Insider Sales at MKS Instruments (MKSI) are Significant and Extend the Selling Trend of Last Quarter

Wednesday, February 21, 2018 10:15 PM ET

Insider Sales at MKS Instruments (MKSI) are Significant and Extend the Selling Trend of Last Quarter

In SEC filings today MKS Instruments disclosed three insiders — Peter Hanley, Director, Seth H Bagshaw, Officer, and John Tseng-Chung Lee, Officer — disposed of 18,782 shares in the company having a market value of approximately $2,166,138. There have been 6 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 37,600 company shares. Adding the most recent activity to this 90-day history indicates insider trades have seen net sales of 56,382 shares and have averaged 6,265 shares per transaction over this time period.

The number of insider buy/sell trades at MKS Instruments is above that of the 28 peer company average over the last 90-day period. The Testing & Measuring Equipment peer group saw 15 buy/sell trades during this period for an average of 0.5 transactions per company. However, the number of shares traded per transaction by MKS Instruments insiders is lower than its peers. Within the peer group there were 160 shares purchased and 138,402 shares sold with company insiders disposing of 9,216 shares on average over this time period.

The data sourced in evaluating and writing in this story eliminates all trading activity reported to the SEC that involves awards, options, exercise of derivative securities, company buy-backs, taxes, gifts, shares acquired via inheritance and tenders or exchange offers.

Today’s Insider Activity
* Peter Hanley, Director, sold 350 shares
* Seth H Bagshaw, Officer, sold 5,000 shares
* John Tseng-Chung Lee, Officer, sold 13,432 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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