# Tractor Supply Company (TSCO)

don’t let our name fool you. sure, we may know a thing or two about tractors. but at tractor supply company, it’s far from our only specialty. our loyal customers come to us for expertise, advice, and thousands of products every day—from lawn and animal care products to equipment, and even clothing. it’s helped make us an important part of the communities we serve, and one of the nation’s fastest growing retail organizations. we proudly celebrate over 75 years years of service. founded in 1938 by charles e. schmidt, sr. as a mail order tractor parts business, today tractor supply is the largest operator of retail farm stores in america. our stores are located in rural communities and in the outlying areas of large cities—“out here”—where people feel a deep connection with their land. our customers are as diverse as the products we carry: from farmers and ranchers to pet owners and hobbyists, construction and trades people, and suburban landowners. no matter what they’re looking for,

## Stock Price Trends

Stock price trends estimated using linear regression.

## Paying users area

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Unhide data and trends.

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#### Key facts

• The primary trend is increasing.
• The growth rate of the primary trend is 1.37% per annum.
• TSCO price at the close of December 8, 2023 was \$212.07 and was inside the primary price channel.
• The secondary trend is decreasing.
• The decline rate of the secondary trend is 20.13% per annum.
• TSCO 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 TSCO 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
=

#### August 11, 2021 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
=

#### February 6, 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()
= \$