tactics with their friend Michael Ovitz, who co-founded the Hollywood talent agency Creative Artists Agency, in 1974. Ovitz told me that he’d advised them to distinguish themselves by treating the entrepreneur as a client: “Take the long view of your platform, rather than a transactional one. Call everyone a partner, offer services the others don’t, and help people who aren’t your clients. Disrupt to differentiate by becoming a dream-execution machine.”
Marc_Andreessen  Andreessen_Horowitz  Silicon_Valley  transactional_relationships  venture_capital  vc  Peter_Thiel  long-term  far-sightedness  Sequoia  mindsets  observations  partnerships  listening  insights  Doug_Leone  talent_representation  CAA  mental_models  warning_signs  signals  beforemath  unevenly_distributed  low_value  extrapolations  acuity  professional_service_firms  Michael_Ovitz  execution  William_Gibson 
may 2015 by jerryking
Banking Start-Ups Adopt New Tools for Lending
JAN. 18, 2015 | - NYTimes.com | By STEVE LOHR.

When bankers of the future decide whether to make a loan, they may look to see if potential customers use only capital letters when filling out forms, or at the amount of time they spend online reading terms and conditions — and not so much at credit history.

These signals about behavior — picked up by sophisticated software that can scan thousands of pieces of data about online and offline lives — are the focus of a handful of start-ups that are creating new models of lending....Earnest uses the new tools to make personal loans. Affirm, another start-up, offers alternatives to credit cards for online purchases. And another, ZestFinance, has focused on the relative niche market of payday loans.
Steve_Lohr  tools  banking  banks  massive_data_sets  start_ups  data_scientists  Earnest  Affirm  ZestFinance  Max_Levchin  consumer_finance  credit_scoring  fin-tech  financial_services  consumer_behavior  signals 
january 2015 by jerryking
Nokia a lesson for backers of Canada’s nanny state - The Globe and Mail
Oct. 17 2014 | The Globe and Mail | BRIAN LEE CROWLEY.

How did it all go so wrong? And what might Canada learn from Finland’s downfall?

One obvious conclusion is not to put all your eggs in one basket, but it goes well beyond that. There was a time when economic change worked slowly enough that you could get a generation or two’s employment out of an industry before it was overtaken by innovation. Detroit dominated automobile manufacturing for many decades before its own complacency and the innovativeness of European and Asian producers came into play. In a similar vein, Nokia allowed itself to believe in its own infallibility, and Finland meekly followed suit. But the forces of change are now so powerful and lightning fast that sometimes a single product release from a competitor can signal the death knell of a previously healthy company or industry....Canada is rife with industries with their heads stuck in the sand, almost invariably because they believe they can shelter behind a friendly bureaucrat with a rulebook.

Examples abound in fields as diverse as telecoms, dairy, airlines, broadcasting, taxis and transport. Could there have been a bigger farce than the CRTC’s attempt to manhandle online content provider Netflix?...The real lesson of Nokia’s demise was that there is no substitute for being driven by what customers want, which is quality products and service at the lowest possible price...Every deviation from this relentless focus on what customers actually want makes your market a tasty morsel for the disrupters.
concentration_risk  Nokia  Finland  mobile_phones  disruption  Netflix  Uber  CRTC  complacency  accelerated_lifecycles  protectionism  nanny_state  customer_focus  change_agents  Finnish  demand-driven  lessons_learned  automotive_industry  downfall  change  warning_signs  signals  customer-driven  infallibility  overconfidence  hubris  staying_hungry 
october 2014 by jerryking
The Risks of Cheap Water - NYTimes.com
OCTOBER 14, 2014 | NYT | Eduardo Porter.

the proliferation of limits on water use will not solve the problem because regulations do nothing to address the main driver of the nation’s wanton consumption of water: its price.

“Most water problems are readily addressed with innovation,” said David G. Victor of the University of California, San Diego. “Getting the water price right to signal scarcity is crucially important.”... markets and prices are an indispensable part of the tool kit to combat scarcity....The signals today are way off. Water is far too cheap across most American cities and towns. ...Adding to the challenges are the obstacles placed in the way of water trading.
California  droughts  water  scarcity  pricing  signals 
october 2014 by jerryking
A 25-Question Twitter Quiz to Predict Retweets - NYTimes.com
JULY 1, 2014 | NYT | Sendhil Mullainathan.

