PKI — PerkinElmer, Inc USA

HealthcareDiagnostics & Research

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Currency in USD
Key statistics
Basic
Not enough data for Risks (Volatility).
Not enough data for Beta calculations.
Market capital
$11.3B
Employees
13,000
Money
Not enough data for Earnings per share statistics.
Not enough data for Book Value calculations.
Wall Street price
$102.07
PE Ratio
48.29
Dividends
$0.28
Volume & Social
Short Ratio
13.14%
Daily Volume
853,800
Volume
Above average +
Social Rate
Untracked
Social Volume
Untracked
 
Latest PKI news
[[ item.source ]] - [[ item.pubDate | date:'MMM d, y @ h:mma' ]]
[[ item.description ]]
Invest ideas
6 ideas for buy
$0.28
Pays dividends
Fundamental signal
The company shares profit with stakeholders
0.74%
Wall Street Higher
Fundamental signal
The price is expected to raise
$2.10
Earnings are positive
Fundamental signal
Earnings per share are positive
67.46x
EPS higher than industry
Fundamental signal
Earnings Per Share Ratio is higher than industry average.
33.73x
EPS higher than sector
Fundamental signal
Earnings Per Share Ratio is higher than sector.
12.22%
Above SMA 200
Technical signal
The price is above SMA for 200 days period
6 ideas for sell
1.42x
PB Ratio higher than industry
Fundamental signal
Price-to-Book Ratio is higher than industry.
1.42x
PB Ratio higher than sector
Fundamental signal
Price-to-Book is higher than sector.
329.57%
Short Ratio higher than industry
Fundamental signal
Short Interest Ratio is higher than industry.
385.32%
Short Ratio higher than sector
Fundamental signal
Short Interest Ratio is higher than sector.
48.74%
Industry costly
Fundamental signal
PE Ratio is higher than industry.
192.61%
Sector costly
Fundamental signal
PE Ratio is higher than sector.
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Most and less correlated stocks. All correllations are calculated for 1 year period. Learn more about correlations.
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Correlation
100.00%
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99.60%
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Correlation
92.00%
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Correlation
91.70%
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Correlation
91.20%
UB Rating
Correlation
90.90%
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Correlation
90.60%
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Correlation
90.40%
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Correlation
90.30%
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Opposite (less correlated) stocks
Correlation
−100.00%
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Correlation
−90.30%
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Correlation
−82.80%
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Correlation
−81.80%
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Correlation
−79.20%
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Correlation
−78.90%
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Correlation
−78.80%
UB Rating
Correlation
−78.40%
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Correlation
−78.30%
UB Rating
Income Statement
All numbers in thousands [[fin.date | strtotimestamp | date: 'MMM d, yyyy']]
Revenue
Total Revenue [[fin.totalRevenue / 1000 | number : 0]]
Cost of Revenue [[fin.costOfRevenue / 1000 | number : 0]]
Gross Profit [[fin.grossProfit / 1000 | number : 0]]
Operating Expenses
Research Development [[fin.researchDevelopment / 1000 | number : 0]]
Selling General and Administrative [[fin.sellingGeneralAdministrative / 1000 | number : 0]]
