# Healthcare Realty Trust Incorporated (HR)

healthcare trust of america, inc. (nyse: hta) is a publicly traded real estate investment trust (reit) that acquires, owns, and operates medical office buildings. over the last ten years since its formation in 2006, the company has invested $3.6 billion in medical office buildings comprising 15.4 million square feet across 28 states. hta has a consistent track record of generating shareholder returns and listed on the new york stock exchange in june of 2012. hta invests in key markets with above average growth and healthcare infrastructure that is capable of servicing long-term patient demand. within each key market, hta focuses on acquiring medical office buildings on health system campuses, in community-core locations, or around university medical centers. the portfolio consists of medical office buildings that are core-critical, a key part of the integrated delivery of healthcare, and that continue to complement the company’s institutional asset management and leasing platform. ht

## 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 30.55% per annum.
- HR price at the close of March 1, 2024 was $13.88 and was inside the primary price channel.
- The secondary trend is decreasing.
- The decline rate of the secondary trend is 86.70% per annum.
- HR price at the close of March 1, 2024 was inside the secondary price channel.

### 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 HR 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

=

#### September 14, 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 12, 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()

= $

#### Description

- The primary trend is decreasing.
- The decline rate of the primary trend is 30.55% per annum.
- HR price at the close of March 1, 2024 was $13.88 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

=

#### January 10, 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()

= $

#### 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 decreasing.
- The decline rate of the secondary trend is 86.70% per annum.
- HR price at the close of March 1, 2024 was inside the secondary price channel.