Kimberly-Clark Corporation (KMB)
kimberly-clark makes the essentials for a better life with well-known brands that matter every day – at home, school, work and on the go. throughout our 144 years, we have challenged conventional wisdom to innovate products that better meet the needs of consumers. we have created new categories with top brands like kleenex®, and redefined categories with huggies® and u by kotex®. while growing our $18+ billion global business, we help build careers through collaborative teams that push boundaries and engaging experiences and endless opportunities to work with some of the world’s most recognized brands. our 43,000 employees are changing the world for the better, too, generously giving back to communities and causes around the globe. if innovative thinking and a passion to win inspire you, come unleash your power at kimberly-clark.
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 30.96% per annum.
- KMB price at the close of November 28, 2023 was $121.99 and was higher than the top border of the primary price channel by $2.02 (1.69%). This indicates a possible reversal in the primary trend direction.
- The secondary trend is increasing.
- The growth rate of the secondary trend is 32.09% per annum.
- KMB 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:
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 KMB 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
=
April 21, 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()
= $
November 10, 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 30, 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()
= $
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()
= $