# Humana Inc. (HUM)

at humana, our cultural foundation is aligned to helping members achieve their best health by delivering personalized, simplified, whole-person healthcare experiences. recognizing healthcare needs continue to evolve for each person, for each family and for each community, humana continuously creates innovative solutions and resources that help people live their healthiest lives on their terms –when and where they need it. our employees are at the heart of making this happen and that’s why we are dedicated to building an organization of dynamic talent whose experience and passion center on putting the customer first.

## 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 8.12% per annum.
- HUM price at the close of November 28, 2023 was $510.45 and was inside the primary price channel.
- The secondary trend is decreasing.
- The decline rate of the secondary trend is 6.66% per annum.
- HUM price at the close of November 28, 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:

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 HUM 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

=

#### April 29, 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 28, 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

=

Price channel spread:

Exp(4 × s) – 1

= Exp(4 × ) – 1

=

#### October 3, 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()

= $

#### November 28, 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()

= $