
Stocks with Outperform Ratings Beat the Market - youngprogrammer
http://blog.ayoungprogrammer.com/2017/05/stocks-with-outperform-ratings-beats-market.html/
======
ikeboy
Several flaws immediately jump out, all potentially fatal to the conclusion
and title:

1\. "We will do so by removing outliers in the 10th and 90th percentiles." you
can't remove outliers when investing unless you have a time machine

2\. Their "starting price" includes an average of 10 days, 5 of which are
before the analyst releases the recommendation. Again, to buy before the
release requires a time machine (or inside information). Suppose a stock is at
$50 for 5 days, an analyst releases a $75 target, stock jumps to $60, then
hits $70 over the next 12 months. The gain based on the average of $55 would
be $70/$55= 27%. But the average based on what price you could actually buy it
at is $70/$60= 16%.

3\. They narrow down analysts apparently a second time to pick out only the
top 10, which seems to be distinct from the first outlier removal (not
entirely clear what's being removed in either case.)

I see no statistical tests relating to removing outliers, significance, etc.
This is all besides the considerable degrees of freedom (cutoff price, cutoff
marketcap, 100 rating minimum for analysts which seems to have been
implemented after collecting data, etc).

~~~
hinkley
This has the Texas Sharpshooter fallacy all over it. Shoot at the side of a
barn and then put the bullseye where the most holes are.

Your number 3 is basically, "the ten people who did the best did better than
everybody else" really? You don't say...

~~~
youngprogrammer
This is nothing like the sharpshooter fallacy. The analysis determined the
average performance of the analysts with >100 stocks rated and 10 analysts out
of 16 did better than the rest.

~~~
hinkley
What? They removed all the outliers. They cooked the data to say something
that made sense instead of something that was accurate.

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chollida1
I wrote this a few years ago about trying to predict earnings movements from
stocks from about 10 years ago.

[https://news.ycombinator.com/item?id=9353569#9356652](https://news.ycombinator.com/item?id=9353569#9356652)

It turns out the best I could do at the time was to rank the analysts and
weight their preditions by their ranking.

It actually worked well for a few years, which is a lifetime for a trading
strategy.

Sadly earnings movements have gotten a lot harder to trade on.

~~~
dsacco
_> Sadly earnings announcements have gotten a lot harder to trade on._

They're absolutely more difficult for reversion strategies, but if you're
armed with more granular data of a high enough signal specific to the company
you can do targeted trades very successfully.

Accurately forecasting the earnings results ahead of time on a per-equity
basis requires more setup and data processing, but it is close to infallible
when it comes to profiting on outperforms. Collect ultra-specified
"alternative" data on individual companies with optimistic or pessimistic
analyst forecasts, analyze it, then take a contrarian position if the data
predicts an unexpected earnings result. This fails is in the case of extremely
uninformed sentiment in the opposite direction of your own position (likely by
unsophisticated investors not interpreting the results "correctly" en masse
and opting for hype instead). But you can establish a win rate with a positive
cushion.

One of the interesting things I've also done is collecting this data and using
it beyond discretionary earnings trades. For example, by selling option
premium for equities with very high theta, conversely stable revenue as
forecasted by the data and low overall sentiment activity in the market. This
is harder to pull off but it allows you to conduct a greater number of trades
on a rolling basis through the quarter.

~~~
inglor
Can confirm from my time at TipRanks that this data was useful for trading
strategies.

------
seanot
Scanning the article, it appears that the author is using two years of data in
order to reach conclusions and this is because only two years of data was
available to the author. If these same criteria were measured with two years
worth of data ending on December 31, 2008, the results would look quite a bit
different.

~~~
youngprogrammer
Unfortunately, the website I used to scrape the data only had 2 years of data.
But each datapoint is looking at each individual analyst rating and price
target for a stock and then comparing it to the price in 1 year. However, you
are correct that datapoints during a downturn would be quite different.

~~~
MatthewDPX
Founder of MarketBeat (website mentioned) here. We do have more than two years
of data (more like 7), but profile pages get too large when we publish it all
in one shot. We can make the full history available as a giant CSV file if
there's a researcher that wants to do a similar analysis over a long period of
time.

~~~
youngprogrammer
Hey Matthew, thanks for running your website! It was very helpful for
obtaining the data I needed for my blogpost.

~~~
MatthewDPX
You're welcome. Email me if you want the full data set. matt [at] mattpaulson
[dot] com.

------
inglor
So, until recently I was employee #1 at TipRanks who was founded to answer the
question "Are Analysts bullshitting us?" \-
[https://www.tipranks.com](https://www.tipranks.com)

TipRanks has loads of great and interesting information - literally what _any_
analyst ranks on _any_ stock since 2009 - huge amounts of verified data from
multiple objective sources.

> You could possibly beat the market by only buying stocks with sector
> outperforms or buy ratings and selling in one year.

This is true in theory (and very easily benchmarkable with TipRanks). If you
follow the top 25 analysts you can beat the market pretty regularly (easily
confirmed with a regression test).

You might be surprised, but you won't beat it by that much and your beta will
be higher.

Also, Marketbeat has maybe 1/3rd of all the ratings and a study based on their
data would be worthless anyway. Basing a study on their bought data would not
be indicative of a whole market trend. The data source is simply not a
reliable one.

The average analyst does not outperform the market (they lose), the average
analyst says "buy" 85% of the time and are wrong most of the time about
outperforms. The average analyst is pretty bad. Some analysts like Mark
Mahaney [https://www.tipranks.com/analysts/mark-
mahaney](https://www.tipranks.com/analysts/mark-mahaney) or
[https://www.tipranks.com/analysts/jonathan-
atkin?benchmark=n...](https://www.tipranks.com/analysts/jonathan-
atkin?benchmark=none&period=yearly) are pretty decent.

In general - be very wary of recommendations - I've not found analyst opinions
a good indicator of market performance over time (and I worked in a company
that ranked analysts for 5 years). I have found however that combining that
with several other signals (news sentiment, bloggers, insider opinions etc)
can create strategies that outperform the market (TipRanks sells such
strategies to big organizations).

I've sent my old employer an email to see if they can open some data regarding
this - and reproducing the above study with real market data.

------
odammit
I have two investment philosophies[1]:

\- invest in things that help people be lazy and/or self centered

\- invest in "evil" companies

Essentially invest in the shittiest components of being human wrapped up in a
corporation.

All of my stocks besides Snap are up between 40%-800%. I'm banking on protein
powder MLMs and camwhores cranking that Snap up over the next few years.

[1] I am not Warren Buffett or Michael Burry

------
rexstjohn
One of the important properties of the stock market is that it is a chaotic
system which changes based on observations people make of the system itself.
This has fascinating implications.

To understand why this is important, compare the following: If everyone looks
up at the sky and sees rainclouds, this does nothing to effect the likelihood
of rain. The weather doesn't depend on what people think about it.

With the stock market things are different. If Tesla stock goes to $400, you
might have a pool of people looking at charts, comparing Tesla's performance
to it's 200 day moving average and deciding that this movement is "too quick"
\- so they start selling Tesla and thus change the stock's behavior. It is a
self-reflective variety of chaos.

The same is true of stock analyst opinions: A publicly voiced opinion of a
stock directly effects the stock because people look to analysts for guidance.
If 20 analysts from important firms like Goldman Sachs appear on CNN /
Bloomberg swearing that Tesla is an outrageous BUY stock, it will cause more
people to buy the stock because analysts opinions effect the price behavior.

Long story short, what the author may actually be observing to some degree is
that analyst opinions may CAUSE stock outperformance.

~~~
LVB
My dad had an old book on technical analysis, published in the early 60s. The
intro talked about how prices move, usually with top execs telling all their
friends and family to buy, and then those people telling their network, and so
on, ending with a press release. I'm sure there's still plenty of that going
on, but I found it funny to see it just spelled out as the default mechanism
50+ years ago.

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loeg
I suspect the model comes from overfitting the training data, that is, you
would not see expect to see 15-20% outperformance from the same group of
analysts next year. Or BigBankCo would immediately hire them to invest their
cash.

There are a number of other flaws that require time traveling to make this
scheme work, and if you have a time traveling machine, beating the stock
market is even easier than this.