how “smart” algorithms are created from big data: Large data sets with known correct answers serve as a training bed and then new data serves as a test bed — not too differently from how we might learn what our co-workers find funny....one of the miracles of big data: Algorithms find information in unexpected places, uncovering “signal” in places we thought contained only “noise.”... the Achilles’ heel of prediction algorithms--being good at prediction often does not mean being better at creation. (1) One barrier is the oldest of statistical problems: Correlation is not causation.(2) an inherent paradox lies in predicting what is interesting. Rarity and novelty often contribute to interestingness — or at the least to drawing attention. But once an algorithm finds those things that draw attention and starts exploiting them, their value erodes. (3) Finally, and perhaps most perversely, some of the most predictive variables are circular....The new big-data tools, amazing as they are, are not magic. Like every great invention before them — whether antibiotics, electricity or even the computer itself — they have boundaries in which they excel and beyond which they can do little.
predictive_analytics  massive_data_sets  limitations  algorithms  Twitter  analytics  data  data_driven  Albert_Gore  Achilles’_heel  boundary_conditions  noise  signals  paradoxes  correlations  causality  counterintuitive  training_beds  test_beds  rarity  novelty  interestingness  hard_to_find 
july 2014 by jerryking
M.I.T.'s Alex Pentland: Measuring Idea Flows to Accelerate Innovation - NYTimes.com - NYTimes.com
April 15, 2014 | NYT | By STEVE LOHR.

Alex Pentland --“Social Physics: How Good Ideas Spread — The Lesson From a New Science.”

Mr. Pentland has been identified with concepts — and terms he has coined — related to the collection and interpretation of all that data, like “honest signals” and “reality mining.” His descriptive phrases are intended to make his point that not all data in the big data world is equal....Reality mining, for example, examines the data about what people are actually doing rather than what they are looking for or saying. Tracking a person’s movements during the day via smartphone GPS signals and credit-card transactions, he argues, are far more significant than a person’s web-browsing habits or social media comments....Central to the concept of social physics is the ability to measure communication and transactions as never before. Then, that knowledge about the flow of ideas can be used to accelerate the pace of innovation.

The best decision-making environment, Mr. Pentland says, is one with high levels of both “engagement” and “exploration.” Engagement is a measure of how often people in a group communicate with each other, sharing social knowledge. Exploration is a measure of seeking out new ideas and new people.

A golden mean is the ideal....[traders] with a balance of diversity of ideas in their trading network — engagement and exploration — had returns that were 30 percent ahead of isolated traders and well ahead of the echo chamber traders, too....The new data and measurement tools, he writes, allow for a “God’s eye view” of human activity. And with that knowledge, he adds, comes the potential to engineer better decisions in a “data-driven society.”
Alex_Pentland  books  cross-pollination  curiosity  data_scientists  data_driven  decision_making  massive_data_sets  MIT  Mydata  sensors  social_physics  Steve_Lohr  idea_generation  heterogeneity  ideas  intellectual_diversity  traders  social_data  signals  echo_chambers 
april 2014 by jerryking
Busy and Busier
Oct 24 2012 | The Atlantic | James Fallows.

a lot of people are feeling overwhelmed is because people are not in true survival or crisis mode as often as they have been in much of our history. The interesting thing about crisis is that it actually produces a type of serenity. Why? Because in a crisis, people have to integrate all kinds of information that’s potentially relevant, they have to make decisions quickly, they have to then trust their intuitive judgment calls in the moment. They have to act. They’re constantly course-correcting based on data that’s coming up, and they’re very focused on some outcome, usually live—you know, survive. Don’t burn up. Don’t die.

But as soon as you’re not in a crisis, all the rest of the world floods into your psyche. Now you’re worried about taxes and tires and “I’m getting a cold” and “My printer just crapped out.” Now that flood is coming across in electronic form, and it is 24/7.....The thing about nature is, it’s information rich, but the meaningful things in nature are relatively few—berries, bears and snakes, thunderstorms, maybe poison oak. There are only a few things in nature that force me to change behavior or make a decision. The problem with e-mail is that it’s not just information; it’s the need for potential action. It’s the berries and snakes and bears, but they’re embedded, and you don’t know what’s in each one....Things on your mind need to be externalized—captured in some system that you trust. You capture things that are potentially meaningful; you clarify what those things mean to you; and you need maps of all that, so you can see it from a larger perspective. With better technology, I’d like a set of maps—maps of my maps. Then I could say, “Okay, which map do I want to work on right now? Do I want to work on my family map, because I’ve got family members coming over for dinner?” Then you can drill down into “Oh, my niece is coming. She likes this food, her favorite color is pink, her dog is named …” Then you can back off and say, “That’s enough of that map. What’s the next map I want to see?” Or: “I’d just like to read some poetry right now.”
busy_work  course_correction  crisis  David_Allen  GTD  human_psyche  information_overload  James_Fallows  living_in_the_moment  mapping  metacognition  metadata  metaphysical  monotasking  productivity  nature  noise  overwhelmed  sense-making  signals  stress_response 
november 2013 by jerryking
More Data Can Mean Less Guessing About the Economy - NYTimes.com
By STEVE LOHR
Published: September 7, 2013

