# Stericycle, Inc. (SRCL)

stericycle is a global services company. we provide highly specialized solutions serving healthcare organizations and commercial businesses of every size and shape. throughout the last 25 years, we have grown from a small start-up in medical waste management into a leader across a range of increasingly complex and highly regulated arenas, such as: • brand protection solutions • environmental & sustainable solutions • patient & customer communication solutions • regulated waste management & compliance solutions from the start we have challenged the status quo of what a business solution can be. by identifying unmet needs, we have redefined and transformed multiple industries from a narrowly defined service category to a robust suite of solutions that customers need and want. our success with this strategy has landed stericycle among the fortune 1000 list and forbes 25 most innovative companies. a publicly-traded company with \$2.5 billion in 2014 revenue, our core purpose is to

## 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 18.67% per annum.
• SRCL price at the close of December 8, 2023 was \$48.45 and was higher than the top border of the primary price channel by \$1.41 (3.00%). This indicates a possible reversal in the primary trend direction.
• The secondary trend is increasing.
• The growth rate of the secondary trend is 475.82% per annum.
• SRCL price at the close of December 8, 2023 was inside the secondary price channel.
• The direction of the secondary trend is opposite to the direction of the primary trend. This indicates a possible reversal in the direction of the primary trend.

### 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 SRCL 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
=

#### November 5, 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()
= \$

#### November 14, 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
=

#### October 24, 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()
= \$