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Just wanted to drop this info in this thread as well:

BTW., for those who'd like to take a look at short sales transaction level data as well (shout-out to @Papafox, @neroden, @KarenRei, @ZachShahan and @ggr), it's publicly available in an obscure location on FINRA's website.

The ones for June, July, August and September can be downloaded from the following links:

(October data is not available yet.)

Warning: these are very large ZIP files, hundreds of MB compressed, ~3 gigabytes uncompressed.

The structure of the short-sales transaction logs is straightforward:
  • it's text files with a fixed record format of one transaction per line:
  • "Q|TSLA|20180831|15:58:10|S|100|301.850000||"
  • 'Q' is NASDAQ, then comes the ticker, date, timestamp, short-sale marker 'S', shares sold and finally execution price.
  • the files include all NASDAQ short sales - so filter for TSLA first. The data becomes a lot more manageable once filtered out for Tesla transactions only.
  • the data is always time-delayed by several weeks - the SEC and FINRA wouldn't want to create a disadvantage for short seller 'investors' by disclosing the patterns of their trades in an overly timely fashion, right? In a world of nanosecond level trading the short-seller transaction log itself becomes public only with weeks of delay. For example it's November 7 already, yet the October data won't be available for weeks.
  • Note the scope of the 'short sales' transaction log: these are only short sales, i.e. TSLA stock sold by traders who had a short position at the time of the trade. They do not include sales by traders long in TSLA.
  • Entries with the 'E' tag can probably be ignored: these are rare transactions by 'exempt' parties such as market-makers who technically are short TSLA in terms of inventory but are not actively trying to profit from shorting Tesla - they make up a fraction of the volume and are not significant factors in determining TSLA price action.
Anyway, even with these restrictions the transaction level short-sales data is very interesting and confirms @Papafox's empirical observations that 'icicles' of sudden downwards $TSLA price movements are created by short-sellers executing 'dumb' sale orders sometimes trading more than 10k shares in a single transaction with significant 'slippage' and immediate trading loss that no true investor in Tesla would utilize when selling shares.

The short-seller transaction data is evidence that many of these $TSLA price action anomalies are not primarily caused by stops or by HFT algos, they are not primarily caused by clever large investors trying to create additional liquidity during their periods of accumulation - but are caused by bog standard short-sellers with a short position in TSLA...

In particular I took a look at the short sales transactions surrounding the infamous 'September 18 Bloomberg' article that caused a big ~10% drop in the $TSLA price from $300 levels to $270 levels.

I based this on the September transaction data available at:


The Bloomberg news article apparently broke on 11:42:27 and caused a -$13 drop within 10 seconds of heavy trading.

But the 60 minutes leading up to this event show suspicious patterns of trading that might be evidence of insider trading - short sellers shorting TSLA in the knowledge that a very negative and deceptively worded and headlined article would be released about Tesla. For example these two larger blocks of sales just 5 minutes before the news was released:

Code:
Q|TSLA|20180918|11:37:28|S|2000|301.939900||
Q|TSLA|20180918|11:37:57|S|3000|301.844300||

These were perfectly timed sales of uncharacteristically big blocks of shares, seemingly unconcerned about the execution inefficiencies such large sales suffer from. These sales were perfectly timed to benefit from the near daily high price levels, just minutes before the Bloomberg article was released.

The SEC could use their considerable investigative powers to uncover the identity behind those particular trades.

Here's the misleading Bloomberg article that triggered the sell-off:


Here's the effect on the price:
809x-1.png


That mystery mini-drop from the daily high of around $302, at around 11:30? Interesting coincidence.
 
Just wanted to drop this info in this thread as well:



In particular I took a look at the short sales transactions surrounding the infamous 'September 18 Bloomberg' article that caused a big ~10% drop in the $TSLA price from $300 levels to $270 levels.

I based this on the September transaction data available at:


The Bloomberg news article apparently broke on 11:42:27 and caused a -$13 drop within 10 seconds of heavy trading.