measurement shortfall in the small-business sector, and a series of other information gaps in the economy, may be overcome by what experts say is an emerging data revolution — Big Data, in the current catchphrase. The ever-expanding universe of digital signals of behavior, from browsing and buying on the Web to cellphone location data, is grist for potential breakthroughs in economic measurement. It could produce more accurate forecasting and more informed policy-making — more science and less guesswork.... THE economics profession is gearing up to exploit new sources of digital data. In a recent paper, “The Data Revolution and Economic Analysis,” two Stanford economists, Liran Einav and Jonathan Levin, concluded that “there is little doubt, at least in our minds, that over the next decades ‘big data’ will change the landscape of economic policy and economic research.”

At Intuit, the small-business data portray a sector that was “hurt much more than big business by the recession and its recovery has been far worse,” says Ms. Woodward, the economic consultant. Over the last three and a half years, payroll employment for all companies has increased 6.9 percent, while small-business employment has risen far less, just 1.9 percent. Hiring among the small companies, though still sluggish, has inched ahead in the last three months.
data  Steve_Lohr  massive_data_sets  Intuit  information_sources  small_business  measurements  Freshbooks  economy  Erik_Brynjolfsson  economics  indicators  real-time  forecasting  economic_data  information_gaps  signals  economists  data_driven 
september 2013 by jerryking
Big Data should inspire humility, not hype
Mar. 04 2013| The Globe and Mail |Konrad Yakabuski.

" mathematical models have their limits.

The Great Recession should have made that clear. The forecasters and risk managers who relied on supposedly foolproof algorithms all failed to see the crash coming. The historical economic data they fed into their computers did not go back far enough. Their models were not built to account for rare events. Yet, policy makers bought their rosy forecasts hook, line and sinker.

You might think that Nate Silver, the whiz-kid statistician who correctly predicted the winner of the 2012 U.S. presidential election in all 50 states, would be Big Data’s biggest apologist. Instead, he warns against putting our faith in the predictive power of machines.

“Our predictions may be more prone to failure in the era of Big Data,” The New York Times blogger writes in his recent book, The Signal and the Noise. “As there is an exponential increase in the amount of available information, there is likewise an exponential increase in the number of hypotheses to investigate … [But] most of the data is just noise, as most of the universe is filled with empty space.”

Perhaps the biggest risk we run in the era of Big Data is confusing correlation with causation – or rather, being duped by so-called “data scientists” who tell us one thing leads to another. The old admonition about “lies, damn lies and statistics” is more appropriate than ever."
massive_data_sets  data_driven  McKinsey  skepticism  contrarians  data_scientists  Konrad_Yakabuski  modelling  Nate_Silver  humility  risks  books  correlations  causality  algorithms  infoliteracy  noise  signals  hype 
march 2013 by jerryking
Surprise business result? Explore whether it is a hidden opportunity
June 18, 2007 | G&M pg. B8 | George Stalk Jr.

What does it take to capitalize on anomalies systematically?

For starters, you need to have metrics and information systems that are sufficiently refined to identify anomalies in the first place. Knowing the average margins and market share isn’t enough; look at the entire range of outcomes—across customers, geographies, products, and the like. This allows you to surface out-of-the-ordinary results for closer inspection.

The next step is to separate wheat from chaff: those anomalies that signal a potential business opportunity from those that are merely one-time events. The key is to examine the pattern of unusual performance over time. The customer who consistently buys high volumes or the market that outperforms the average year after year are, by definition, not random. Is there an underlying cause that can be identified and then replicated elsewhere?

Finally, you need to understand the precise mechanisms that animate the anomalies you identify. Why is the unusual pattern of performance happening? What specific features of the product or the local environment or the customer experience are bringing it about? Don’t accept the usual first-order explanations. It’s not enough to know that a particular customer has been loyal for years; find out precisely why.

