How to Speak Money: What the Money People Say-And What It Really Means

How to Speak Money: What the Money People Say-And What It Really Means

John Lanchester

Language: English

Pages: 288

ISBN: 039335170X

Format: PDF / Kindle (mobi) / ePub


“One of the world’s great explainers of the financial crisis and its aftermath.”―Michael Lewis

To those who don’t speak it, the language of money can seem impenetrable and its ideas too complex to grasp. In How to Speak Money, John Lanchester―author of the New York Times best-selling book on the financial crisis, I.O.U.―bridges the gap between the money people and the rest of us.

With characteristic wit and candor, Lanchester reveals how the world of finance really works: from the terms and conditions of your personal checking account to the evasions of bankers appearing in front of Congress. As Lanchester writes, we need to understand what the money people are talking about so that those who speak the language don’t just write the rules for themselves.

Lanchester explains more than 300 words and phrases from “AAA rating” and “amortization” to “yield curve” and “zombie bank.” He covers things we say or hear every day―such as GDP, the IMF, credit, debt, equity, and inflation―and explains how hedge funds work, what the World Bank does, and why the language of money has gotten so complicated. Along the way he draws on everything from John Maynard Keynes to the Wu-Tang Clan, Friedrich Hayek to Thomas Piketty, The Wealth of Nations to Game of Thrones.

A primer, a polemic, and a reference book, How to Speak Money makes economics understandable to anyone. After all, “money,” as Lanchester writes, “is a lot like babies, and once you know the language, the rule is the same as that put forward by Dr. Spock: ‘Trust yourself. You know more than you think you do.’”

 

 

 

 

 

 

 

 

 

 

 

 

City of London but also in the eyes of US law enforcement. That has profoundly changed the mood music, and the resources devoted to investigating wrongdoing. If Libor had been of relevance only within the UK, the same actions could have taken place in the same institutions, and my suspicion is that we wouldn’t have heard a word about it. The full scorecard from the Libor scandal isn’t yet in plain sight: we’re somewhere in the middle of the story, and there will be more news, more revelations,

distinctive. “Welfare scroungers” has a different spin from “benefit claimants,” who don’t sound at all the same as “the working poor,” even if these are all the same people, and the benefit they’re claiming is called “job seeker’s allowance,” where once it was known as “unemployment benefit” in an attempt to provide a heavy nudge (and to placate right-wing headline writers). Your “asylum seeker” is my “refugee”; your “entitlements” are my “pensions.” Aristotle was right when he said that man is

about. no-recourse loans Loans in which the person who has borrowed the money can stop paying the loan, forfeit the asset against which the loan was made, and walk away. The textbook example involves mortgages that go wrong: the borrower, realizing that the math has gone against him or her, decides to stop paying the mortgage and to give up the house. This is something that you would do only if the loan was for a large part of the value of the house—or even, in many cases, when the mortgage was

all the evident inequalities and injustices in the world result from those unpalatable facts. But that’s interesting, in a way, no? It would be better if the people who think that actually say it, and try to argue for it. At the moment we in the English-speaking world have a political and economic direction of travel that embodies the trends towards baked-in, permanent inequality, without the conversation in which people in favor of the arrangement spell out their views. In any case, I have to

every 4,039,906 years, and seven sigma is one day in every 3,105,395,365 years. In recent years, the mathematical models used by banks repeatedly calculated events as being at these levels of probability, despite the fact that the events kept happening. The obvious lesson was that the models were wrong, but the banks went on using them anyway. The overreliance on these models is one of the things that helped cause the credit crunch. On a personal note, I find it quite helpful to think about

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