But the 60 minutes leading up to this event show suspicious patterns of trading that might be evidence of insider trading - short sellers shorting TSLA in the knowledge that a very negative and deceptively worded and headlined article would be released about Tesla. For example these two larger blocks of sales just 5 minutes before the news was released:

Code:
Q|TSLA|20180918|11:37:28|S|2000|301.939900||
Q|TSLA|20180918|11:37:57|S|3000|301.844300||

These were perfectly timed sales of uncharacteristically big blocks of shares, seemingly unconcerned about the execution inefficiencies such large sales suffer from. These sales were perfectly timed to benefit from the near daily high price levels, just minutes before the Bloomberg article was released.

The SEC could use their considerable investigative powers to uncover the identity behind those particular trades.

Here's the misleading Bloomberg article that triggered the sell-off:


Here's the effect on the price:
809x-1.png


That mystery mini-drop from the daily high of around $302, at around 11:30? Interesting coincidence.


Wow. Nice data. Downloading...

I just did a quick check: I selected all TSLA lines from Sept 18 and summed up all shares.
(Linux bash: 'cat FNSQsh201809.txt |grep TSLA | grep 20180918 |cut -d "|" -f 6 | paste -sd+ | bc')

There were 3'359'275 shared sold short in this dataset. There where 16'547'522 shared traded on Sept 18. This is 20.3% traded short. This dowsn't match papafox' data of around 60%. Any ideas?


-
 
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Wow. Nice data. Downloading...

I just did a quick check: I selected all TSLA lines from Sept 18 and summed up all shares.
(Linux bash: 'cat FNSQsh201809.txt |grep TSLA | grep 20180918 |cut -d "|" -f 6 | paste -sd+ | bc')

There were 3'359'275 shared sold short in this dataset. There where 16'547'522 shared traded on Sept 18. This is 20.3% traded short. This dowsn't match papafox' data of around 60%. Any ideas?


-

The short, immediate answer, is that the data @Papafox has available on the spot isn't this detailed / granular. The best real-time'ish data that the market publishes is in batches of transactions, where if any one transaction that makes up the batch includes somebody selling to open, then the batch is marked that way.

You can thank the market makers, exchanges, and so forth for cloaking short sales in obscurity.


Two things I would like to learn from this historical and apparently transactional level data, even if it's lagged in time heavily (we can start learning patterns after the fact, that we can use to inform our intuition about the present, and then compare our intuition later to reality when it gets published).

- Are transactions where somebody is BUY-TO-CLOSE flagged in some way? This is important for figuring out the change on share ownership associated with short sales. My guess is no. (So we can learn how many shares were sold short, but we can't learn how many were offset on the same day via buy-to-close, and thus we can't calculate a lagged short interest change)

- Can you (easily!?!) put the total of shares sold short with total shares transacted for each day in that data? I bet somebody else would do the work of going back to Papa's posts for those days and matching up actual short % calculated this way, with the reported short % that Papa had access to.
 
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For identifying manipulation, the placement of enormous shortsale block orders at market prices would be a clear sign of fairly obvious manipulation. If it was timed with the release of FUD articles that would be even more suspicious.
 
@Fact Checking , thanks for your good work. Here are two Fact Checking posts from the market action thread that deserve attention if you haven't seen them:

Concerning proof of how a short seller creates "icicle"

Location of more detailed short selling data from FINRA

I also added a few more pieces of data to an updated version of the above 'Bloomberg crash' analysis:


What seems weird to me is also the volume mismatch observation by @Mich:

Wow. Nice data. Downloading...

I just did a quick check: I selected all TSLA lines from Sept 18 and summed up all shares.
(Linux bash: 'cat FNSQsh201809.txt |grep TSLA | grep 20180918 |cut -d "|" -f 6 | paste -sd+ | bc')

There were 3'359'275 shared sold short in this dataset. There where 16'547'522 shared traded on Sept 18. This is 20.3% traded short. This dowsn't match papafox' data of around 60%. Any ideas?

The FINRA short-seller log covers ~3.36m shares worth of transactions on 20180918, but other sources indicate 16.5m shares traded and a higher than 50% 'short-seller percentage'.

So either the proportion of short-selling is much lower than suggested by volumebot and similar sites, or there's some reporting loophole, or I'm mis-reading the data in some fashion.

BTW., here's some more data: in the critical $20 drop during 18 minutes of the 'Bloomberg crash' short sellers sold 963,613 shares from 11:42:00 to 11:59:59 according to the FINRA data, but according to the volume data on Yahoo Finance for example the official volume for that time range was around 4.5 million shares.

