Women-led companies perform three times better than the S&P 500
fortune.com
fortune.com
Results like that are generally bunk, or if they really cared, they would have made a broader statement (in these and those periods they performed like that).
I have only looked at the Credit Suisse paper that I think started this meme, and they clearly use a cut off point that makes women led companies look good. If they start their comparison a couple of years earlier, suddenly it looks different.
That's just standard methodology for companies like Credit Suisse whose main business is convincing people to buy stock. That same method is used to make stock market funds look good all the time (so that gullible people pay the 5% premium for the seemingly brilliant manager of that fund).
Other explanations of course could be: categories of businesses were trending that were more attractive to women (like digital services vs mining or something like that). Or the market in the time favored a risk averse approach and women tend to be more risk averse (don't know that) - there was a bad economical recession in that period of time (as they claim women "manage risk better" - well there are times when more or less risk taking are called for).
Don't get me wrong, I don't mind if women are CEOs and lead companies. I'm just wary of "narratives" that sound too good or too ideologically motivated.
2. If n is very small in a several-year period, you wouldn't be able to do meaningful analyses on that period. How many women CEO's were there in the Fortune 1000 in the 80's? 90's? I'm going to guess epsilonically few.
3. Possible explanation that isn't hand-waving: selection bias, somewhat akin to the immigration effect. Because it's more challenging for women to get on a career path that eventually leads them to become a CEO, only the most determined/resourceful/hardworking will get there and be measured in the sample, whereas fewer men get weeded out. (e.g., IQ scores of H1B recipients from Asia is not representative of Asia as a continent, where IQ is a standin for whatever measurable trait you want here; and overall Asia and North America may well be quite comparable along most dimensions.)
As to your explanation 3: that's just the kind of thing people want to believe who cherish such studies. At the same time there were also women who failed as CEOs (as the article said). Sure, it's a valid hypothesis, but there would be many ways to test it. For starters, there must already be studies correlating IQ to CEO success. What do they say?
Now it seems rather curious to me that they choose 2004-2008 for their comparison (in the first paper you linked to). So strangely, they catch exactly that crash point in their interval.
It's always the same shenanigans...
Edit: But it sounds like it actually was due to the size of the dataset: https://news.ycombinator.com/item?id=9222416
Also, what percentage of companies in the S&P 500 where ran by women? I didn't see that anywhere.
Why choose all companies with female CEOs from the S&P 1000? The S&P 500 as of last year had 26 female CEOs, and if I had to guess, I'd say that number is higher than it would have been in 2002. The portfolio of "S&P 500 companies with female CEOs as of 2002" wouldn't have been diversified enough to reliably converge to the "market return of companies with female CEOs" that they were trying to investigate.
This is a great point. Anytime you see a study where the time period seems contrived, it's usually because it was used to tweak the outcome to get what the author wanted.
Never invest in the stock market!!! (Source: S&P500 from Jan 02 to Jan 08)
What does it look like?
Only skimmed it, but they have for example a chart for 2005 to 2011. Between 2005 and mid 2007the zero-women companies outperform the at-least-one-women companies, then there is some sort of crash and the roles reverse. Would be curious to see the chart for pre-2005...
You can check out the full analysis and data set in a shared IPython notebook.
The study was done over a 12 year period because that's the full length of the pricing data available in the backtester Karen was using to do the study. It would be interesting to extend the analysis back in time as well.
NB: I work with Karen at Quantopian and we both have two X chromosomes :)
Also, if you have a source of split-and-dividend-adjusted prices, you don't have to do a daily simulation, you can just simulate on the days when there is a buy or a sell.
Also, why does the leverage vary? Shouldn't it be 1.0 every day?
Apples to oranges. Why not compare female-CEO companies in the Fortune 1000 to male-CEO companies from the Fortune 1000? Why not include how male-CEO companies from the Fortune 1000 compare to the S&P 500? Why not compare female-CEO companies in the S&P 500 to male-CEO companies in the S&P 500 to the average company in the S&P 500?
Most importantly, why do people's critical thinking skills go right out the window when female positive news stories hit?
First, sorry but no excuses for releasing questionable studies that will spread like wildfire due to confirmation bias. Just because something is 'girl positive' doesn't mean we should all abandon our critical thinking skills. It's a small fraction of these feminist studies that go viral that can withstand any amount of scrutiny which makes the movement look worse.
