Fedspeak, Karl Popper and market directions

“Risk takers have been encouraged by a perceived increase in economic stability to reach out to more distant time horizons. But long periods of relative stability often engender unrealistic expectations of it[s] permanence and, at times, may lead to financial excess and economic stress.” — Alan Greenspan, testimony before the House Financial Services Committee on July 20, 2005.

Confused? You are not alone. This is a typical example of what is known in the financial world as Fedspeak — obscure language used by U.S. Federal Reserve Chairmen in unavoidable public speeches, so as not to cause unnecessary market instability. Alan Greenspan is

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Seminar at the International Association for Quantitative Finance

The Mistress of Investment Management

Until a few years ago, applied mathematics had a very limited role in the financial profession. Standard applications involved pricing of derivative products and convex portfolio optimization. But with the advent of High-Frequency Trading and Big Data, Mathematics is now pervasive. Today, virtually every investment decision requires the analysis of massive amounts of unstructured data. Algorithms must be developed to order, filter, process, store, visualize that data. And that is before we are ready to model it! Networks must be designed to handle flows of information from multiple sources of varying quality. Optimization methods are

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The Mathematical Investor: A personal perspective by JMB

[Editorial note: During the next few weeks, each of the editors of the Mathematical Investor will provide, in an essay format, some personal background explaining the origins of their interest and work in this area. This is a perspective essay by Jonathan M Borwein.]

Early interest in economics and finance

I went to Oxford in 1971 to study functional analysis and number theory but ended up (very quickly) working in Optimization theory with Michael Dempster, who even then was running models of the full non-defence US budget. My early history is described in a chapter of a forthcoming book. My

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Testing early warning indicators

According to a recently-published article on “early warning indicators,” the gain or loss of the S&P500 index (a widely cited metric of the U.S. stock market) during the seven trading days around the new year (the last five days before and the first two days after the new year) predicts the performance of the index for the entire coming year with 85% accuracy. An accuracy level at 85% is very high by any standard. Nevertheless, scientifically literate investors will find this claim unsatisfactory.

First of all, the period over which this indicator is tested is not specified. More importantly, if

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