Guggenheim says bonds not stocks for next "long term"

[bobandsherry]

Quote:

Originally Posted by JustCurious Actually, the Bogleheads have been doing a contest every year since 2013 to see who can predict the S&P500 closing price at the end of the year. The contest tracks professional predictions as well as individual Boglehead predictions. https://www.lostoak.com/ls/diehards/...t/default.aspx

Thanks for sharing the link. Interesting to see individual Bogleheads fairing much better than the professionals on current outlook. Interesting to look at the predictions from prior years.

[Sojourner]

The biggest obstacle in trying to predict the performance of the S&P or other broad indices is, for lack of a more concise term, the "butterfly effect". No matter how much careful analysis and research and modeling you do, one or two entirely unpredictable, small events can (and usually do) have an enormous impact on the system, leading to vastly different outcomes. This is a fundamental property of complex, nonlinear systems such as capital markets. It's basic, inescapable science that can't be overcome by better modeling or analysis, period.

So, given this, I know that medium-to-long term predictions of market performance are little more than educated guesses and should be taken with a grain of salt.

[OldShooter]

Quote:

Originally Posted by Sojourner ... So, given this, I know that medium-to-long term predictions of market performance are little more than educated guesses and should be taken with a grain of salt.

Agreed. I'd propose a small simplification, though:

xx, xxxxx xxxx, x xxxx xxxx xxxxxx-xx-xxxx xxxx predictions of market performance are xxx xxxx xxxx xxxxxxxx guesses xxx xxxxxx xx xxxxx xxxx x xxxxx xx xxxx.

[Blue Collar Guy]

Quote:

Originally Posted by JustCurious Actually, the Bogleheads have been doing a contest every year since 2013 to see who can predict the S&P500 closing price at the end of the year. The contest tracks professional predictions as well as individual Boglehead predictions. https://www.lostoak.com/ls/diehards/...t/default.aspx

the pros were really off in 2008, I like this link, Ill look at it more over my afternoon coffee.

[OldShooter]

Quote:

Originally Posted by Blue Collar Guy This one is old, but very hysterical. Overall they are right less than half the time ,hahahah. But some managed to break 50 %.[/url].https://www.forbes.com/sites/rickfer.../#6b1d695727c0. https://www.cxoadvisory.com/gurus/

Thanks for the cxo link. Very interesting.

There is another important aspect of forecasting that has not come up here yet: persistence. For example, a guru who was correct with several forecasts in a row is exhibiting persistence. Looking for persistence is the way to differentiate skill from luck.

No joy here however. If you accept active mutual fund managers as gurus, the semiannual S&P Manager Persistence report cards basically says that almost no managers exhibit persistence. From the latest one: " It is worth noting that no large-cap, mid-cap, or small-cap funds managed to remain in the top quartile at the end of the five year measurement period. This figure paints a negative picture regarding long-term persistence in mutual fund returns." (Thought Leadership - Research - S&P Dow Jones Indices)

The S&P SPIVA report card is also a good read. Again, if you accept active managers as gurus, it says that the gurus consistently fail. "Over the one-year period, 56.56% of large-cap managers, 60.69% of mid-cap managers, and 59.55% of small-cap managers underperformed the S&P 500, the S&P MidCap 400, and the S&P SmallCap 600, respectively. This is really not too far from the 50/50 cxo data if you consider that the weight of fees will inevitably make the average of all active funds underperform.

[gcgang]

Guggenheim? Their predictions were so good, they built a museum for em, didn't they?

But count me as a believer that valuation makes a difference in long term (10 yr) returns. Whether they can be so exact, 0.9% for ten years, I doubt. Lower than normal, maybe way lower, ok.

[dallas27]

Margin of error, +/- 1000%