# Dollar Tree, Inc. (DLTR)

at dollar tree, it’s really all about the thrill of the hunt. as a fortune 150 company and the nation’s leading operator of single-price-point dollar stores, we operate more than 6,000 stores and 11 distribution centers across 48 contiguous u.s. states and five canadian provinces. we hunt the world over to find the most exciting merchandise for our customers, who are always telling us that they can’t believe the cool items they find in our stores for just $1.00. from party supplies and home décor to health & beauty, seasonal items, food & snacks, and so much more, we offer a huge selection — everything you need and want for every day, every holiday, and every occasion... and every single item is only $1 (or less)! we are experts in creative ideas and sound business management. for over 28 years, our price, philosophy, and mission have not changed, yet we are constantly adapting to an ever-changing marketplace with innovative and creative ideas. we understand the value of a dollar, plus

## 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 14.38% per annum.
- DLTR price at the close of February 16, 2024 was $143.37 and was inside the primary price channel.
- The secondary trend is increasing.
- The growth rate of the secondary trend is 127.24% per annum.
- DLTR price at the close of February 16, 2024 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:

Y_{i} = α + β × X_{i} + ε_{i}

Top border of price channel:

Exp(Y_{i}) = Exp(a + b × X_{i} + 2 × s)

Bottom border of price channel:

Exp(Y_{i}) = Exp(a + b × X_{i} – 2 × s)

where:

i - observation number

Y_{i} - natural logarithm of DLTR price

X_{i} - time index, 1 day interval

σ - standard deviation of ε_{i}

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

=

#### March 14, 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()

= $

#### February 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 primary trend is decreasing.
- The decline rate of the primary trend is 14.38% per annum.
- DLTR price at the close of February 16, 2024 was $143.37 and was inside the primary price channel.

### 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

=

#### September 21, 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()

= $

#### 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 increasing.
- The growth rate of the secondary trend is 127.24% per annum.
- DLTR price at the close of February 16, 2024 was inside the secondary price channel.