Mortgages Are About Math: Open-Source Loan-Level Analysis of Fannie and Freddie

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Mortgages Are About Math: Open-Source Loan-Level Analysis of Fannie and Freddie [M]ortgages were acknowledged to be the most mathematically complex securities in the marketplace.

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This week on the JOURNAL, Bill Moyers talked with economist Dean Baker and columnist bob herbert about the economy and the political conditions that have contributed to its troubles. Bob Herbert said:.

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Loan-level analysis of Fannie Mae and Freddie Mac data – toddwschneider/agency-loan-level

Today, in addition to Fannie and Freddie making their data freely available, we’re in the midst of what I might call the "medium data" revolution: personal computers are so powerful that my MacBook Air is capable of analyzing the entire 215 GB of data, representing some 38 million loans, 1.6 billion observations, and over $7.1 trillion of origination volume.

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In this brief, new loan-level data recently released by Freddie Mac on more than 17 million single-family mortgages are analyzed to reveal a range of new and useful insights into the ultimate financial losses associated with a loan after it experiences a credit event.

> It should not be overlooked that in the not-so-distant past, i.e. when I worked as a mortgage analyst, an analysis of loan-level mortgage data would have cost a lot of money. Between licensing data and paying for expensive computers to analyze it, you could have easily incurred costs north of a million dollars per year. If it existed. It did not.

Fannie Mae and Freddie Mac Data. Multifamily Data includes size of the property, unpaid principal balance, and type of seller/servicer from which Fannie Mae or Freddie Mac acquired the mortgage. multifamily unit-class data includes a linkage to the property record in the Multifamily Data Set and information on the number and affordability of the units in the property.

Conversing with Bill Moyers on the JOURNAL this week, media expert Kathleen Hall Jamieson suggested that misleading political attacks can undermine the quality of our discourse by emphasizing talking.