# O'Reilly Automotive, Inc. (ORLY)

it started with two men - c.f. and chub o’reilly. together they had the courage and the confidence to strike out on their own. they gathered together 11 others who shared the same desire to offer great customer service and auto parts availability and opened the doors of o’reilly automotive, inc. on december 2, 1957. now, more than 57 years later, the more than 68,000 team members at o’reilly auto parts are proud of the growth and success we’ve experienced over the years. during our early years, we focused on sales and slow and steady growth. at the end of our first year, sales totaled \$700,000, and by 1961 these sales reached \$1.3 million. for the first seven years of operation, our first store in springfield, mo was our only store until the second one opened in july 1965.by march of 1975, we had nine stores, annual sales of \$7 million, and opened our new 48,000 square-foot warehouse, also in springfield. the long range plans and stability of the company were solidified by a publ

## Stock Price Trends

Stock price trends estimated using linear regression.

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#### Key facts

• The primary trend is increasing.
• The growth rate of the primary trend is 37.67% per annum.
• ORLY price at the close of March 1, 2024 was \$1,085.45 and was lower than the bottom border of the primary price channel by \$70.06 (6.06%). This indicates a possible reversal in the primary trend direction.
• The secondary trend is increasing.
• The growth rate of the secondary trend is 28.12% per annum.
• ORLY price at the close of March 1, 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 ORLY 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
=

#### February 7, 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()
= \$

#### April 27, 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 increasing.
• The growth rate of the primary trend is 37.67% per annum.
• ORLY price at the close of March 1, 2024 was \$1,085.45 and was lower than the bottom border of the primary price channel by \$70.06 (6.06%). 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
=

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

#### May 4, 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()
= \$

#### March 1, 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 increasing.
• The growth rate of the secondary trend is 28.12% per annum.
• ORLY price at the close of March 1, 2024 was inside the secondary price channel.