Tough times for hedge funds

The past few years have not been kind to hedge funds, namely those specialized funds, usually marketed to large institutions and wealthy individuals, which combine a somewhat more risky overall strategy managed by highly professional traders, with a relatively safer “hedge” to limit volatility. (Our comments here refer specifically to investment hedge funds, as opposed to, for example, an airline hedging future fuel prices or an international corporation hedging future currency rates.) Worldwide, hedge funds currently manage USD$2.86 trillion in assets, down from USD$3.2 trillion in September 2015.

Hedge funds typically charge a management fee of 2 percent plus a

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How well does a “robot AI” predict the Japanese stock market?

A recent Bloomberg article reported on the work of Junsuke Senoguchi, who has developed a “robot” artificial intelligence-powered computer program that forecasts the Japanese stock market, in particular the Nikkei-225 index.

Senoguchi, who currently works for Mitsubishi UFJ Morgan Stanley Securities in Tokyo and who has previously worked for Lehman Brothers and also the Bank of Japan, has a Ph.D. in artificial intelligence (AI), and his new investment program employs AI techniques. Senoguchi is delighted when it is working well, “because I feel I can predict the future“.

While we certainly wish Mr. Senoguchi well in his efforts, we need

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How well does the “January barometer” work?

The January barometer

The January barometer is the claim, often mentioned in financial circles, that the performance of the stock market in January is a reliable portend of its performance for the full year — as January goes, so goes the year. The term was first coined by Yale Hirsch in 1972.

Many market analysts take it quite seriously. For example, a BofA-Merrill Lynch Global Research Report asserts “Based on S&P 500 data going back to 1928, January is a good predictor of the year.”

As another example, CNBC reports

The January barometer has been right in 62 of

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Overview of the Mathematical Investor

This site was created out of growing concern with the usage of less-than-fully rigorous mathematical and statistical methodologies in the financial/investment world. One example is the increasing prevalence of backtest overfitting, due in part to the ease of generating large numbers of model variations (more than statistically justified) using modern computer technology. Indeed, such statistical errors are likely the primary reason that investment strategies which look good on paper often fall flat in practice.

We are also concerned with the proliferation of quasi-mathematical investment advice and financial columns in the past few years, which appear to be based on sophisticated

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Disclaimer and copyright

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The material on this site is provided for research and informational purposes only, and does NOT necessarily represent the views or policies of the respective institutions or funding agencies of the site editors and authors. The site editors are NOT licensed, professional financial advisors to public clients, although they may provide financial advice to private clients and/or organizations in the course of their professional work. The site editors and other authors of

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