Cirrus Logic, Inc. (CRUS)

cirrus logic is a leader in high performance, low-power ics for audio and voice signal processing applications. cirrus logic’s products span the entire audio signal chain, from capture to playback, providing innovative products for the world’s top smartphones, tablets, digital headsets, wearables and emerging smart home applications. with headquarters in austin, texas, cirrus logic is recognized globally for its award-winning corporate culture. check us out at www.cirrus.com. founded in 1984, cirrus logic excels at developing complex chip designs where feature integration and innovation is a premium. cirrus logic has more than 2,100 patents that are key to our more than 700 products serving more than 2,500 end customers globally, through both direct and distributor-based channel sales. the company’s headquarters are in austin, texas, with international locations in europe, china and japan.

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 5.60% per annum.
• CRUS price at the close of March 1, 2024 was \$93.23 and was higher than the top border of the primary price channel by \$11.64 (14.27%). This indicates a possible reversal in the primary trend direction.
• The secondary trend is increasing.
• The growth rate of the secondary trend is 94.81% per annum.
• CRUS price at the close of March 1, 2024 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 CRUS 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
=

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

November 11, 2020 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 10, 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()
= \$

Description

• The primary trend is decreasing.
• The decline rate of the primary trend is 5.60% per annum.
• CRUS price at the close of March 1, 2024 was \$93.23 and was higher than the top border of the primary price channel by \$11.64 (14.27%). This indicates a possible reversal in the primary trend direction.

Secondary Trend

Start date:
End date:

a =

b =

s =

Annual growth rate:

Exp(365 × b) – 1
= Exp(365 × ) – 1
=

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

October 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()
= \$

March 1, 2024 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()
= \$

Description

• The secondary trend is increasing.
• The growth rate of the secondary trend is 94.81% per annum.
• CRUS price at the close of March 1, 2024 was inside the secondary price channel.