DataLend increased its offering in the securities finance data business recently with the launch of the Target 50 index. Ben Glicher, product owner of DataLend, explains what this does.
GoPro, a maker of video camera equipment worn by cyclists, surfers and – since its June flotation – potentially many more people, has been the most in-demand US stock for borrowing purposes in recent months.
Short sellers have circled the stock as they question the company’s true value, though so far, the big short in GoPro has defied them and GoPro’s stock price has increased.
As of the end of November, there was around $400 million worth of GoPro stock available for lending and the utilisation rate was 98%, indicating it was heavily borrowed. Consequently, fees to borrow it were among the highest for any stock around the globe, meaning the stock provided lenders with an opportunity to make money.
“It is consistently the hottest stock in US lending,” says Ben Glicher, chief information officer at EquiLend, which owns DataLend, a securities finance data provider. Glicher is also product owner of DataLend.
The stock recently has ranked number one in DataLend’s Target 50 Securities Finance Index, which comprises the 50 most expensive equities to borrow in the US, UK, Europe and Asia.
To be included in the index, securities must have a minimum utilisation rate and a volume-weighted average fee or rebate rate. The index is rebalanced daily and acts as a benchmark to determine how securities that are most in demand in the finance market are trending over time.
Launched in October, the index is a recent development from DataLend, while DataLend itself has been active in the securities finance data sector since January 2013.
Customers of DataLend are participants in the securities finance market, such as prime brokers and custodians that run stock lending programmes. Also included are beneficial owners, the ultimate lenders of securities. Beneficial owners comprise a catchment that includes regulated mutual funds which, like pension funds, may use stock lending to increase a portfolio’s yield.
DataLend provides clients with a list of inventory of all available stocks – along with key metrics such as utilisation rates, fees to borrow and short interest, to name a few – covering more than 40,000 unique securities globally with an on-loan value of $1.8 trillion and inventory value of $13 trillion.
Among key features of DataLend are:
• Data Dashboard. This offers high-level metrics based on the previous business day’s trading activity.
• Security Search. This provides current and historical data for a specific security.
• DataTrack. This provides quick access to lists of securities and their on-loan metrics and information about the inventory.
• Research. A customisable tool allowing users to slice and dice information across the entire universe of securities in DataLend.
• Client Performance Reporting. This is a suite of tools for comparing beneficial owners’ securities lending performance against other beneficial owners with similar attributes.
The high volume of data needs to be cleansed. Glicher explains that this process essentially comes down to removing incorrect data that can lead to erroneous information.
Cleansing includes excluding duplicate records to avoid double counting. Also, potential outliers have to be removed so that they do not distort the data.
The collection of data is carried out on a “give-to-get” basis, meaning users must supply their own securities finance data to receive access to DataLend’s anonymised, aggregated data in return. Data is gathered from clients daily and, once cleansed, is available the following business day.
EquiLend is an industry-owned company formed in 2001. Its aim was to optimise efficiency in the securities finance industry by developing a standardised and centralised global platform for securities finance trading and post-trade services. Owners include BlackRock, Credit Suisse, Goldman Sachs, J.P. Morgan Clearing, J.P. Morgan, Bank of America Merrill Lynch, Morgan Stanley, Northern Trust, State Street and UBS.
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