# Cognex Corporation (CGNX)

cognex corporation designs, develops, manufactures and markets a range of products that incorporate sophisticated machine vision technology that gives them the ability to "see."​ cognex products include barcode readers, machine vision sensors and machine vision systems that are used in factories, warehouses and distribution centers around the world to guide, gauge, inspect, identify and assure the quality of items during the manufacturing and distribution process. cognex is the world's leader in the machine vision industry, having shipped more than 900,000 vision-based products, representing over \$3.5 billion in cumulative revenue, since the company's founding in 1981. headquartered in natick, massachusetts, usa, cognex has regional offices and distributors located throughout north america, japan, europe, asia and latin america. for details visit cognex online at http://www.cognex.com.

## Stock Price Trends

Stock price trends estimated using linear regression.

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#### Key facts

• The primary trend is decreasing.
• The decline rate of the primary trend is 24.65% per annum.
• CGNX price at the close of December 8, 2023 was \$38.07 and was inside the primary price channel.
• The secondary trend is decreasing.
• The decline rate of the secondary trend is 65.64% per annum.
• CGNX price at the close of December 8, 2023 was inside the secondary price channel.

### Linear Regression Model

Model equation:
Yi = α + β × Xi + εi

Top border of price channel:
Exp(Yi) = Exp(a + b × Xi + 2 × s)

Bottom border of price channel:
Exp(Yi) = Exp(a + b × Xi – 2 × s)

where:

i - observation number
Yi - natural logarithm of CGNX price
Xi - time index, 1 day interval
σ - standard deviation of εi
a - estimator of α
b - estimator of β
s - estimator of σ
Exp() - calculates the exponent of e

### Primary Trend

Start date:
End date:

a =

b =

s =

Annual growth rate:

Exp(365 × b) – 1
= Exp(365 × ) – 1
=

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

#### December 14, 2020 calculations

Top border of price channel:

Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= \$

Bottom border of price channel:

Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= \$

#### December 8, 2023 calculations

Top border of price channel:

Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= \$

Bottom border of price channel:

Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= \$

### Secondary Trend

Start date:
End date:

a =

b =

s =

Annual growth rate:

Exp(365 × b) – 1
= Exp(365 × ) – 1
=

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

#### June 2, 2023 calculations

Top border of price channel:

Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= \$

Bottom border of price channel:

Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= \$

#### December 8, 2023 calculations

Top border of price channel:

Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= \$

Bottom border of price channel:

Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= \$