It’s up to senior management to create the forum for asking why and to persist until the question is answered with genuine insight.
metrics  George_Stalk_Jr.  BCG  anomalies  growth  opportunities  customer_insights  surprises  systematic_approaches  quizzes  ratios  pattern_recognition  insights  questions  first-order  second-order  OPMA  Waudware  curiosity  new_businesses  one-time_events  signals  noise  overlooked_opportunities  latent  hidden  averages  information_systems  assessments_&_evaluations  randomness  5_W’s 
january 2013 by jerryking
Why Listening Is So Much More Than Hearing - NYTimes.com
By SETH S. HOROWITZ
Published: November 9, 2012

The difference between the sense of hearing and the skill of listening is attention.

Hearing is a vastly underrated sense.... hearing is a quantitatively fast sense. While it might take you a full second to notice something out of the corner of your eye, turn your head toward it, recognize it and respond to it, the same reaction to a new or sudden sound happens at least 10 times as fast.

This is because hearing has evolved as our alarm system — it operates out of line of sight and works even while you are asleep. And because there is no place in the universe that is totally silent, your auditory system has evolved a complex and automatic “volume control,” fine-tuned by development and experience, to keep most sounds off your cognitive radar unless they might be of use as a signal that something dangerous or wonderful is somewhere within the kilometer or so that your ears can detect.

This is where attention kicks in.

Attention is not some monolithic brain process. There are different types of attention, and they use different parts of the brain. The sudden loud noise that makes you jump activates the simplest type: the startle. A chain of five neurons from your ears to your spine takes that noise and converts it into a defensive response in a mere tenth of a second — elevating your heart rate, hunching your shoulders and making you cast around to see if whatever you heard is going to pounce and eat you. This simplest form of attention requires almost no brains at all and has been observed in every studied vertebrate.

More complex attention kicks in when you hear your name called from across a room or hear an unexpected birdcall from inside a subway station. This stimulus-directed attention is controlled by pathways through the temporoparietal and inferior frontal cortex regions, mostly in the right hemisphere — areas that process the raw, sensory input, but don’t concern themselves with what you should make of that sound. (Neuroscientists call this a “bottom-up” response.)

But when you actually pay attention to something you’re listening to, whether it is your favorite song or the cat meowing at dinnertime, a separate “top-down” pathway comes into play. Here, the signals are conveyed through a dorsal pathway in your cortex, part of the brain that does more computation, which lets you actively focus on what you’re hearing and tune out sights and sounds that aren’t as immediately important.

In this case, your brain works like a set of noise-suppressing headphones, with the bottom-up pathways acting as a switch to interrupt if something more urgent — say, an airplane engine dropping through your bathroom ceiling — grabs your attention.

Hearing, in short, is easy. You and every other vertebrate that hasn’t suffered some genetic, developmental or environmental accident have been doing it for hundreds of millions of years. It’s your life line, your alarm system, your way to escape danger and pass on your genes. But listening, really listening, is hard when potential distractions are leaping into your ears every fifty-thousandth of a second — and pathways in your brain are just waiting to interrupt your focus to warn you of any potential dangers.

Listening is a skill that we’re in danger of losing in a world of digital distraction and information overload.

And yet we dare not lose it. Because listening tunes our brain to the patterns of our environment faster than any other sense, and paying attention to the nonvisual parts of our world feeds into everything from our intellectual sharpness to our dance skills.

Luckily, we can train our listening just as with any other skill.
10x  listening  attention  hearing  senses  information_overload  distractions  perception  empathy  signals  physiological_response  bottom-up  top-down  pay_attention 
november 2012 by jerryking
How to Tell When A CEO Is Toast: The Early Warnings - WSJ.com
April 18, 2000 | WSJ |By CAROL HYMOWITZ

Here's a short list of telltale warning signals indicating trouble at the top.

TURNING A DEAF EAR to directors: When the CEO of a technology company that had grown considerably during his tenure suddenly faced enormous competition from a faster-growing rival and difficulty absorbing two acquisitions, he ignored a number of suggestions from his board. "We told him to try this, do that, consider this -- and he simply wouldn't listen," fumes a director who did not want to be named. The more the CEO insisted on business as usual and refused to listen to his directors' concerns, the more he lost their trust. "His failure to listen became a warning signal to us" and led to his ouster, the director says.
[Illustration of a CEO with a rocket strapped to the back of his chair]

Similarly, former Coca-Cola KO +0.36% CEO Douglas Ivesterdidn't heed his board's urgings to name a No. 2 executive. And when Coke customers in Belgium and France complained of nausea after drinking Coke products, Mr. Ivester ignored at least one director's advice to go quickly to Belgium and address the situation.

