Stock Price Trends

Xcel Energy Inc. (XEL)

as a leading electric and natural gas energy company, we offer a comprehensive portfolio of energy-related products and services to 3.4 million electricity customers and 1.9 million natural gas customers across our eight states: colorado, michigan, minnesota, new mexico, north dakota, south dakota, texas and wisconsin. our workforce of more than 12,000 is rising to the challenge of a dynamic, constantly-changing utility industry. one that requires us to be even more customer focused, forward thinking and productive while remaining committed to meeting our customers’ fundamental need for safe, reliable, affordable energy. with nearly 50% of our workforce eligible to retire in the next five years, there’s never been a better time to come on board. do you have a passion for renewable energy, like wind or solar? or care about giving back to the community? you’ll be in a position to directly impact our energy future. at xcel energy, you’ll be challenged, respected and rewarded. you’ll find

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 12.07% per annum.
  • XEL price at the close of February 16, 2024 was $59.07 and was inside the primary price channel.
  • The secondary trend is increasing.
  • The growth rate of the secondary trend is 12.39% per annum.
  • XEL price at the close of February 16, 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 XEL 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 25, 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()
= $

February 16, 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 primary trend is decreasing.
  • The decline rate of the primary trend is 12.07% per annum.
  • XEL price at the close of February 16, 2024 was $59.07 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 14, 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()
= $

February 16, 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 increasing.
  • The growth rate of the secondary trend is 12.39% per annum.
  • XEL price at the close of February 16, 2024 was inside the secondary price channel.