Stock Analysis on Net

Tesla Inc. (NASDAQ:TSLA)

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Stock Price Trends

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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 41.92% per annum.
  • TSLA price at the close of June 8, 2023 was $234.86 and was higher than the top border of the primary trend channel by $21.01 (9.83%). This indicates a possible reversal in the primary trend direction.
  • The secondary trend is increasing.
  • The growth rate of the secondary trend is 11,015.93% per annum.
  • TSLA price at the close of June 8, 2023 was inside the secondary trend 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 trend channel:
Exp(Yi) = Exp(a + b × Xi + 2 × s)

Bottom border of trend channel:
Exp(Yi) = Exp(a + b × Xi – 2 × s)

where:

i - observation number
Yi - natural logarithm of TSLA 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
=

Trend channel spread:

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

October 18, 2021 calculations

Top border of trend channeld:

Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $

Bottom border of trend channel:

Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $

May 30, 2023 calculations

Top border of trend channel:

Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $

Bottom border of trend 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
=

Trend channel spread:

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

May 15, 2023 calculations

Top border of trend channel:

Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $

Bottom border of trend channel:

Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $

June 8, 2023 calculations

Top border of trend channel:

Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $

Bottom border of trend channel:

Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $