
The Volfefe Index - danknutz
https://en.wikipedia.org/wiki/Volfefe_index
======
dagw
Given that JPM is publishing this I think we can draw one of two conclusions.
Either this strategy used to work, but no longer works due to it becoming too
popular. Or they never managed to actually get this strategy to work, so
they're publishing it as a fun PR piece.

~~~
jannes
I would say it's a PR piece, because they named it "Volfefe" and because the
Wikipedia article reads like it was written by a PR firm for JPM. (and if not
that, it at least quotes a lot of PR articles)

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anon9001
I'm sure there are some quants reading this thread, so here's a real question:
Can somebody explain the technical pipeline from tweet->execution?

I assume there's some low latency twitter API that you can pay big money to
access? And then I guess that goes to some array of GPUs to run the NLP model
as quickly as possible? And the NLP results get traded on by placing orders
with an exchange?

Are there companies that roll up many low latency data feeds for purposes like
this?

~~~
luc4sdreyer
Disclaimer: not a quant but I've built a similar system.

>some low latency twitter API that you can pay big money to access

Yes. The twitter firehose is the big one, where you get a stream of _all_
tweets. Twitter doesn't publish the price, and one source claims $360k/y for
half of the hose. [https://econsultancy.com/want-your-own-twitter-firehose-
you-...](https://econsultancy.com/want-your-own-twitter-firehose-you-can-now-
buy-it-for-a-price/)

>And then I guess that goes to some array of GPUs to run the NLP model as
quickly as possible?

General speaking, trained models usually aren't so big that you need a cluster
of GPUs, or even a single one. Sometimes running it on a CPU makes more sense
because if it's small enough it's just easier and cheaper.

In particular, basic NLP and sentiment analysis is pretty easy, especially
like in this case when you're dealing with a very limited vocabulary. A free
CPU based library like
[https://github.com/cjhutto/vaderSentiment](https://github.com/cjhutto/vaderSentiment)
should be good enough.

> And the NLP results get traded on by placing orders with an exchange?

Yes. Doing this quickly is pretty tricky, but financial institutions like
JPMorgan Chase would have access to an extremely fast and low cost (per trade)
API to do this. And then they probably already have the tech to strategically
place big orders, so the other bots don't realise what you're doing. Or just
use a private exchange, aka a dark pool:
[https://en.wikipedia.org/wiki/Dark_pool](https://en.wikipedia.org/wiki/Dark_pool)

~~~
askmike
Disclaimer: arguably a quant but definitely not this kind.

In this specific case you only need access to Trump his tweets, which you can
get without parsing and evaluating the firehose (expensive to get and
process).

> In particular, basic NLP and sentiment analysis is pretty easy, especially
> like in this case when you're dealing with a very limited vocabulary.

Exactly. With Trump's tweets you can probably find easy correlations between
sentiment (good or bad) and a select range of words as well as tweet times,
whether he is in office or not, whether it was tweeted from his android[1] or
not. Statistically speaking you can also look at his overall sentiment. Eg.
simply always short the market whenever he tweets might be the profitable move
80% of the time.

[1]: [http://varianceexplained.org/r/trump-
tweets/](http://varianceexplained.org/r/trump-tweets/)

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seltzered_
Carl Quintanilla (cnbc) had a thread with some of the charts on this:
‏[https://twitter.com/carlquintanilla/status/11706934775769169...](https://twitter.com/carlquintanilla/status/1170693477576916992)

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markvdb
Geeks were far faster to think of that:

[https://github.com/maxbbraun/trump2cash](https://github.com/maxbbraun/trump2cash)

~~~
paggle
Well companies like JPM only publish this stuff after the rest of the world
discovers it and it stops making money. They don’t publish actively profitable
strategies.

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villgax
I have traversed through every new article & none of them actually link to the
mysterious report. Just copying each other blindly. All I found was the
twitter thread with plots.

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skrebbel
Why is it called the Volfefe index and not the covfefe index?

~~~
divbyzer0
Vol - for volatility as it usually results in a price change. Timings of
tweets seem to coincide with market openings\closings.

edit:spelling

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ralfd
r/Wallstreetbets expertise discussion about this market index:

[https://www.reddit.com/r/wallstreetbets/comments/d1edm4/jpmo...](https://www.reddit.com/r/wallstreetbets/comments/d1edm4/jpmorgan_has_a_new_index_called_the_volfefe_index/)

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gadders
Similar to this, I think some people trade off the back of "woke" twitter
storms. They buy stock at the peak of the outrage cycle and sell when everyone
has moved on to the next.

EG Buy Papa John's Pizza on July 11th (when the CEO got fired for using the
N-word). It's up $6 since then.

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soVeryTired
Most 'research' articles are really just published for the entertainment of
traders. JPM are probably just trying to drum up some notoriety by publishing
this index.

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haywirez
I’m looking for some API or scraping source to add it as a metric to my music
app, anyone came across one?

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whoisjuan
Why would you need this for a music app at all?

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timeattack
Twitter-driven economy.

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dcanelhas
Another candidate for covfefe?

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inflatableDodo
I believe it means volatility of covfefe.

