Stock Price Trends

Standard Motor Products, Inc. (SMP)

standard motor products, inc., (smp) is a leading independent manufacturer and distributor of replacement parts for motor vehicles in the automotive aftermarket industry, with an increasing focus on the original equipment and original equipment service markets. smp stock is publicly traded on the new york stock exchange (smp) where it has been listed since 1977. smp is organized into two major operating segments, each of which focuses on a specific line of replacement parts. engine management segment manufactures a full line of engine management related products. temperature control segment manufactures and remanufactures a full line of replacement parts for automotive air conditioning and heating systems. smp products are marketed throughout the u.s., canada, latin america, europe and asia through traditional as well as non-traditional channels.

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 26.94% per annum.
  • SMP price at the close of November 28, 2023 was $35.58 and was higher than the top border of the primary price channel by $5.25 (17.32%). This indicates a possible reversal in the primary trend direction.
  • The secondary trend is increasing.
  • The growth rate of the secondary trend is 0.62% per annum.
  • SMP 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 SMP 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
=

October 4, 2021 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()
= $

January 19, 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
=

August 4, 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 11, 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()
= $