Monday, February 05, 2018 10:15 PM ET
Insiders Make Significant Stock Sales in Monolithic Power Systems (MPWR) Shares Extending the Trend of Last Quarter
A notable level of insider sales in Monolithic Power Systems was disclosed in form 4 documents filed with the SEC today. Four insiders — xiao, Hsing, Tseng, and Sciammas — disposed of 29,850 shares in the company having a market value of approximately $3,398,545. There have been 5 insiders with buy/sell transactions in the past 90 days prior to these filings. All of these trades have been sales resulting in the disposition of 97,585 company shares. Adding the most recent activity to this 90-day history indicates insider trades have seen net sales of 127,435 shares and have averaged 14,159 shares per transaction over this time period.
In relation to the peer group over the last 90 days, insider buy/sell trading at Monolithic Power Systems is greater than the 77-company peer group average. Semiconductors peer group saw 181 buy/sell trades during this period for an average of 2.4 transactions per company. The number of shares per buy/sell trade for Monolithic Power Systems insiders was also higher. Within the peer group there were 18,465 shares purchased and 2,123,153 shares sold with company insiders selling 11,628 shares on average.
In determining significant insider buying and selling, trades reported to the SEC that involve awards, options, exercise of derivative securities, company buy-backs, taxes, gifts, shares acquired via inheritance and tenders or exchange offers have been eliminated in data sourced to evaluate and write this story.
Today’s Insider Activity
* Deming Xiao, Officer, sold 4,382 shares
* Michael Hsing, Director and Officer, sold 17,354 shares
* Saria Tseng, Officer, sold 4,057 shares
* Maurice Sciammas, Officer, sold 4,057 shares
Using proprietary Natural Language Generation (NLG) technology, UpTick evaluates corporate insider filings reported to the SEC and creates real-time news and analysis to report the most significant insider transactions based on transaction type, size and historical trends.
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