Tuesday, 15 January 2019

Latest Updates

Here at Sharadar HQ we are pretty obsessed with expanding our datasets and making them increasingly valuable to our customers. A downside of the singular focus on expanding our datasets is that we are not particularly good at taking the time to tell our customers about these improvements.

This post is an effort to remedy this situation. We'll list recent updates to the datasets, and we'll keep adding to this same post for future updates. We have many future updates in the pipeline, so you can keep checking back here. At some point we'll also backfill the full history of updates, because we're sticklers for completeness.

This post can be read in conjunction with our progress post which charts the high-level long term trend in our expansion efforts.

Latest updates:

15 January 2019 - Added current & historical S&P500 constituents as a free update for our fundamentals customers (here).

15 January 2019 - Added corporate actions as a free update for our fundamentals and equity prices customers (here, here, here and here). Focused initially on stock splits and expanding in the future to cover a broader array of corporate actions.

5 January 2019 - Passed the 20,000 ticker milestone for coverage in our equity and fund prices offering (here).

26 December 2018 - Added Exchange Traded Debt (ETD) as a free update for our fund price customers (here and here).

2 November 2018 - Added daily resolution of price-based metrics as a free update for our fundamentals customers (here and here).

14 October 2018 - Added preferred stock and stock warrants to coverage as a free update for our equity prices customers (here, and here).

7 June 2018 - Passed the 15,000 ticker milestone for coverage in our equity and fund prices offering (here).

7 June 2018 - Launched our EOD fund price offering (here, and bundled with equity prices here). Focused initially on ETFs, CEFs and ETNs and subsequently expanded to include Exchange Traded Debt (ETD).

24 April 2018 - Added indicator (field) descriptions that are retrievable via API as a free update for our fundamentals, insiders, institutional holdings, equity prices and the bundle customers.

24 April 2018 - Added rich ticker/company meta data that is retrievable via API as a free update for fundamentals, equity prices and the bundle

- Vincent

Wednesday, 28 November 2018


Another excellent investor tool joins the ranks - Koyfin

I've learnt a lot from using it, and recommend that you check it out too.

- Vincent

[Disclosure: uses Sharadar data]

Wednesday, 24 October 2018


Udacity has launched a new nanodegree program focused on artificial intelligence for trading.
It uses Sharadar data for part of the curriculum and so of course I think the course is great. But in this case it is actually true. It has been a pleasure to deal with Udacity throughout. It was also kinda cool since Udacity played a big part in me personally upskilling from an advanced spreadsheet jockey to computer programmer all those years ago. I still recommend their free CS 101 course as the best way to get started.

- Vincent

Tuesday, 2 October 2018

The Street Is Probably Not As Short On Tesla As You Think

It's common knowledge that Tesla is among the most shortest stocks around. Jockeying for the top spot with the likes of Amazon and Apple, companies with 20x the market cap. Each price fluctuation spawns countless headlines and as many forgettable articles about the "billions" that have been made or lost in short span by those betting against the company.

There are a few problems with this.

The underlying Nasdaq published short interest data evidently looks at the "total" short position and ignores any long position that the short seller might simultaneously hold in Tesla stock. i.e. these are gross short positions rather than net. And then we don't get to see who are the actual holders of the short positions. Instead we are subjected to the media musings of a cast of self-identified short sellers whose portfolio sizes range from tiny to small, and who as such cannot possibly account for a material portion of the money that we are told is short Tesla.

Fortunately, due to the varying mechanics of establishing a short position there is another data source that offers us more visibility - institutional holdings data which is disclosed to the SEC via form 13F and which allows us to look at individual investor holdings of stock, call options and put options. Peaking behind the curtain at such data we find that the top put holder also happens to be the top call holder. The same is true of the number 2 put holder. This is a surprising result with potential implications for everything that is written about short selling of Tesla.

