Progress Daily

[I]t does not make sense to talk about market efficiency without taking into account that market participants have bounded resources. In other words, instead of saying that a market is “efficient” we should say, borrowing from theoretical computer science, that a market is efficient with respect to resources S, e.g., time, memory, etc., if no strategy using resources S can generate a substantial profit. Similarly, we cannot say that investors act optimally given all the available information, but rather they act optimally within their resources. This allows for markets to be efficient for some investors, but not for others; for example, a computationally powerful hedge fund may extract profits from a market which looks very efficient from the point of view of a day-trader who has less resources at his disposal—arguably the status quo.

“A Computational View of Market Efficiency”

—

“We analyze the intertemporal stability of returns to technical trading rules in the foreign exchange market by conducting true, out-of-sample tests on previously published rules. The excess returns of the 1970s and 1980s were genuine and not just the result of data mining. But these profit opportunities had disappeared by the mid-1990s for filter and moving average (MA) rules. Returns to less-studied rules, such as channel, ARIMA, genetic programming and Markov rules, also have declined, but have probably not completely disappeared. …The most likely time for a structural break in the MA and filter rule returns is the early 1990s. These regularities are consistent with the Adaptive Markets Hypothesis (Lo, 2004), but not with the Efficient Markets Hypothesis.”

“The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market”

—

“Have You Reviewed Papers on the Adaptive Market Hypothesis?,” CXO Blog

The cost of sequencing DNA has fallen from about $1 per base pair in the mid-1990s to a tenth of a cent today. Rob Carlson started tracking the price of DNA synthesis a decade ago. He found a steady decline, from over $10 per base pair to, lately, well under $1. This decline recalls Moore’s law, which, when promulgated in 1965, predicted the exponential rise of computing power.

A study by Amir Barnea, Henrik Cronqvist and Stephan Siegel (”Nature or Nurture: What Determines Investor Behavior?“), based on characteristics for approximately 40,000 identical and non-identical twins from the Swedish Twin Registry and associated investing data for the period 1998-2006, concludes that genetics explain up to 45% of individual variation in stock market participation, asset allocation and portfolio risk choices.

Genetic influence is robust to differences in age, education and net worth. Genetics explain more of the variation in individual investing behavior than does an extensive set of individual characteristics combined.

Family environment has an effect on the investing behavior of younger individuals, but this effect disappears as they acquire non-family experiences.

“The Genetics of Investing (Not the Algorithms),” CXO

The number of foreign residents in Germany increased from 3m in 1971 to 7.5m in 2000 though the number of foreigners in the workforce did not budge. Today immigrants account for about 10% of the population of most west European countries, and up to 30% in some of Europe’s great cities.

In the middle of the 20th century there were almost no Muslims in Europe. Today there are 15m-17m, making up about half of all new arrivals in Europe.

Only 19% of Europeans think immigration to be a good thing for their country; 57% think that their country has “too many foreigners.”

Review of Christopher Caldwell’s Reflections on the Revolution in Europe: Immigration, Islam and the West

In a study just published in Evolution and Human Behavior (”Costs and benefits of fat-free muscle mass in men: relationship to mating success, dietary requirements, and native immunity“), Steven Gaulin analyzes muscularity.

The data came from the NHNES, which followed 12,000 American men and women over the course of 6 years. The researchers found that men require 50% more calories than women do, even after adjusting for activity levels, and that their muscle mass is the strongest predictor of their intake of calories — stronger than their occupation or their body-mass index. Men’s immune systems are less effective than those of women (which was known before), and become worse the more muscular the men are (which was not).

The more muscular a man, the more sexual partners he reported, both in the past year and over his lifetime, and the earlier his first sexual experience was likely to have been.

Gaulin speculates that an evolutionary fight is going on between natural selection, which conserves metabolic expenditure and promotes longevity, and sexual selection, which willingly trades both for extra mating opportunities. This may explain why men have such a range of muscularity. In the past, the strong man would have had better mating opportunities in the short term, but the skinny guy who outlived him could have had just as much reproductive success over the course of his longer life.

“Mr Muscle,” The Economist

Research by Paola Sapienza & Luigi Zingales (”Gender differences in financial risk aversion and career choices are affected by testosterone“) suggests that testosterone levels may explain why men dominate risky financial professions.

The researchers measured the amount of testosterone in the saliva of aspiring bankers (MBA students from the University of Chicago). They also estimated the students’ exposure to the hormone before they were born by measuring the ratios of their index fingers to their ring fingers (a long ring finger indicates high testosterone exposure) and by measuring how accurately they could determine human emotions by observing only people’s eyes, which also correlates with prenatal exposure to testosterone.

The students had to decide between a 50:50 chance of getting $200 or a gradually increasing sure payout, which ranged from $50 up to $120. The point at which a participant decided to switch from the gamble to the sure thing was reckoned a reasonable approximation of his appetite for risk.

Women and men with the same levels of testosterone generally switched at the same time, demonstrating similar risk preferences. Women who had more testosterone were more risk-loving than women with less, while the data for men at the lower end of the spectrum displayed a similar relationship. Curiously, the relationship between testosterone and risk taking was not as strong for men with moderate to high levels.

The correlation was strongest when the salivary measure of testosterone was used.

The researchers then followed the subjects’ progress after they graduated, to see what sort of careers they entered. Men were more likely than women to choose a risky job in finance but the difference was accounted for entirely by their levels of salivary testosterone.

“Risky business, The Economist