How to Analyze Short Selling Data

Short selling data can provide invaluable market insights for investors. As a general rule, short sellers are sophisticated, high-conviction traders that do their research. If they are betting against a stock by taking a short position, there’s usually a reason they are doing so.

In this guide, we are going to look at how to analyze short selling data. By understanding how to interpret this niche form of data – which is rich with institutional sentiment information – active investors can potentially make more informed trading decisions.

Short Interest

When analyzing short selling data on a stock, the first thing to do is to look at the stock’s short interest. Short interest is the number of shares that have been sold short divided by the total number of shares outstanding, expressed as a percentage. For example, if a stock has 10 million shares outstanding and two million of these shares have been sold short, the stock’s short interest is 20%.

Short interest is essentially an indicator of market sentiment. If a stock’s short interest is high, it’s generally a bearish signal. Typically, a high level of short interest indicates that many institutions are betting against the stock because they expect it to fall in value.

A stock’s short interest is important to consider because studies have found that stocks with high levels of short interest tend to underperform. For example, a 2008 study entitled ‘Which Shorts are Informed?’ by Boehmer, Jones, and Zhang showed that heavily-shorted stocks underperformed lightly-shorted stocks by a risk‐adjusted average of 1.16% over the following 20 trading days (15.6% annualized).

In terms of what is considered a ‘high’ short interest ratio, a reading of 10% and higher is generally considered quite high (i.e. a red flag). However, there are a few variables to consider, including the market the stock is in and the type of stock it is. For example, in the US, it’s relatively common for stocks to have short interest of 10% or higher. However, in the UK, you don’t often see stocks with short interest of 10%+. Meanwhile, in the US, it’s not unusual to see a speculative small-cap growth stock with short interest of 10% or higher. However, you don’t often see a well-established, US large-cap company with short interest of 10%+.

So ultimately, when examining a stock’s short interest, it’s a good idea to analyze it on a relative basis. Compare the stock’s short interest to the short interest of other stocks in the same market as well as other stocks in the same industry.

It’s also a good idea to monitor changes in short interest. A sudden large increase or decrease in a stock's short interest can provide valuable insights into sentiment towards the stock. A large sudden increase in short interest is generally a bearish signal as it tells you that short sellers are ramping up their bets on the stock. By contrast, a large sudden decrease in short interest can be a sign that the outlook for the stock is improving.

It’s important to understand that short interest data published by regulators such as the Financial Industry Regulatory Authority (FINRA) and the UK’s Financial Conduct Authority (FCA) is often not very accurate. In FINRA’s case, it only requires firms to report short interest positions twice a month. So, the data can be out of date. Meanwhile, the FCA’s data is based on short positions that are over 0.5% of the issuer’s share capital. So, it doesn’t include smaller short positions.

Therefore, it’s worth analyzing multiple sources of short interest data to get a more complete view of a stock’s true short interest. It’s worth noting that the short interest data on 2iQ’s terminal is gathered from different investment banks and passive investors that have lent out stock to short sellers. This data can provide a more complete view of a stock’s short interest.


Another metric to focus on when analyzing short selling data on a stock is its utilization rate. Utilization is the number of loaned shares divided by the available shares in the securities lending market, expressed as a percentage. Essentially, it is a measure of demand for shares from short sellers. A high utilization rate can be a red flag because it tells you that demand for the stock from short sellers is elevated.

Like short interest, utilization should be analyzed on a relative basis. A large-cap stock that is very liquid, such as Apple, may have a very low utilization of less than 1% because the stock has vast availability relative to the demand to borrow shares from short sellers. By contrast, a more illiquid stock, such as Skillz, might have a very high utilization of 90% because of high demand from short sellers relative to the number of available shares.

Utilization should also be monitored over time. That way, trends related to demand on the short side can be analyzed. If a stock’s utilization is rising rapidly, it is generally a bearish signal.

Cost to Borrow

A third short selling metric to examine is the cost to borrow stock. To short a stock, short sellers have to borrow the stock and pay a loan fee. These borrowing costs can provide insight into the demand for the stock on the short side. If costs to borrow are high, it signals that demand from short sellers for the stock is elevated. This is generally a bearish signal.

It’s worth noting that costs to borrow vary across regions and segments of the market. Generally speaking, costs to borrow are lower for developed market stocks. Large-cap stocks also typically have lower costs to borrow than small-cap stocks. So, once again, this metric should be examined on a relative basis.

One example of a stock that has had high costs to borrow recently is electric vehicle manufacturer Lordstown Motors. As of 28 May 2021, its costs to borrow were a high 31.84%. By contrast, Apple’s costs to borrow on the same date were just 0.27%.

Borrowing Activity Rating (BAR)

2iQ’s short selling data also includes a ‘Borrowing Activity Rating’ (BAR). This is a rating between one and 10 that provides a simple indication of the level of demand to borrow a given stock. A rating of one indicates a relatively low demand to short the stock whereas a rating of 10 indicates a relatively high demand. The formula to calculate the BAR includes inputs from outstanding loan fees, new loan fees, new loan volume, and utilization rates.

Days-to-Cover Ratio

Finally, the loan days-to-cover ratio is also worth analyzing when examining short selling data on a stock. This indicates approximately how many days it would take short sellers to cover their existing positions. It is calculated by taking the number of shares that are being shorted and dividing this by the average daily trading volume. For example, if one million shares of a stock are being shorted, and its average daily trading volume is 200,000 shares, the days-to-cover ratio is five.

A high days-to-cover ratio tells you that it will take short sellers a long time to unwind their positions if the price of the stock suddenly rises. In other words, there could be a significant short squeeze. By contrast, a low days-to-cover ratio tells you that short sellers could easily and quickly cover their positions if the price of the security was to suddenly rise. Generally speaking, a days-to-cover ratio of 10 or higher is considered high.

Short Selling Data: A Powerful Tool for Investors

In conclusion, short selling data can add a lot of value for active investors, particularly from a risk management perspective. By analyzing metrics such as short interest, utilization rate, days to cover, and borrowing costs, investors can get a better picture of institutional sentiment towards a stock and potentially make more informed trading decisions.

Of course, while short selling data can be a powerful tool, it should not be the sole determinant of an investment decision. A stock can maintain a high level of activity on the short side for a long period of time without a major price decline or short squeeze. As with most forms of alternative financial data, short selling data is best used in conjunction with other data as part of an investor’s overall analysis.

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