------
amorphid
They beat the market until they don't. Patterns that generate better returns
don't last. In this case, everyone sees that outperform rated stocks (OSR):

\- OSR yield better returns

\- OSR demand increases

\- price of OSR goes up

\- higher prices yield lower returns

\- in near future, non-OSR have more attractive returns

\- article is published saying non-OSR

\- repeat in perpetuity

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codecamper
Careful going from programming to investing. In programming you have a
confidence & that makes sense because the results are often up to your own
skills. With investing.. there is so much that is beyond what you know. Things
go against you all the time. There is all the finance stuff. But then there
are mechanics to the market that can surprise you. Triple witching? (etc etc)
It's often not about the fundamentals of a company but what the perception or
the trend is.

If I could give myself advice a year ago it would be to start with a paper
account, & seriously try to make "money" that way. It requires a ton of
research & time. Everyone else is trying the same thing so not only must you
figure out which company is under or over valued, you must figure it out
before others do. People with entire staffs doing just that.

As programmers, it can be a good idea to stick to software & service
companies, because we have a leg up on the understanding of how big those
things can get. A lot of investors fail to realize how software companies can
grow.

Check out Square.

Square has some of the best programming talent around. They have a Point of
Sale system but are also expanding into small business services (like running
payroll). I imagine they will tackle inventory, maybe wholesale ordering, do
they have a loyalty system? They are using AI to choose who gets small
business loans. They offer loans that are smaller than a typical bank would,
thus carving out a new niche. As long as they don't hand out too much money to
the wrong people, I see this business growing massively. No other software
companies seem to combine a great UI, with a mobile / tablet focus. The moat
is just once you get set up with it, it'd be a pain to switch out. Curious
what others think. (hijack the thread!)

It's my top pick at the moment. I saw it at 9 a share last summer & did not
invest enough in it. Even with a market cap of 7 billion, it would seem that
it could fit those shoes & then some.

~~~
YZF
If I could give myself advice 20 years ago it'd be 70/30 (world) index/(world)
bonds and keep doing so. Go a little heavier (80/20) on stocks in times of
crisis (>20% correction). That's all. You can just get lucky over a year and
confuse that with skill.

~~~
seanp2k2
This is what I've basically gone with and I've had good results so far. I
basically wanted the most return with the least effort, so I just went for
index funds with the lowest expense ratios.

""" There are some potential advantages to the share class structure of the
Vanguard S&P 500 ETF. Although VOO is only a fraction of the size of IVV and
SPY, VOO offers the lowest expense ratio of the group, charging just five
basis points. """ [http://etfdb.com/equity-etfs/closer-look-at-
sp-500-options/](http://etfdb.com/equity-etfs/closer-look-at-sp-500-options/)

I get that SPY is better if you need to liquidate millions on a moments
notice, but I'm definitely not there, so the nearly-double expense ratio
didn't make sense IMO.

~~~
YZF
This is the most sensible option for most people.

The tough part will be staying the course if the market crashes, which it will
at some point. It'll look like the world is ending and you should be investing
in gun powder, canned foods and gold. You need to be comfortable with the idea
that it may go down (even 40%-50%) and take a _long_ time to come back up but
you can keep buying through that and also get dividends...

------
dforrestwilson
[https://www.tipranks.com/](https://www.tipranks.com/) <\- You can see large
data sets analyzing the same thing at work here.

------
gaetanrickter
Would be nice to correlate analysts ratings that are similar to rare earth or
chemical correlations to public companies here "Profiting from Python &
Machine Learning in the Financial Markets"
[https://hackernoon.com/unsupervised-machine-learning-for-
fun...](https://hackernoon.com/unsupervised-machine-learning-for-fun-profit-
with-basket-clusters-17a1161e7aa1)

------
tomrod
This is a great exploration of something many folks wonder about. Kudos to the
author, especially in realizing that target prices aren't a great variable to
use when optimizing investments.

------
davidw
"We can beat the market"... Those are bold words.

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Spooky23
The secret to making a lot of money in stocks is simple: don't buy the stock
that go down.

------
TomK32
buy bitcoins! /s

~~~
phaed
You have eaten your words, and will continue to eat your words.

~~~
TomK32
I know, friend told me about that weirdo stuff back in 2010 and I don't fall
for the trap. Never will. Booze, that's what I invest in.