Non Recurring [[fin.nonRecurring / 1000 | number : 0]]
Others [[fin.otherOperatingExpenses / 1000 | number : 0]]
Total Operating Expenses [[fin.totalOperatingExpenses / 1000 | number : 0]]
Operating Income or Loss [[fin.operatingIncome / 1000 | number : 0]]
Income from Continuing Operations
Total Other Income/Expenses Net [[fin.totalOtherIncomeExpenseNet / 1000 | number : 0]]
Earnings Before Interest and Taxes [[fin.ebit / 1000 | number : 0]]
Interest Expense [[fin.interestExpense / 1000 | number : 0]]
Income Before Tax [[fin.incomeBeforeTax / 1000 | number : 0]]
Income Tax Expense [[fin.incomeTaxExpense / 1000 | number : 0]]
Minority Interest [[fin.minorityInterest / 1000 | number : 0]]
Net Income From Continuing Ops [[fin.netIncomeFromContinuingOps / 1000 | number : 0]]
Non-recurring Events
Discontinued Operations [[fin.discontinuedOperations / 1000 | number : 0]]
Extraordinary Items [[fin.extraordinaryItems / 1000 | number : 0]]
Effect Of Accounting Changes [[fin.effectOfAccountingCharges / 1000 | number : 0]]
Other Items [[fin.otherItems / 1000 | number : 0]]
Net Income
Net Income [[fin.netIncome / 1000 | number : 0]]
Net Income Applicable To Common Shares [[fin.netIncomeApplicableToCommonShares / 1000 | number : 0]]
Balance Sheet
All numbers in thousands [[fin.date | strtotimestamp | date: 'MMM d, yyyy']]
Current Assets  
Cash And Cash Equivalents [[fin.cash / 1000 | number : 0]]
Short Term Investments [[fin.shortTermInvestments / 1000 | number : 0]]
Net Receivables [[fin.netReceivables/ 1000 | number : 0]]
Inventory [[fin.inventory/ 1000 | number : 0]]
Other Current Assets [[fin.otherCurrentAssets/ 1000 | number : 0]]
Total Current Assets [[fin.totalCurrentAssets / 1000 | number : 0]]
Long Term Investments [[fin.longTermInvestments / 1000 | number : 0]]
Property Plant and Equipment [[fin.propertyPlantEquipment / 1000 | number : 0]]
Goodwill [[fin.goodWill / 1000 | number : 0]]
Intangible Assets [[fin.intangibleAssets / 1000 | number : 0]]
Other Assets [[fin.otherAssets / 1000 | number : 0]]
Total Assets [[fin.totalAssets / 1000 | number : 0]]
Current Liabilities
Accounts Payable [[fin.accountsPayable / 1000 | number : 0]]
Short/Current Long Term Debt [[fin.shortLongTermDebt / 1000 | number : 0]]
Other Current Liabilities [[fin.otherCurrentLiab / 1000 | number : 0]]
Total Current Liabilities [[fin.totalCurrentLiabilities / 1000 | number : 0]]
Long Term Debt [[fin.longTermDebt / 1000 | number : 0]]
Other Liabilities [[fin.otherLiab / 1000 | number : 0]]
Deferred Long Term Liability Charges [[fin.deferredLongTermLiab / 1000 | number : 0]]
Total Liabilities [[fin.totalLiab / 1000 | number : 0]]
Stockholders' Equity
Common Stock [[fin.commonStock / 1000 | number : 0]]
Retained Earnings [[fin.retainedEarnings / 1000 | number : 0]]
Other Stockholder Equity [[fin.otherStockholderEquity / 1000 | number : 0]]
Total Stockholder Equity [[fin.totalStockholderEquity / 1000 | number : 0]]
Net Tangible Assets [[fin.netTangibleAssets / 1000 | number : 0]]
Cash Flow Statement
All numbers in thousands [[fin.date | strtotimestamp | date: 'MMM d, yyyy']]
Net Income [[fin.netIncome/ 1000 | number : 0]]
Operating Activities, Cash Flows Provided By or Used In
Depreciation [[fin.depreciation / 1000 | number : 0]]
Adjustments To Net Income [[fin.changeToNetincome / 1000 | number : 0]]
Changes In Accounts Receivables [[fin.changeToAccountReceivables / 1000 | number : 0]]
Changes In Liabilities [[fin.changeToLiabilities / 1000 | number : 0]]
Changes In Inventories [[fin.changeToInventory / 1000 | number : 0]]
Changes In Other Operating Activities [[fin.changeToOperatingActivities / 1000 | number : 0]]
