Stock Price Trends

Gartner Inc (IT)

Gartner, Inc. is a leading global research and advisory firm headquartered in Stamford, Connecticut, specializing in providing insights and strategic guidance to business leaders across various sectors, including IT, finance, human resources, and supply chain management. Renowned for its comprehensive market analysis and robust research methodologies, Gartner supports organizations in making informed decisions that drive growth and innovation. The company's extensive portfolio of services includes tailored consulting, benchmarking, and training, enabling clients to navigate complex business landscapes effectively. With a rich history and a commitment to delivering actionable insights, Gartner continues to be an indispensable partner for enterprises seeking to enhance performance and strategic advantage.

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.

Get full access to the entire website.

This is a one-time payment. There is no automatic renewal.

Key facts

  • The primary trend is decreasing.
  • The decline rate of the primary trend is 57.04% per annum.
  • IT price at the close of October 31, 2025 was $248.34 and was inside the primary price channel.
  • The secondary trend is increasing.
  • The growth rate of the secondary trend is 23.27% per annum.
  • IT price at the close of October 31, 2025 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 IT 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
=

October 11, 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()
= $

October 31, 2025 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 57.04% per annum.
  • IT price at the close of October 31, 2025 was $248.34 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
=

August 5, 2025 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()
= $

October 31, 2025 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 23.27% per annum.
  • IT price at the close of October 31, 2025 was inside the secondary price channel.