Stock Price Trends

UniFirst Corporation (UNF)

unifirst corporation (nyse: unf), headquartered in wilmington, mass., is a north american leader in the supply and servicing of managed uniform and workwear programs, as well as in the delivery of ancillary facility services. together with its subsidiaries, the company also provides first aid and safety products, and manages specialized workwear programs for the cleanroom and nuclear industries. unifirst manufactures its own branded work clothing, protective garments, and floorcare products; maintains 250 locations coast-to-coast; serves more than 300,000 business customers; and employs 14,000 employee team partners. the company outfits nearly 2 million workers each business day through its managed rental, lease, and purchase programs. unifirst's corporate mission is to be recognized as the leading provider of quality uniform products and services. our continuous customer focus enables us to grow, to provide an equitable return on investment, and to create development opportunities for

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 20.60% per annum.
  • UNF price at the close of February 16, 2024 was $169.48 and was higher than the top border of the primary price channel by $37.69 (28.60%). This indicates a possible reversal in the primary trend direction.
  • The secondary trend is decreasing.
  • The decline rate of the secondary trend is 10.04% per annum.
  • UNF price at the close of February 16, 2024 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 UNF 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
=

Price channel spread:

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

December 16, 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()
= $

July 18, 2022 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()
= $

Description

  • The primary trend is decreasing.
  • The decline rate of the primary trend is 20.60% per annum.
  • UNF price at the close of February 16, 2024 was $169.48 and was higher than the top border of the primary price channel by $37.69 (28.60%). This indicates a possible reversal in the primary trend direction.

Secondary Trend

Start date:
End date:

a =

b =

s =

Annual growth rate:

Exp(365 × b) – 1
= Exp(365 × ) – 1
=

Price channel spread:

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

December 16, 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()
= $

February 16, 2024 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()
= $

Description

  • The secondary trend is decreasing.
  • The decline rate of the secondary trend is 10.04% per annum.
  • UNF price at the close of February 16, 2024 was inside the secondary price channel.