Total Cash Flow From Operating Activities [[fin.totalCashFromOperatingActivities / 1000 | number : 0]]
Investing Activities, Cash Flows Provided By or Used In
Capital Expenditures [[fin.capitalExpenditures / 1000 | number : 0]]
Investments [[fin.investments / 1000 | number : 0]]
Other Cash flows from Investing Activities [[fin.otherCashflowsFromInvestingActivities / 1000 | number : 0]]
Total Cash Flows From Investing Activities [[fin.totalCashflowsFromInvestingActivities / 1000 | number : 0]]
Financing Activities, Cash Flows Provided By or Used In
Dividends Paid [[fin.dividendsPaid / 1000 | number : 0]]
Sale Purchase of Stock [[fin.salePurchaseOfStock / 1000 | number : 0]]
Net Borrowings [[fin.netBorrowings / 1000 | number : 0]]
Other Cash Flows from Financing Activities [[fin.otherCashflowsFromFinancingActivities / 1000 | number : 0]]
Total Cash Flows From Financing Activities [[fin.totalCashFromFinancingActivities / 1000 | number : 0]]
Change In Cash and Cash Equivalents [[fin.changeInCash / 1000 | number : 0]]
 

PerkinElmer, Inc. provides products, services, and solutions to the diagnostics, life sciences, and applied services markets worldwide. The company operates in two segments, Discovery & Analytical Solutions and Diagnostics. The Discovery & Analytical Solutions segment offers a suite of solutions, including reagents, informatics, and detection and imaging technologies that enable scientists to enhance research breakthroughs in the life sciences research market, as well as laboratory services. It also provides analytical technologies, solutions, and services for the environmental, food, and industrial markets that enable its customers to understand the characterization and health of various aspects, including air, water, and soil. In addition, this segment offers solutions to farmers and food producers; and analytical instrumentation for the industrial market, which includes the chemical, semiconductor and electronics, energy, lubricant, petrochemical, and polymer industries. The Diagnostics segment provides instruments, reagents, and software products for the early detection of genetic disorders, such as pregnancy and early childhood, as well as infectious disease testing in the diagnostics market. Its products are used for testing and screening genetic abnormalities, disorders, and diseases, including down syndrome, hypothyroidism, infertility, and various metabolic conditions. This segment also develops technologies that enable and support genomic workflows using protein coupled receptor and next-generation DNA sequencing for applications in oncology and drug discovery. The company serves pharmaceutical and biotechnology companies, laboratories, academic and research institutions, public health authorities, private healthcare organizations, doctors, and government agencies. PerkinElmer, Inc. was founded in 1937 and is headquartered in Waltham, Massachusetts.

Sector: Healthcare
Full Time Employees: 13,000
Avg
1.33 0.84 4.07 4.63
High
1.35 1.05 4.09 4.76
Low
1.32 0.76 4.06 4.46
Avg
801M 700M 2.88B 3.08B
High
807M 717M 2.91B 3.14B
Low
793M 683M 2.88B 3.02B
  [[fin.date | strtotimestamp | date: 'MMM d,yyyy']]
Earnings History
Earnings Actual [[fin.epsActual | number : 2]]
Earnings Estimate [[fin.epsEstimate | number : 2]]
Difference [[fin.epsDifference | number : 2]]
Surprise [[fin.surprisePercent | number : 1]]%
  Cur Qtr ([[financials['etrend']['0q'].date | strtotimestamp | date: 'MMM yyyy']]) Next Qtr ([[financials['etrend']['+1q'].date | strtotimestamp | date: 'MMM yyyy']]) Cur Year ([[financials['etrend']['0y'].date | strtotimestamp | date: 'MMM yyyy']]) Next Year ([[financials['etrend']['+1y'].date | strtotimestamp | date: 'MMM yyyy']])