Here's the minute by minute short seller volume data:

Code:
2018/09/18 11:00 -    4,743 ####
2018/09/18 11:01 -    1,399 #
2018/09/18 11:02 -    4,877 ####
2018/09/18 11:03 -    8,139 ########
2018/09/18 11:04 -    1,934 #
2018/09/18 11:05 -    5,167 #####
2018/09/18 11:06 -    2,980 ##
2018/09/18 11:07 -      931
2018/09/18 11:08 -      954
2018/09/18 11:09 -    3,653 ###
2018/09/18 11:10 -    9,564 #########
2018/09/18 11:11 -   13,226 #############
2018/09/18 11:12 -    5,285 #####
2018/09/18 11:13 -   10,684 ##########
2018/09/18 11:14 -    1,462 #
2018/09/18 11:15 -    4,745 ####
2018/09/18 11:16 -    5,906 #####
2018/09/18 11:17 -    1,896 #
2018/09/18 11:18 -    2,378 ##
2018/09/18 11:19 -    3,407 ###
2018/09/18 11:20 -    2,547 ##
2018/09/18 11:21 -    7,321 #######
2018/09/18 11:22 -    5,433 #####
2018/09/18 11:23 -    4,973 ####
2018/09/18 11:24 -    7,137 #######
2018/09/18 11:25 -    7,119 #######
2018/09/18 11:26 -    7,710 #######
2018/09/18 11:27 -    3,837 ###
2018/09/18 11:28 -    2,843 ##
2018/09/18 11:29 -    5,043 #####
2018/09/18 11:30 -    5,016 #####
2018/09/18 11:31 -    4,508 ####
2018/09/18 11:32 -    1,259 #
2018/09/18 11:33 -      442
2018/09/18 11:34 -      761
2018/09/18 11:35 -    1,400 #
2018/09/18 11:36 -      420
2018/09/18 11:37 -    5,976 #####
2018/09/18 11:38 -    2,235 ##
2018/09/18 11:39 -    3,580 ###
2018/09/18 11:40 -      312
2018/09/18 11:41 -    3,105 ###
2018/09/18 11:42 -  115,600 ###################################################################################################################
2018/09/18 11:43 -  100,822 ####################################################################################################
2018/09/18 11:44 -   54,977 ######################################################
2018/09/18 11:45 -   36,043 ####################################
2018/09/18 11:46 -   73,748 #########################################################################
2018/09/18 11:47 -   41,076 #########################################
2018/09/18 11:48 -   52,907 ####################################################
2018/09/18 11:49 -   26,560 ##########################
2018/09/18 11:50 -   56,875 ########################################################
2018/09/18 11:51 -   50,438 ##################################################
2018/09/18 11:52 -   62,290 ##############################################################
2018/09/18 11:53 -   46,729 ##############################################
2018/09/18 11:54 -   48,175 ################################################
2018/09/18 11:55 -   54,148 ######################################################
2018/09/18 11:56 -   37,661 #####################################
2018/09/18 11:57 -   46,013 ##############################################
2018/09/18 11:58 -   37,412 #####################################
2018/09/18 11:59 -   22,139 ######################

A single '#' is 1 thousand shares sold short. There was a volume spike at around 11:11, I believe this was possibly reaction to the price breaching $300.

(Shout-out to @lklundin)
 
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I got a phone call from my representative's office in response to my letter. Basically he said that since the press is covered by the 1st amendment, there was nothing he could do to help unless there was a civil action started against the WSJ. I am coming back around to the thought that maybe a bunch of high-net-worth investors might want to actually get together and sue. But IANAL... don't know if this is a realistic possibility or not. What do people think?
 
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I got a phone call from my representative's office in response to my letter. Basically he said that since the press is covered by the 1st amendment, there was nothing he could do to help unless there was a civil action started against the WSJ. I am coming back around to the thought that maybe a bunch of high-net-worth investors might want to actually get together and sue. But IANAL... don't know if this is a realistic possibility or not. What do people think?

May have already been filed if twitter users mean what they say?

Ben on Twitter
Elon´s World on Twitter
fiddler_on_the_roof on Twitter
 
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