On Making Good Predictions – Part 2

crystal-ball

(Part 1)

Fast forward to today and check out this interesting website – IPad Death Watch.  It tracks various doomsday predictions for Apple from many years back.  In fact, it is made entirely out of the documented wrong predictions.  Masterpieces like this are listed and cataloged there for the future generations to enjoy:

5 Reasons Why Apple’s iPad Tablet Will Fail:

  1. It won’t fit in your pocket.
  2. It’s too expensive.
  3. It won’t replace the laptop.
  4. You only get access to a watered-down Internet.
  5. No one really needs an iPad.

This particular prediction is from 2010. Do you think its author was later asked to apologize, to admit he was wrong, or to leave his job? Or perhaps he simply lost professional credibility?  Maybe, I don’t know. But I really doubt it.  Likely, he/she is still happily employed and getting paid to make new bold predictions.

If you want to be entertained, plenty of other predictions on that website are worth reading.

We can dismiss this and examples similar to it by saying that predicting market response to a product is really hard, it isn’t a real science, and people making  these predictions are not really trained for this and can therefore be wrong from time to time.

But what about the economy and economic predictions?

These can be extremely valuable to all of us (assuming the predictions are correct)!   And, those predictions seem to be based on some sort of proven fundamental rules and laws (like the law of supply and demand), and are made by people from reputable universities and companies who have a relevant education and advanced degrees… Right?   And they award a Nobel Prize in this field every year!   Surely, we have a good reason to follow their advice, right? Right?

img_0624

Well, not really. They are wrong most of the time−we just don’t know all of the facts and have  very short, forgiving memories.

Let me quote Jan Hatzius here (See! I am doing what I discussed in the beginning of this article−quoting experts!), the chief economist of Goldman Sachs, when talking about the value of economic forecasts:

“Nobody has a clue. It’s hugely difficult to forecast the business cycle. Understanding an organism as complex as the economy is very hard.”

The following few examples demonstrate his point:

  • The majority of economists didn’t “predict” the three most recent recessions (1990, 2001 and 2007) even after they had begun.
  • In November 2007, economists in the Philadelphia Federal Reserve’s Survey of Professional Forecasters called for GDP growth by 2.4 percent for 2008, with only a 3 percent chance of a recession, and only a 1 in 500 chance of the GDP falling by more than 2 percent. GDP actually fell by 3.3 percent.
  • Since 1990, economists have forecasted a year in advance only two of the 60 recessions that occurred around the world.

crisis-2008

You probably all remember the economic crisis of 2008…In December 2007, Goldman Sachs chief investment strategist Abby Joseph Cohen made a prediction that the S&P 500 would hit 1,675 by the end of 2008, a climb of 14% — it actually ended up to be below 900.

And how about this book:  “Dow 36,000: The New Strategy for Profiting fdow-36000rom the Coming Rise in Stock Market” (link)?  The authors of this “interesting” masterpiece argued that the Dow Jones may rise to 36,000 within just a few years.  That book was published in 2000.

Former Fed chairman Alan Greenspan warned in his 2007 book, “The Age of Turbulence,” that the world might need double digit interest rates to control inflation in the near future. Rates have been near zero for the vast majority of the time since then, and inflation has not been severe.

There are many examples like this – too many to mention.  And they are not completely unexpected if you know what the famous John Maynard Keynes, considered to be the founder of modern macroeconomics, said (link):

“Economists set themselves too easy, too useless a task if in tempestuous seasons they can only tell us that when the storm is past the ocean is flat again.”

If you ask me, “but what about all those other successful predictions?  Aren’t you just listing the examples of bad and forgetting about the good?”  I think that Nassim Taleb had a good explanation for this in his book titled “Fooled by Randomness”: making most forecasts is like playing Russian roulette, and people hear your story only when you survive the game (in other words, when your prediction is right).

Except, I may add, the wrong prediction doesn’t kill in the above game of “prognostication Russian roulette” (unlike 1000s of years ago), which encourages people to try the game again and again.

And people like these operate without much accountability and are rarely confronted with tough questions about their past accuracy and true predictive abilities.  They are right there, on television, on the Internet, making new predictions and new promises and writing new books.  For example, one of the co-authors of the “Dow 36,000…” book (above) already published another book on smart investment in 2011 called “Safety Net: The Strategy for De-risking Your Investments in a Time of Turbulence” (link).

I should probably get it right away!

(To be continued)

(Part 1)

This entry was posted in Analytics, data analytics, big data, big data analytics, data on the internet, data analytics meaning, Editorials, Money, business, investments, statistics, trends, Past, present, and future and tagged , . Bookmark the permalink.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s