Earnings Estimate
Number of Analysts [[financials['etrend']['0q'].earningsEstimateNumberOfAnalysts | number : 0]] [[financials['etrend']['+1q'].earningsEstimateNumberOfAnalysts | number : 0]] [[financials['etrend']['0y'].earningsEstimateNumberOfAnalysts | number : 0]] [[financials['etrend']['+1y'].earningsEstimateNumberOfAnalysts | number : 0]]
Estimate Average [[financials['etrend']['0q'].earningsEstimateAvg | number : 2]] [[financials['etrend']['+1q'].earningsEstimateAvg | number : 2]] [[financials['etrend']['0y'].earningsEstimateAvg | number : 2]] [[financials['etrend']['+1y'].earningsEstimateAvg | number : 2]]
Estimate High [[financials['etrend']['0q'].earningsEstimateHigh | number : 2]] [[financials['etrend']['+1q'].earningsEstimateHigh | number : 2]] [[financials['etrend']['0y'].earningsEstimateHigh | number : 2]] [[financials['etrend']['+1y'].earningsEstimateHigh | number : 2]]
Estimate Low [[financials['etrend']['0q'].earningsEstimateLow | number : 2]] [[financials['etrend']['0q'].earningsEstimateLow | number : 2]] [[financials['etrend']['0y'].earningsEstimateLow | number : 2]] [[financials['etrend']['+1y'].earningsEstimateLow | number : 2]]
Estimate Growth [[financials['etrend']['0q'].earningsEstimateGrowth | number : 2]] [[financials['etrend']['+1q'].earningsEstimateGrowth | number : 2]] [[financials['etrend']['0y'].earningsEstimateGrowth | number : 2]] [[financials['etrend']['+1y'].earningsEstimateGrowth | number : 2]]
Year Ago EPS [[financials['etrend']['0q'].earningsEstimateYearAgoEps | number : 2]] [[financials['etrend']['+1q'].earningsEstimateYearAgoEps | number : 2]] [[financials['etrend']['0y'].earningsEstimateYearAgoEps | number : 2]] [[financials['etrend']['+1y'].earningsEstimateYearAgoEps | number : 2]]
All numbers in thousands (except analysts) Cur Qtr ([[financials['etrend']['0q'].date | strtotimestamp | date: 'MMM yyyy']]) Next Qtr ([[financials['etrend']['+1q'].date | strtotimestamp | date: 'MMM yyyy']]) Cur Year ([[financials['etrend']['0y'].date | strtotimestamp | date: 'MMM yyyy']]) Next Year ([[financials['etrend']['+1y'].date | strtotimestamp | date: 'MMM yyyy']])
Revenue Estimate
Number of Analysts [[financials['etrend']['0q'].revenueEstimateNumberOfAnalysts | number : 0]] [[financials['etrend']['+1q'].revenueEstimateNumberOfAnalysts | number : 0]] [[financials['etrend']['0y'].revenueEstimateNumberOfAnalysts | number : 0]] [[financials['etrend']['+1y'].revenueEstimateNumberOfAnalysts | number : 0]]
Estimate Average [[financials['etrend']['0q'].revenueEstimateAvg / 1000 | number : 0]] [[financials['etrend']['+1q'].revenueEstimateAvg / 1000 | number : 0]] [[financials['etrend']['0y'].revenueEstimateAvg / 1000 | number : 0]] [[financials['etrend']['+1y'].revenueEstimateAvg / 1000 | number : 0]]
Estimate High [[financials['etrend']['0q'].revenueEstimateHigh / 1000 | number : 0]] [[financials['etrend']['+1q'].revenueEstimateHigh / 1000 | number : 0]] [[financials['etrend']['0y'].revenueEstimateHigh / 1000 | number : 0]] [[financials['etrend']['+1y'].revenueEstimateHigh / 1000 | number : 0]]
Estimate Low [[financials['etrend']['0q'].revenueEstimateLow / 1000 | number : 0]] [[financials['etrend']['0q'].revenueEstimateLow / 1000 | number : 0]] [[financials['etrend']['0y'].revenueEstimateLow / 1000 | number : 0]] [[financials['etrend']['+1y'].revenueEstimateLow / 1000 | number : 0]]
Estimate Growth [[financials['etrend']['0q'].revenueEstimateGrowth * 100 | number : 2]]% [[financials['etrend']['+1q'].revenueEstimateGrowth * 100 | number : 2]]% [[financials['etrend']['0y'].revenueEstimateGrowth * 100 | number : 2]]% [[financials['etrend']['+1y'].revenueEstimateGrowth * 100| number : 2]]%
