# Horace Mann Educators Corporation (HMN)

horace mann was founded in 1945 by two educators in springfield, ill., who believed teachers deserved affordable auto insurance. originally called the illinois education association mutual insurance company, our name was changed to honor the father of the american public education system, horace mann. we are proud to share his name. at horace mann, the hard work, commitment and dedication of our employees are the foundation of our success. and today we are the largest, national multiline insurance company dedicated to serving america’s educators and their families. our purpose is to provide lifelong financial well-being for educators and their families through personalized service, advice, and a full range of tailored insurance and financial products. through our professional agents and their staff, we offer insurance and financial products to the educational community across the united states. horace mann offers auto, homeowners and life insurance, retirement annuities, and other fina

## Stock Price Trends

Stock price trends estimated using linear regression.

## Paying users area

The data is hidden behind and trends are not shown in the charts.
Unhide data and trends.

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#### Key facts

• The primary trend is increasing.
• The growth rate of the primary trend is 84.69% per annum.
• HMN price at the close of December 8, 2023 was \$33.21 and was inside the primary price channel.
• The secondary trend is decreasing.
• The decline rate of the secondary trend is 4.45% per annum.
• HMN 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 HMN 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 15, 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()
= \$

### 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
=

#### November 22, 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()
= \$