But first let's quickly motivate why the SEC institutional holdings data can be used as a complement or substitute to the Nasdaq short interest data. There are two main mechanisms for going short a stock: (1) by borrowing and short selling directly (represented by Nasdaq data); or, (2) by buying put options (represented by SEC data). For more detailed explanations of these mechanisms see here. Many of the Tesla short sellers identified on television or in the pages of Seeking Alpha are the holders of put options.

Importantly, buying put options and direct short selling are not unrelated since the counterparty to a purchase of put options may offset their exposure by themselves establishing a direct short position. Therefore, to the extent that a short position is established via put options, and the counterparty offsets their exposure through a direct short position we should expect their to be overlap between the Nasdaq short interest data and the SEC put data.
The question is therefore, in the case of Tesla how much overlap is there between the Nasdaq short interest data and the SEC put data?

It's not a question that can be answered definitively since the Nasdaq data are completely opaque. However, viewing the long term trends in each source does allow us to make an educated guess.

To the extent the above trends are aligned the data sources are likely to overlap each other. Clearly there are periods of difference, which may themselves be instructive, but the sources are of the same magnitude and trend with a tendency to converge and intersect. The sources are more alike than they are different and this is unlikely to be accidental.

If we accept that the SEC put data are similar enough to be used as a proxy for the Nasdaq short interest data we can derive the "net" short position, as above, after adjusting for long positions held by put holders. This net short position is drastically reduced and, on numerous occasions, negative.

This suggests that not only are short positions and their reported wins and losses greatly exaggerated in the countless articles on this subject, but they may even be directionally incorrect at times!

Last, there remains the curious question of why the largest short position (put holder) would also be the largest call holder?
The firm in question, Susquehanna International Group ("SIG"), is a quant focused shop with $291 billion of reportable holdings at the end of June. Not quite the same scale as Tesla institutional longs such as Fidelity and T Rowe Price, but a lot closer than any of our media musing short sellers. $4.5 billion of this is short Tesla via put options, $2.7 billion is long via call options, and nominal amounts of Tesla stock and debt are held too. SIG's net position has varied over the years and has been net long on occasion. Interestingly, SIG is also the largest put and call holder in Apple, Amazon, Google, Netflix and Facebook (and even QQQ) - suggesting that the overall short positions of these stocks are also likely to be greatly exaggerated.

We don't get to see the durations and strike prices of SIG's options. Nor do we get to see the details of any call or put options that SIG has written. But at an aggregate level from what we do see it appears that SIG has most recently been betting on price declines *or* volatility. Bets which would probably have rewarded in recent days:
Some quick housekeeping before I go. (1) I am personally long Tesla stock, and have been accumulating shares since prior to the Model S release; and, (2) the SEC data used in this article can be found here.

- Vincent

Monday, 30 July 2018


We love seeing things being built around our datasets. One of the cool things we've seen recently is a module to ingest our data for use with Zipline. Zipline is an open source algorithmic trading library that can be used for backtesting strategies. My thanks to Peter for putting this together and publishing it.

- Vincent

Tuesday, 3 July 2018


Since launching our flagship fundamentals product in late 2014 we've worked continuously to expand it on three core dimensions: ticker coverage, length of history and depth of detail. The dataset has already grown by many multiples over this time and we continue to chart a similar trajectory moving forward. Here we track our progress in this regard, and forecast future growth. The figures presented here will update periodically in the future.

In addition to expanding our fundamentals product we have launched numerous additional products since 2014, each of which are expanding along similar dimensions and trajectories: Institutional Holdings (2016), Insider Holdings & Transactions (2016), EOD Stock Prices (2017), and EOD Fund Prices (2018). We have many more products in the pipeline, and can't wait to show you more.

- Vincent

Friday, 29 June 2018


These days there are some great stock tools being made accessible online, and we want to shine a light on them.

Tiingo is one such site that has been built with the mission of empowering the individual by putting good information and tools in their hands. It also has a great, growing community around it, fostered by its creator Rishi.

- Vincent