My Thoughts Exactly @stockcats

At some point the madness of the crowds gets boring. @stockcatscat yawn

 

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When capitalism wants to data mine you | FT Alphaville

Interesting point in an FT article today: If Big Data is seen by companies and investors as an asset, one reflected in valuations, regulations on its use, like the one in Europe kicking in next year, could have a big bottom-line impact on company financials and share prices. Alphaville does a read-across from oil – if the government were to regulate it more dramatically, what would happen, etc. Not an entirely airtight argument, but a conversation starter.

via When capitalism wants to data mine you | FT Alphaville

Why So Few Will “Retire” Comfortably

Serial blunders in the structure of retirement vehicles, especially Social Security, explained. A long post on Naked Capitalism, well worth reading – including the comments. From the embedded interview of Michael Hudson:

The Federal Reserve has just published statistics saying the average American family, 55 and 60 years old, only has about $14,000 worth of savings. This isn’t nearly enough to retire on. There’s also been a vast looting of pension funds, largely by Wall Street. That’s why the investment banks have had to pay tens of billions of dollars of penalties for cheating pension funds and other investors. The current risk-free rate of return is 0.1% on government bonds, so the pension funds don’t have enough money to pay pensions at the rate that their junk economics advisors forecast. The money that people thought was going to be available for their retirement, all of a sudden isn’t. The pretense is that nobody could have forecast this!

There are so many corporate pension funds that are going bankrupt that the Pension Benefit Guarantee Corporation doesn’t have enough money to bail them out. The PBGC is in deficit. If you’re going to be a corporate raider, if you’re going to be a Governor Romney or whatever and you take over a company, you do what Sam Zell did with the Chicago Tribune: You loot the pension fund, you empty it out to pay the bondholders that have lent you the money to buy out the company. You then tell the workers, “I’m sorry there is nothing there. It’s wiped out.” Half of the employee stock ownership programs go bankrupt. That was already a critique made in the 1950s and ‘60s.

via Michael Hudson: Retirement? What Social Obligation? | naked capitalism

The Big Problem With Big Data

Cathy O’Neil (aka MathBabe) has posted another good piece on the drawbacks of using big data-driven algos to make important choices. Via Bloomberg View:

One issue is that the algorithms tend to use linear models, so they assume that more is always better, and way more is way better. This can be fine when dealing with attributes such as education or experience. Something like Facebook activity, by contrast, could have a golden mean — a reasonable amount might suggest engagement in a community, while an abundance could indicate addiction.

More important, such algorithms will tend to discriminate against attributes that, though beyond people’s control, have historically been correlated with a lack of success. A marker of poverty or race, for example, can translate into a demerit, even if the person is eminently qualified — thus reinforcing the historical pattern that the algorithm finds in the data.

This follows on an earlier post (Insurance and Big Data Are Incompatible) regarding the drawbacks of allowing health insurers to use big data-fed algos to make coverage and premium-setting decisions.

These algos are touted as impartial arbiters, free from human bias and prejudice. They’re not. They draw conclusions from properties exhibited by large groups of people – their Facebook likes, zip codes, career choices – and apply them to individuals. In the aggregate, this might work, but for the individual person seeking insurance, applicant seeking a job, inmate seeking parole or homebuyer seeking a mortgage, the outcome can be manifestly unfair and riddled with the types of biases that the systems were meant to eliminate in the first place.

via Bigger Data Isn’t Always Better Data – Bloomberg View

This is Worse than Before the Last Three Crashes | Wolf Street

How long will “magical thinking” sustain the rally? No way to say. But when the gears are reversed, it could get ugly…. From Wolf Street:

“There are a million reasons why multiple compression hasn’t started yet, including the scorched-earth monetary policies by central banks around the world and the hope for miracles during the Trump administration.”

via This is Worse than Before the Last Three Crashes | Wolf Street