Turning a deaf ear to employees: Mr. Ivester also decided, as part of a management reorganization, that the company's highest-ranking African American, Carl Ware, one of his longtime supporters, would no longer report directly to him -- effectively demoting him. The timing couldn't have been worse since Coke is facing an employee lawsuit alleging discrimination. Mr. Ware announced plans for early retirement, and Mr. Ivester lost more credibility as Coke's leader. He stepped down as CEO at the end of last year. Mr. Ivester couldn't be reached for comment.

Former Delta Air Lines DAL -1.69% CEO Ronald Allenalso was a victim of his own insensitive management style three years ago. Mr. Allen had pulled Delta out of a financial tailspin by slashing costs. But a lot of those cuts represented employee layoffs and he did little to smooth over anxieties. Directors ultimately blamed him for a drop in morale throughout the company. With many executives who reported to Mr. Allen leaving and blue-collar workers considering unionization, Mr. Allen was asked to step down. He declined to comment about the ordeal.

PROMISING TOO MUCH: At toymaker Mattel , MAT +0.59% former CEO Jill Barad madeearnings forecasts to her board and shareholders that the company then failed to meet. "Nobody likes surprises," says Thomas Neff, chairman of the executive recruiter Spencer Stuart's U.S. operations. "The best CEOs beat their forecasts, while the worst thing you can do is be overly optimistic," he adds.

Ms. Barad at times dismissed forecasts made by other executives, insisting to directors that Mattel would do better. She resigned in February, after three years as CEO and a stream of disappointing earnings. She was unavailable for comment.

Misreading expectations: A former CEO ousted from his job with a large financial-services company a few years ago recalls how he thought he was in agreement with his board on a succession plan, only to realize they wanted him gone much sooner, mostly out of fear that he was intentionally dragging his feet. The CEO had formed a search committee for a successor, but was taking his time about recommending candidates. Then, at a board meeting, he was asked to leave the room so directors could confer alone. What he thought would be a 15-minute exchange turned into an hour-long discussion. "That's when I knew something was up," he says. "They wanted to move on succession right away."

Underestimating conflict: Bank One 's ONE +2.80% former CEO John McCoyoversaw numerous acquisitions before he merged his Columbus, Ohio, bank with First Chicago to create a $260 billion powerhouse Midwestern bank. Previous smaller mergers, he says, took about 18 mon
aloofness  blue-collar  Carol_Hymowitz  CEOs  expectations  misinterpretations  misjudgement  overoptimism  overpromising  signals  surprises  tailspins  underestimation  unionization  warning_signs 
june 2012 by jerryking
The Rhino Principle
01.30.06 | Forbes.com | Paul Johnson
We can choose to lead quiet lives and get through them without achieving much. But if we want to do the big thing, if we hope to leave a record that will be admired and remembered, we must learn to distinguish between the peripheral and the essential. Then, having clearly established our central objective, we must charge at it again and again until the goal is achieved.

That is what the rhinoceros does. It may not be a model animal in most ways. But it does one thing very well. And that one thing we can learn: Charge!
historians  gtd  indispensable  worthiness  signals  noise  discernment  judgment  thinking_big 
june 2012 by jerryking
A First Draft of History? - WSJ.com
March 12, 2005 | WSJ | By BRET STEPHENS

The cliché is that journalism is the first draft of history. Yet a historian searching for clues about the origins of many of the great stories of recent decades--the collapse of the Soviet empire; the rise of Osama bin Laden; the declining American crime rate; the economic eclipse of Japan and Germany--would find most contemporary journalism useless. Perhaps a story here or there might, in retrospect, seem illuminating. But chances are it would have been nearly invisible at the time of publication: eight column inches, page A12.

