Albemarle Corporation (ALB)
albemarle corporation, headquartered in baton rouge, louisiana, is a premier specialty chemicals company with leading positions in attractive end markets around the world. with a broad customer reach and diverse end markets, albemarle develops, manufactures and markets technologically advanced and high value added products, including lithium and lithium compounds, bromine and derivatives, catalysts and surface treatment chemistries used in a wide range of applications including consumer electronics, flame retardants, metal processing, plastics, contemporary and alternative transportation vehicles, refining, pharmaceuticals, agriculture, construction and custom chemistry services. albemarle is focused on delivering differentiated, performance-based technologies that deliver innovative and sustainable solutions to its customers. the company employs approximately 6,900 people and serves customers in approximately 100 countries. albemarle regularly posts information to www.albemarle.com,
Stock Price Trends
Stock price trends estimated using linear regression.
Paying users area
Try for free
Stock pages available for free today:
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 41.94% per annum.
- ALB price at the close of November 28, 2023 was $123.91 and was inside the primary price channel.
- The secondary trend is decreasing.
- The decline rate of the secondary trend is 82.58% per annum.
- ALB price at the close of November 28, 2023 was inside the secondary price channel.
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 ALB 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
=
August 11, 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()
= $
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()
= $
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
=
July 3, 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()
= $