Splunk Sees Unusually-High Trading Volume on Earnings Beat (SPLK)
Shares of Splunk (NASDAQ:SPLK) saw strong trading volume on Friday after the company announced better than expected quarterly earnings, American Banking & Market News reports. 15,456,914 shares changed hands during trading, an increase of 451% from the previous session’s volume of 2,805,094 shares.The stock last traded at $53.85 and had previously closed at $45.29.
The company reported $0.01 earnings per share for the quarter, beating the analysts’ consensus estimate of ($0.02) by $0.03. The company had revenue of $101.50 million for the quarter, compared to the consensus estimate of $93.93 million. During the same quarter in the previous year, the company posted ($0.01) earnings per share. The company’s revenue for the quarter was up 51.7% on a year-over-year basis.
A number of research firms have recently commented on SPLK. Analysts at Barclays reiterated an “equal weight” rating on shares of Splunk in a research note on Friday. They now have a $52.00 price target on the stock, up previously from $51.00. Separately, analysts at Deutsche Bank reiterated a “buy” rating on shares of Splunk in a research note on Friday. They now have a $56.00 price target on the stock, up previously from $55.00. Finally, analysts at Goldman Sachs reiterated a “neutral” rating on shares of Splunk in a research note on Friday. Ten analysts have rated the stock with a hold rating and sixteen have issued a buy rating to the stock. The stock currently has an average rating of “Buy” and an average price target of $71.69.
The stock’s 50-day moving average is $45.09 and its 200-day moving average is $58.84. The company’s market cap is $6.381 billion. Splunk also was the recipient of unusually large options trading on Thursday. Investors bought 10,430 call options on the company. This represents an increase of 369% compared to the typical volume of 2,224 call options.
Splunk Inc provides software products. The Company’s products enable users to collect, index, and search, explore, monitor and analyze data regardless of format or source.
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