The problem is not that journalists can't get their facts straight: They can and usually do. Nor is it that the facts are obscure: Often, the most essential facts are also the most obvious ones. The problem is that journalists have a difficult time distinguishing significant facts--facts with consequences--from insignificant ones. That, in turn, comes from not thinking very hard about just which stories are most worth telling....As for the media, it shouldn't be too difficult to do better. Look for the countervailing data. Broaden your list of sources. Beware of exoticizing your subject:
Bret_Stephens  journalism  journalists  critical_thinking  history  signals  noise  frictions  pain_points  worthiness  countervailing  storytelling  seminal_moments  wide-framing  discernment  origin_story  historians  consequential  clichés  worthwhile_problems 
may 2012 by jerryking
The Misguided Attack on Derivatives - WSJ.com
APRIL 26, 2010 | Wall Street Journal | By L. GORDON CROVITZ.
Short-selling warns markets that an asset bubble is about to burst.
Easy money, easy mortgages, and banks too big to fail were key causes of
the credit crisis. It was also Wall Street's greatest information
failure in many years. We need more trading, not less, and more signals
in the market faster that prices need to be adjusted. The last thing we
need is outlawing opportunities for people like Mr. Paulson to bring
vital information to market.
derivatives  L._Gordon_Crovtiz  John_Paulson  information_gaps  signals  information_flows  too_big_to_fail  short_selling  bubbles 
april 2010 by jerryking
Contrary Rules for Business Success
Jun. 24, 2009 | The Globe & Mail | by Harvey Schachter.
Reviews The Moneymakers, by Anne-Marie Fink, Crown Business, 310
pages, $32. Fink gets paid to separate the wheat from the chaff in the
corporate world or, to put it in business terms, separate the
moneymakers from the destroyers of shareholder value. Fink is an equity
analyst with J.P. Morgan Asset Management, she has billions of dollars
resting on her assessment of companies and their management.
equity_research  investment_research  books  rules_of_the_game  book_reviews  Harvey_Schachter  slight_edge  signals  noise  value_creation  value_destruction  shareholder_value  JPMorgan_Chase 
february 2010 by jerryking
How to Be a Billionaire: Worry!
Monday, Feb. 05, 2001| TIME | By JOSHUA COOPER RAMO. For
George Soros, the problem is not how to make money. That's easy, he
believes. You do that by spotting mistakes. The problem is the mistakes
themselves. Soros thinks that our history, especially economic history,
is sculpted by blunders. It's a radical proposition, as if you suggested
that Botticelli's best art was the result of paint splatters. But Soros
is insistent: mistakes make history. They also make--and
destroy--fortunes. Soros, who made a fortune looking for and finding
mistakes, worries we are making one now. He picks up on these errors by
listening to his money. These days he doesn't like what he
hears..."George is signal," says a Fed adviser, referring to the high
noise-signal ratio among advice givers to Alan Greenspan.

===================================================
From Farhad Manjoo
Step 1: Worry. If you're an investor, employee, founder, tech journalist or in some other way connected to the tech business, worrying about the bubble is your best defense against the bubble. Worrying keeps you sharp. Worrying keeps magical thinking (i.e. happy talk) at bay. As in the 1990s, the tech industry is pushing grand, society-transforming novelties on the rest of the world. If you're not worried that some of these claims are crazy, you're not paying attention.
====================================================
George_Soros  Joshua_Cooper_Ramo  financial_history  wishful_thinking  Kissinger_Associates  pattern_recognition  patterns  moguls  lessons_learned  mistakes  Bank_of_England  financiers  negative_space  investors  signals  worrying  paranoia  human_errors  economic_history  happy_talk  pay_attention 
october 2009 by jerryking
The art of bringing order - and healthy returns - out of chaos
Mar 19, 2007 | Financial Times pg. 5 | PETER SMITH.Nothing attracts the interest of private equity more than a distress signal
private_equity  distressed_debt  vulture_investing  signals 
june 2009 by jerryking
Mining for Gold - WSJ.com
Interview with Deutsche Bank Asset Management CIO, Sean Kelly.
Details how the firm sorts through the clutter of information to gain an
edge.

THE WALL STREET JOURNAL: How is information technology strategically important for Deutsche Asset Management?

MR. KELLEY: In finance there is a concept called "alpha," which means that you make returns beyond the market as a whole. It's really what asset managers get paid for. For us technology is a sizable factor for creating alpha.

"There's a lot of information but also a lot of noise. You have to figure out algorithms to crawl through [all] this automatically, taking out 95% of the noise and finding signals that indicate the emotions of the market. That's the thing: The information doesn't have to be correct -- it just has to be dominant. A person doesn't have to be right. It just has to be that everyone thinks that way. So if you can figure out ways to get to that information and act on it before the market has a chance to correct itself, it gives you an added edge."
alpha  Deutsche_Bank  data_mining  slight_edge  information_overload  competingonanalytics  CIOs  sorting  noise  signals  informational_advantages 
january 2009 by jerryking

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