Do new backtested index ETFs outperform the market?

Many investors, individual and institutional, have come to the conclusion that index-linked investments are a rational and, in the long term, profitable investment strategy.

It is certainly true that many individual investors could do far worse that merely investing, say, in a S&P500 index fund or exchange-traded fund (ETF). As we described in a previous Mathematical Investor blog, the typical U.S. equity investor has significantly underperformed the S&P500, with similarly dismal results in other asset categories. In particular, the average equity investor has a 20-year return of 4.25% per annum, compared with a 8.21% average return of the S&P500, for

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Is the stock market weaker during mid-term election years?

A recent Globe and Mail blog repeats an oft-cited claim that the U.S. stock market is weaker in mid-term election years (MTEYs). According to this blog, stock markets “have traditionally been weaker than normal during mid-term election years. Price returns during these four-year cycle lows have been atypically negative in January, but then frequently favorable in February. What’s more, March also typically posted an gain, just before a string of sub-par performances from April through September, with two-thirds of these months recording average declines.”

This is, in fact, one version of the presidential election market cycle theory first proposed by

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FAQs on Backtest Overfitting

Our recent papers [1,2] on backtest overfitting have attracted significant interest, including several press releases [American Mathematical Society, Science Daily, University of Newcastle] and news articles [Financial Times, Wall Street Journal, Bloomberg, Barron’s, Pacific Standard, Morningstar, Seeking Alpha]. The feedback so far has been encouraging, and numerous colleagues have approached us with interesting questions and requests for clarification. This blog lists and responds to a number of these items.

1. Why do so many quantitative investments fail? In the 21st century, we are surrounded by math and algorithms designed to filter noise out of signal. Why is it that the

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Pseudo-mathematics and financial charlatanism

The rise of quantitative investing

With the dramatic increase in computation power available in recent years, quantitative methods are gaining momentum in the finance world. The results, however, are mixed. The Renaissance Fund, founded by brilliant mathematician James Simons, has produced an average annual return of 35%, after fees, over a period of 25 years. Yet other quantitative funds have failed, sometimes miserably. Solid, mathematically-driven investment methods are as profitable as they are scarce!

The public rarely learns about the highly successful funds or has the opportunity to invest in them. Unfortunately, the void between the public and highly

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A sobering analysis of financial gurus’ market forecasts

CXO’s evaluation of forecasters

The CXO Advisory Group of Manassas, Virginia, which offers “objective research and reviews to aid investing decisions,” has just published an interesting evaluation of equity market forecasts. Titled Guru Grades, the column concludes that the class did not do very well!

CXO evaluated a total of 6582 forecasts for the U.S. stock market, published by 68 different market experts, over the years 2005 through 2012. These forecasts were limited to publicly published predictions (i.e., not in private newsletters), and excluded forecasts that were judged too vague or too complex be reliably evaluated.

The results were not

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Lopez de Prado and Bailey speak at “Battle of the Quants”

On Wednesday March 26, 2014 at 11:15am Marcos Lopez de Prado and David H. Bailey, two of the bloggers on this site, jointly presented a talk How to spot backtest overfitting at the Battle of the Quants meeting in New York City.

The Battle of the Quants conferences, organized by Bartt C. Kellerman of Global Capital Acquisition, are held regularly in New York City, Shanghai and London. They gather together academicians, asset managers and other professionals in the area of quantitative finance and investment.

The viewgraphs of the talk by Lopez de Prado and Bailey are available here. Their talk

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The “scary chart” fallacy

A “scary chart” has recently made the rounds of numerous financial analysts and news commentators. It exhibits what appears to be a disturbing parallel between the current U.S. stock market and the DJIA in the period (1928-1929) just prior to the 1929 crash. A MarketWatch.com article, for instance, warns that if the U.S. stock market follows the same script, “trouble lies directly ahead.” One version of the chart is the following (source: McClellan Market Report, via Matthew O’Brien):

So what are the facts here? Should investors dump their portfolios immediately?

The problem with this graph, like many of its

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The Mathematical Investor: A personal perspective by QJZ

[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 Qiji J. Zhu.]

Education and research

I entered college and started my academic career in 1978 after spending the last several years of the `cultural revolution’ in a farm. My graduate and post graduate research first started in control theory dealing with control systems modeled by ordinary, partial and stochastic differential equations in Zhejiang University, Hangzhou, Fudan University, Shanghai,

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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

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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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