Year Ago EPS [[financials['etrend']['0q'].revenueEstimateYearAgoEps | number : 0]] [[financials['etrend']['+1q'].revenueEstimateYearAgoEps | number : 0]] [[financials['etrend']['0y'].revenueEstimateYearAgoEps | number : 0]] [[financials['etrend']['+1y'].revenueEstimateYearAgoEps | number : 0]]
Cur Qtr ([[financials['etrend']['0q'].date | strtotimestamp | date: 'MMM yyyy']]) Next Qtr ([[financials['etrend']['+1q'].date | strtotimestamp | date: 'MMM yyyy']]) Cur Year ([[financials['etrend']['0y'].date | strtotimestamp | date: 'MMM yyyy']]) Next Year ([[financials['etrend']['+1y'].date | strtotimestamp | date: 'MMM yyyy']])
EPS Trend
Current Estimate [[financials['etrend']['0q'].epsTrendCurrent | number : 2]] [[financials['etrend']['+1q'].epsTrendCurrent | number : 2]] [[financials['etrend']['0y'].epsTrendCurrent | number : 2]] [[financials['etrend']['+1y'].epsTrendCurrent | number : 2]]
7 Days Ago [[financials['etrend']['0q'].epsTrend7daysAgo | number : 2]] [[financials['etrend']['+1q'].epsTrend7daysAgo | number : 2]] [[financials['etrend']['0y'].epsTrend7daysAgo| number : 2]] [[financials['etrend']['+1y'].epsTrend7daysAgo | number : 2]]
30 Days Ago [[financials['etrend']['0q'].epsTrend30daysAgo | number : 2]] [[financials['etrend']['+1q'].epsTrend30daysAgo | number : 2]] [[financials['etrend']['0y'].epsTrend30daysAgo | number : 2]] [[financials['etrend']['+1y'].epsTrend30daysAgo | number : 2]]
60 Days Ago [[financials['etrend']['0q'].epsTrend60daysAgo | number : 2]] [[financials['etrend']['+1q'].epsTrend60daysAgo | number : 2]] [[financials['etrend']['0y'].epsTrend60daysAgo | number : 2]] [[financials['etrend']['+1y'].epsTrend60daysAgo | number : 2]]
90 Days Ago [[financials['etrend']['0q'].epsTrend90daysAgo | number : 2]] [[financials['etrend']['+1q'].epsTrend90daysAgo | number : 2]] [[financials['etrend']['0y'].epsTrend90daysAgo | number : 2]] [[financials['etrend']['+1y'].epsTrend90daysAgo | number : 2]]
Cur Qtr ([[financials['etrend']['0q'].date | strtotimestamp | date: 'MMM yyyy']]) Next Qtr ([[financials['etrend']['+1q'].date | strtotimestamp | date: 'MMM yyyy']]) Cur Year ([[financials['etrend']['0y'].date | strtotimestamp | date: 'MMM yyyy']]) Next Year ([[financials['etrend']['+1y'].date | strtotimestamp | date: 'MMM yyyy']])
EPS Revisions
Up Last 7 Days [[financials['etrend']['0q'].epsRevisionsUpLast7days | number : 0]] [[financials['etrend']['+1q'].epsRevisionsUpLast7days | number : 0]] [[financials['etrend']['0y'].epsRevisionsUpLast7days | number : 0]] [[financials['etrend']['+1y'].epsRevisionsUpLast7days | number : 0]]
Up Last 30 Days [[financials['etrend']['0q'].epsRevisionsUpLast30days | number : 0]] [[financials['etrend']['+1q'].epsRevisionsUpLast30days | number : 0]] [[financials['etrend']['0y'].epsRevisionsUpLast30days| number : 0]] [[financials['etrend']['+1y'].epsRevisionsUpLast30days | number : 0]]
Down Last 30 Days [[financials['etrend']['0q'].epsRevisionsDownLast30days | number : 0]] [[financials['etrend']['+1q'].epsRevisionsDownLast30days | number : 0]] [[financials['etrend']['0y'].epsRevisionsDownLast30days | number : 0]] [[financials['etrend']['+1y'].epsRevisionsDownLast30days | number : 0]]
Down Last 90 Days [[financials['etrend']['0q'].epsRevisionsDownLast90days | number : 0]] [[financials['etrend']['+1q'].epsRevisionsDownLast90days | number : 0]] [[financials['etrend']['0y'].epsRevisionsDownLast90days | number : 0]] [[financials['etrend']['+1y'].epsRevisionsDownLast90days | number : 0]]
 
Date Open High Low Close Volume
[[data.Date]] [[data.Open | number : 2]] [[data.High | number : 2]] [[data.Low | number : 2]] [[data.Close | number : 2]] [[data.Volume | number : 0]]