I figured out how to get Fortune 1000 companies arbitrarily far back, and the S&P500 back to 2005. But the information is under copyright. I spent a long time thinking about the implications of helping you subvert copyright and decided that it's not something I'm going to do even though I'd like to see the study done better.
If you want the 2014 Fortune 1000 with contacts (i.e. CEO names) it costs $1799 from Fortune, the historical data from 1996-2013 costs $399/yr though it's unclear if that includes CEO names. (http://www.fortunedatastore.com/) Fortune's contact for historical data is female, she may be sympathetic to your cause. The S&P500 data might cost another $5-10k.
Since what you're doing is commercial your company has a responsibility to go through the proper channels to get your data. Really, the project is being used for advertising and brand-recognition. I also think your company has a responsibility to make sure you have the data you need to do proper analysis when you're representing the company.
Honestly I can't believe a company focused on quantitative market analysis doesn't already have this data!
Once you have CEO names it should be fairly straightforward to assign gender.
The research was done in an IPython notebook, on the Quantopian platform. You can see (and copy) the full notebook here: https://www.quantopian.com/posts/research-investing-in-women...
- women in business today are like female scientists of merely one or two generations ago. Only the brilliant / driven can overcome the obstacles, and brilliant driven people will outperform, and as CEO they drive the company to perform.
- companies that have sufficient internal mobility that a female CEO is able to be appointed, also are likely to have many other qualities that will allow the company to outperform.
Personally I prefer the second as an explanation for why the companies shown are doing better, and the first as an explanation of why those particular women are CEOs. (I'm not a big fan of the superstar CEO theory)
Thoughts?
Yes. We should take methodological criticism seriously.
If the methodology is flawed, why should effort be put into searching for hypotheses? If the methodology is flawed, then the results are not valid, and any hypotheses are meaningless as well.
More seriously there's research on company performance before and after either Norway or Sweden put a quota of woman members on company boards. I have heard differing things on it, positive and negative and would be delighted if someone who wasn't skiving off work could add to the discussion by citing some of that research. In general female and male executives are dissimilar in their career trajectories. Women are much more likely to be company lifers for one. That's not going to be the only difference but it is plausible that there are more intervening factors than whether or not the CEO has XX chromosones.
Just guessing - that's probably not it. But I think results like that are generally interesting as something seems to be going on. I just can't stand it if people jump to conclusions, usually to the ones that support their biases. It would be great to learn what is really going on.
Current count of comments = 31; points = 37.
Similarly to how during World War 2 when African American pilots were finally allowed to fly (The Tuskegee Airmen) they outperformed many other squadrons due to all the barriers put up ensured that they had the most dedicated, smartest and toughest pilots.
For example, suppose a company hired a female CEO during the market bottom in 2002 and fired her before the crash in 2008. Then, that would cause the "female CEO" statistic to be inflated relative to the S&P 500. If you calculate the relative IRR, it's more correct.
I.e., instead of a buy-and-hold S&P 500 investment vs buying/selling when the female CEO is hired/fired, you should instead buy $100k of the S&P 500 and female CEO stock SIMULTANEOUSLY, and then cash out both holdings when the female CEO is fired.
If you buy-and-hold the S&P 500 for 12 years vs buy/sell during a female CEO tenure, that's an apples-to-oranges comparison. That isn't properly adjusting for the market conditions when the female CEO was hired/fired.
He didn't provide enough details for me to check. I'd need a list of female CEO Tickers, hire/fire dates, and split-and-dividend-adjusted share price on the two dates.
On one line, buy-and-hold the S&P 500. Re-invest all dividends. You are 100% in the market at all times.
On the other line, buy-and-hold all companies run by female CEOs, weighted by the number of companies. Rebalance your portfolio every time a company is added or removed. You are 100% in the market at all times.
I think that if you look at the IPython notebook that the Fortune article refers to you can find the details spelled out in code.
(FWIW, the calculations are done by a she, not a he! It's my colleague Karen.)
The method you mention is correct. It wasn't clear reading the article that was what she did.
I'm looking for the raw list of female CEOs, Tickers, and hire/fire dates. I'm also wondering if the results are different based on sector.
If they did the same test but for any new CEO I wonder what the results would be.
What a nice sexist introduction.