Would you believe someone who claims knowledge of how to transform lead into gold, and yet he is not rich? Enter the perplexing world of financial academia, the modern-day “alchemists”
According to the just-published 2016 Rich List of the World’s Top-Earning Hedge Fund Managers by Institutional Investor’s Alpha magazine, eight of the top ten earners fall into the “quant” category, and half of the 25 richest of the year are quants. The firms listed include the likes of Renaissance Technologies, D.E. Shaw, Two Sigma, Millennium, Citadel and Schonfeld, none of which engage in “smart beta” or factor-based investments.
Continue reading Where are the billionaire financial academics?
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
Continue reading Tough times for hedge funds
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
Continue reading How well does a “robot AI” predict the Japanese stock market?
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
Continue reading How well does the “January barometer” work?
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
Continue reading Overview of the Mathematical Investor
When a prophet speaketh, … if the thing follow not, nor come to pass, … the prophet hath spoken it presumptuously: thou shalt not be afraid of him.” [Deuteronomy 18:22].
In a December 2014 Math Investor blog, we assessed how 2014 market prophets had fared (answer: not very well). Thus with the holiday season once again upon us, it is time to check scores. So how have 2015 prophets performed? Can prophets make profits?
Stock pickers lose
2015 was not a good year for stock pickers. According to Thomson Reuters and FacSet, the ten U.S. stocks that leading Wall Street
Continue reading High noon for 2015 market prophets
Reproducibility in scientific research
In the past year or two, the reproducibility of research results in finance and economics has come under serious question.
If it is any comfort, similar difficulties have emerged in numerous other scientific fields. In 2011, a team of Bayer researchers attempted to reproduce a set of key published pharmaceutical studies. They were only able to validate 11 out of 67 of these studies. Similarly, in 2012, Amgen attempted to reproduce a set of studies in oncology (cancer). They were only able to reproduce 6 out of 53 (11%). A commentary in Nature remarked, “Even knowing
Continue reading Is research in finance and economics reproducible?
Hedge funds are a boutique segment of the investing world, usually marketed to large institutions and wealthy individuals (not to the general public). As the name implies, many of these funds combine a somewhat more risky overall strategy, operated by highly professional traders, with a relatively safer “hedge.” Together, these two balancing strategies seek overall returns exceeding more conventional investments with less susceptibility to losses during periods of higher volatility. Worldwide, hedge funds manage roughly USD$3.2 trillion in assets.
Hedge funds typically charge a management fee of around 2 percent, and a performance fee (a take on profits) of around
Continue reading Are hedge funds losing their edge?
As we emphasized in earlier Math Drudge blogs (May 2014 and July 2014), individual investors are not very well equipped, and certainly not very effective, in managing their own investments, or in making other key financial decisions.
U.S. 401(k) accounts, and their equivalents elsewhere, are a particular problem. According to the 2014 DALBAR report, over the past 20 years the average “equity fund” investor achieved an average 5.02% annualized return, which is 4.2% less than the 9.22% than he/she could have achieved by simply investing funds in an S&P500 index-tracking fund. Investors in “fixed income funds” did more poorly
Continue reading Do individual investors understand Social Security and its overseas counterparts?
The Social Science Research Network’s Econometrics: Mathematical Methods and Programming eJournal distributes working and accepted paper abstracts in the area of mathematical methods applied to econometrics. The journal maintains a list of the All Time Top Ten Papers of the journal, based on total download counts from the journal’s SSRN website from January 2, 1997 through the current date. The current top ten list is shown below, together with download counts as of June 3, 2015. These are selected out of a current total of 4,201 papers.
We note with some measure of satisfaction that three papers from this list,
Continue reading Three of the all-time top ten SSRN Econometrics:Math papers are from the MAFFIA