MasTec, Inc. (MTZ)
over the course of the last 80 years, mastec companies have been involved in some of the largest and most complex infrastructure construction projects across the country. our experience has given us a deep and comprehensive understanding of the markets we serve, as well as the ability to effectively manage people, projects and equipment. it allows us to proactively identify challenges, avoid pitfalls, and overcome obstacles, and to accurately set and meet expectations for schedule and budget. with offices across the country, a workforce of nearly 12,000 skilled professionals, and an extensive wholly-owned fleet of specialized construction equipment, mastec has the resources needed to reliably deliver quality work for even the most complicated jobs. our geographic reach, scalability, and overall financial stability enable us to meet each of our customers' changing needs on a daily basis. our focus on innovation colors everything we do, and as we've grown, we've fostered it throughout e
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 89.37% per annum.
- MTZ price at the close of December 8, 2023 was $66.43 and was higher than the top border of the primary price channel by $10.46 (18.68%). This indicates a possible reversal in the primary trend direction.
- The secondary trend is increasing.
- The growth rate of the secondary trend is 3,588.83% per annum.
- MTZ price at the close of December 8, 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 MTZ 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
=
June 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 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
=
November 6, 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()
= $
December 8, 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()
= $