1/ I've been getting e-mails "encouraging" me to vote one way or the other... this is how I've responded:

There is a lot of research over the past sixty years suggesting that people think prediction is much easier than it actually is (for both sides of the political spectrum).
2/ We anchor on pieces of information that are easy to remember because we've seen them in the news, but those are not a randomly chosen sample (so unsuitable for making predictions). They are also such a small sample that it's hard to draw statistically significant conclusions.
3/ "The problem is that it *feels* like a random sample and *feels* like a large enough sample, so the more information that people receive, the more overconfident they become, and (ironically) the worse their predictions get.
4/ "It's worst for experts, who have the most information and are the most overconfident.

For predictions, experts underperform both their own students and models based on simple algebra.

The work is significant enough to have won a Nobel Prize in 2002:
en.wikipedia.org/wiki/Daniel_Ka…
5/ It's also been featured in a book by Michael Lewis:
6/ It seems wise not to get too confident about who would make a good president.

Prediction is hard: think about 2017, when almost everyone, including me, was expecting market volatility after the election. We got the calmest market in history instead:
7/ This is not to support Trump (as I've said numerous times, I don't actually do that).

It's just to make the point that the world is counterintuitive and tends to do the opposite of what the crowd predicts will happen.

Here are some examples:
8/ When markets price in a crisis, we tend to get calmer markets and higher returns.

Conversely, when the market is pricing in calmness, the risk of a crisis actually goes up:
9/ It's historically been profitable to sell the stocks that highly-paid analysts say to buy and to buy the stocks that the analysts say to sell. This is a highly statistically significant effect and shows up in the data when measured in multiple ways.

11/ One possible explanation is that when everyone feels one way, it's easier for events to play out in the opposite fashion. A crisis (crash, high inflation, recession) can be triggered by the crowd being wrong about something and having to dump their positions at the same time.
12/ More on sentiment as a trading indicator:


So the extent that the news reflects how the country as a whole feels, how analysts feel, and how the crowd has its financial bets positioned, it tends to pay to lean in the opposite direction.

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More from @ReformedTrader

29 Oct
1/ Short-Term Momentum (Almost) Everywhere (Zaremba, Karathanasopoulos, Long)

"Contrary to stock-level evidence, we find a short-term momentum pattern in five major asset classes: the most recent month’s return positively predicts future performance."

papers.ssrn.com/sol3/papers.cf…
2/ Asset classes: Equities, bonds, bills, commodities, and currencies
Sample period: 1800-2018
Data converted to U.S. dollars
For commodities, *spot* prices are used

"The aggregate number of assets increases gradually from 16 in January 1800 to more than 250 in the final years."
3/ Short-term momentum (SMOM) = asset return in month t-1

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23 Oct
What do you or your company primarily look for in new hires?
It's interesting... whatever people who don't work in finance tell me, I almost always get the opposite result when I do these surveys.
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18 Oct
1/ The Undoing Project (Michael Lewis)

"What were people’s minds doing that led to the misjudgments that could be exploited for profit by those who ignored experts and relied on data?

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amazon.com/Undoing-Projec… Image
2/ "A big part of a consultant’s job was to feign total certainty about uncertain things.

"In a job interview with McKinsey, they told Morey that he was not certain enough in his opinions. ‘We’re billing clients five hundred grand a year, so you have to be sure.’
3/ "The firm was forever asking him to exhibit confidence when, in his view, confidence was a sign of fraudulence. They’d asked him to forecast oil for clients, for instance.

"What people said when they “predicted” was phony: pretending to know rather than actually knowing.
Read 102 tweets
14 Oct
1/ Building a Better Commodities Portfolio (Kay, Levine, Ooi, Pedersen)

"Investors can potentially build a better commodities portfolio that is risk-balanced across sectors and that targets a steady level of volatility through time."

aqr.com/-/media/AQR/Do… Image
2/ "Because commodities have exhibited low correlations to stocks and bonds, a portfolio comprised of all three has produced higher risk-adjusted returns than a 60/40 portfolio of stocks and bonds alone." Image
3/ "Commodity returns have historically shown a low correlation to other asset classes. Other common inflation protection assets – such as publicly traded REITs, natural resources equities, and TIPS – have shown far higher correlations to either stocks or nominal bonds." Image
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1/ THREAD: Magazine cover predictions, shoeshine boy tips, and other questionable calls

"On Aug 13, 1979, the front cover of Business Week featured a crumpled share certificate in the shape of a crashed paper dart: ‘The Death of Equities.‘ "

2/ Business Week's dot-com bubble prediction:

3/ "Each bull market has its rationale. In 1987, it was that since Japanese stocks were more absurd at 60x earnings, U.S. stocks were held to be safe.

"A bull market is a bit like falling in love: it has never happened to anyone before."

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13 Oct
1/ How Money Became Dangerous: The Inside Story of Our Turbulent Relationship with Modern Finance (Christopher Varelas, Dan Stone)

"How did our financial system become so labyrinthine and perilous as we became more disconnected from its workings?" (p. 2)

amazon.com/How-Money-Beca… Image
2/ "Do we really not care about looming crises (national debt, underfunded pensions/Social Security/health care, student debt), or is it that we feel shackled by our lack of understanding?

"As money continues to become a bigger part of our lives, we understand it less." (p. 2)
3/ "Not too long ago, we didn’t have the advantages the financial world now provides. For example, mortgages weren’t widely available to the general public. If you wanted to buy a house, you had to save up the entire purchase price." (p. 3)

More on this:
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