Stock Price Trends

T. Rowe Price Group, Inc. (TROW)

t. rowe price (trow) is an independent investment management firm with an unyielding focus on helping investors around the world achieve their long-term goals. headquartered in baltimore, we provide a broad array of mutual funds, subadvisory services, separate account management, and related services for individuals, institutions, retirement plan sponsors, and financial intermediaries. our approach to managing investments is rooted in our own fundamental research, distinguished by discipline, and carried out by experienced professionals. the investment products (including the t. rowe price mutual funds) or services referred to on this profile may be offered only to persons in the united states. this profile should not be considered a solicitation or offering of any investment products or services to investors residing outside the united states t. rowe price investment services, inc.

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 67.83% per annum.
  • TROW price at the close of March 1, 2024 was $113.48 and was lower than the bottom border of the primary price channel by $657.62 (85.28%). This indicates a possible reversal in the primary trend direction.
  • The secondary trend is decreasing.
  • The decline rate of the secondary trend is 23.51% per annum.
  • TROW price at the close of March 1, 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:
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 TROW 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
=

Price channel spread:

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

March 5, 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()
= $

September 13, 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()
= $

Description

  • The primary trend is increasing.
  • The growth rate of the primary trend is 67.83% per annum.
  • TROW price at the close of March 1, 2024 was $113.48 and was lower than the bottom border of the primary price channel by $657.62 (85.28%). This indicates a possible reversal in the primary trend direction.

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
=

March 5, 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()
= $

February 28, 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 23.51% per annum.
  • TROW price at the close of March 1, 2024 was inside the secondary price channel.