MAFFIA paper receives the “Silver Bullet” award

We have learned that two of our MAFFIA group (Bailey and Lopez de Prado), together with Jonathan Borwein (posthumously) and Amir Salehipour, were awarded the “Silver Bullet” award (from the “Dash of Insight” group) for our article “Evaluation and ranking of market forecasters.”

See the entry for 5/20/2017 HERE.

(Only Bailey’s name was listed at the above URL, but all authors should be equally credited.)

Our preprint manuscript is available HERE.

Which hedge funds actually beat the market?


The last few years have been difficult times for hedge funds. For the majority of these funds, performance has lagged market averages, certainly not in keeping with the exalted fees charged by the fund managers. For example, as of 1 July 2017, the HFRI Fund Weighted Composite Index is up 3.28% year-to-date, and 4.79% annualized gain for the previous 5 years. The corresponding figures for the S&P500 Index (including dividends) are 9.34% and 13.6%.

These chronic performance shortfalls have led many clients to rethink their hedge fund investments. In 2014, the California Public Employees’ Retirement System (CalPERS), the largest

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Gender, marital status and investment performance

The folly of panic selling and market timing

A recent DALBAR study found that over a 30-year period, the average self-directed equity mutual fund investor earned only 3.7 percent, compared with 10.3 percent that could be obtained by simply investing in a S&P500 index fund. Much of this huge shortfall is due to panic selling during market downturns, or attempts to time the market.

A typical scenario is that in the midst of a market downturn, investors panic and sell out, with the intent of waiting for the market to “bottom out” before reinvesting. Some investors believe that they can

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As the old joke says, “math is what mathematicians do.” Somehow this simple tautology is lost in the dishonest world of finance

Quantitative investing: A crisis waiting to happen

In a recent WSJ article, Jason Zweig brilliantly summarizes the unbearable hype and hubris exhibited by some self-titled “quants”:

BlackRock, the giant asset manager, recently announced it will rely more heavily on computers to pick stocks. Rob Arnott, a leading advocate of mechanical investing approaches, said this past week that it’s “actually relatively easy to beat the market” if you get the math right.

Mr. Zweig is of

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How accurate are market forecasters?

Optimistic and pessimistic forecasters

Many investors, individual as well as institutional, rely on market experts and forecasters when making investment decisions. Needless to say, some of these forecasts tend to be more accurate than others. How can one decide which of these forecasts, if any, to take seriously?

Some of these forecasts are optimistic. For example, on 3 January 2015 Thomas Lee predicted that the S&P 500 index would be at 2325 one year hence. (The S&P 500 ranged between 1867 and 2122 during this period, closing at 2012 on 4 January 2016, well short of the goal.)

Some are

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Investment advice from the world’s most successful stock picker

Warren Buffett, the Chairman of Berkshire Hathaway since 1970, sometimes called the “oracle of Omaha,” is arguably the world’s most successful stock-picking investor. Under his leadership Berkshire Hathaway has grown to a financial powerhouse, with total market capitalization of approximately USD$420 billion. Buffett has certainly shared in this success — as of this writing (27 February 2017), Buffett’s net worth was USD$76.5 billion, making him the second wealthiest person in the world.

So what advice does Buffett have for the rest of us mere mortals, individual investors as well as institutional investors?

His answer is quite arresting: Invest mainly in

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Backtest overfitting in smart beta investments


In the past few years “smart beta” (also known as “alternative beta” or “strategic beta”) investments have grown rapidly in popularity. As of the current date (January 2017), assets in these investment categories have grown to over USD$500 billion, and are expected to reach USD$1 trillion by 2020. More than 844 exchange-traded funds employing a smart beta strategy are now in operation.

The basic idea behind smart beta is to observe that traditional capitalization-weighted investments (such as S&P 500 index funds) tend to be heavily weighted in favor of securities from large, stable firms. Thus the smart beta community

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How much of hedge fund profits are taken by management?

“Miserable, miserable”

The past few years have been rough on hedge funds. Some have done very well, such as the Medallion Fund, a highly mathematical quant fund operated by Renaissance Technologies. It has produced returns averaging over 30% since its founding in 1988, totaling approximately $55 billion in profits, making multimillionaires of many of its very fortunate investors, who for the most part are professional mathematicians and others employed by Renaissance.

For most other hedge funds, it has been a different story, namely year after year of subpar performance. For example, the HFRI Equity Hedge (Total) Index of U.S. equity

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Erdos numbers: A true “Prince and the Pauper” story

I still say to myself when I am depressed and find myself forced to listen to pompous and tiresome people: “Well, I have done one thing you could never have done, and that is to have collaborated with Littlewood and Ramanujan on something like equal terms.”

A Mathematician’s Apology (1941). G.H. Hardy (1877-1947)

Mathematics as the great equalizer

What do many of the most successful (and richest) hedge fund managers have in common with a life-long homeless person? That they have worked together, on equal terms, in solving some of the hardest mathematical questions.

Yes, in a stratified world

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Mathematics and economics: A reality check

One of us (Marcos Lopez de Prado) has published the article Mathematics and economics: A reality check in the Journal of Portfolio Management. The article is open-access — there is no fee for viewing or downloading.

Lopez de Prado argues that while economics is arguably one the most mathematical of the social sciences, the mathematical methods of economists may not be up to the task of modeling the complexity of the social institutions and the business/finance world. Outdated and inappropriate statistical methods are of particular concern, with economists and econometricians often drawing very dubious conclusions from the available data.


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