Stock Price Trends

NVR, Inc. (NVR)

nvr, inc. is a top 5 us homebuilder and an industry leading company. with more than 65 years of experience building quality homes and successful careers, and our standing as the most profitable publicly traded homebuilding company in the us, nvr has developed our reputation for stability & responsibility. as a market leading homebuilder, nvr operates throughout 27 metropolitan areas in 15 states under the brand names of ryan homes, nvhomes, foxridge homes, and newly acquired heartland homes. we are the dominant homebuilder in each of our markets and have constructed more than 365,000 homes while maintaining a commitment to quality product & customer care. nvr mortgage’s primary focus is to serve the needs of nvr homebuyers while nvr settlement services provides a complete range of settlement and title services to support nvr’s homebuilding operations. at the corporate level, nvr provides various support functions and an intertwined network of resources utilized by each of its co

Stock Price Trends

Stock price trends estimated using linear regression.

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Key facts

  • The primary trend is increasing.
  • The growth rate of the primary trend is 52.01% per annum.
  • NVR price at the close of December 8, 2023 was $6,535.89 and was lower than the bottom border of the primary price channel by $0.25 (0.00%). This indicates a possible reversal in the primary trend direction.
  • The secondary trend is increasing.
  • The growth rate of the secondary trend is 4.75% per annum.
  • NVR price at the close of December 8, 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 NVR 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 10, 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()
= $

September 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()
= $


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
=

April 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()
= $

December 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()
= $