CXO study on forecasters

[larryswedroe]

http://www.cbsnews.com/8301-505123_162-57568891/who-are-the-most-least-accurate-stock-gurus/

here is my take, looking at how well some of the more famous names have done as well as the dispersion of forecasting accuracy, even worse than would be expected randomly, another reminder of why we should avoid paying attention to market forecasts

Best wishes
Larry

[umfundi]

One should also consider that forecasts are tailored to their audience:

www.tinyurl.com/wetbias

(A NY Times article)

In what may be the worst-kept secret in the business, numerous commercial weather forecasts are also biased toward forecasting more precipitation than will actually occur. (In the business, this is known as the wet bias.) For years, when the Weather Channel said there was a 20 percent chance of rain, it actually rained only about 5 percent of the time.

People don’t mind when a forecaster predicts rain and it turns out to be a nice day. But if it rains when it isn’t supposed to, they curse the weatherman for ruining their picnic. “If the forecast was objective, if it has zero bias in precipitation,” Bruce Rose, a former vice president for the Weather Channel, said, “we’d probably be in trouble.”

The analogy for financial soothsayers is probably that they are simply wrong. Nothing intentional about that.

But, I believe there is a "bear bias". People are happier with down predictions that do not happen than they are with up predictions that do not happen.

Keith

[larryswedroe]

Keith
Weather forecasts have a reason to bias their predictions. So do forecasters. The reason is that average or normal type forecasts don't attract attention while extreme ones do. So you have to understand that many forecasters are not in the business of forecasting but are instead in the business of fame. To be famous you must forecast an extreme event and then get it right. If wrong no one pays attention anyway. IF right you get your fame, and no one holds you accountable for your prior wrong forecasts because accountability would ruin the game
Best wishes
Larry

[Akiva]

http://www.cbsnews.com/8301-505123_162-57568891/who-are-the-most-least-accurate-stock-gurus/

here is my take, looking at how well some of the more famous names have done as well as the dispersion of forecasting accuracy, even worse than would be expected randomly, another reminder of why we should avoid paying attention to market forecasts

Best wishes
Larry

Ferri posted a similar article not too long ago and I had the same complaint then -- "accuracy" isn't what matters. (To see this just ask yourself how reasonable it is to believe that you could have beaten the market by doing the opposite of what this panel of experts advised.) You have to look at expectancy -- the probability of being right times the profits if you are right minus the probability of being wrong times the losses if you are wrong. (This is a simplification; in reality you want to integrate over the probability distribution.)

Now, I don't believe for a minute that these guys have positive expectancy (if they did why would they share their information publicly instead of trading on it?), but there are a lot of bad studies that try to "show" that gurus, active managers, etc. don't add value and end up using fallacious arguments and bad statistics. This is disingenuous and unnecessary.

[larryswedroe]

akiva
A much simpler test is available, are you better off ignoring them.
Larry

[Akiva]

akiva
A much simpler test is available, are you better off ignoring them.
Larry

That's my point. There's no information in these predictions. So you are better off ignoring them. (But the study you quoted doesn't actually prove this. Depending on what other assumptions we make, it could come out that you make money by doing the opposite or by following their advice. Neither of which should be true...)

[larryswedroe]

akiva
Yes it doesn't scientifically prove anything but it does show IMO that forecasts are almost certainly of no value, you cannot tell who is a good forecaster or bad, you cannot tell which of their forecasts you should listen to, and so on. The data looks like random or worse outcomes on being right or wrong.

[umfundi]

Someone should study the forecasters' customers. What do they believe?

Who believes horoscopes? Yet, they are published every day.

Keith