# Silicon Laboratories Inc. (SLAB)

silicon labs is a leading provider of silicon, software and solutions for a smarter, more connected world. our award-winning technologies are shaping the future of the internet of things, internet infrastructure, industrial automation, consumer and automotive markets. headquartered in austin, silicon labs has more than 1,400 team members in over 20 countries creating products focused on performance, energy savings, connectivity and simplicity. we're passionate about what we do and are proud that the global semiconductor alliance voted us the most respected public semiconductor company for three of the last four years. connect with us at silabs.com.

## Stock Price Trends

Stock price trends estimated using linear regression.

#### Key facts

- The primary trend is decreasing.
- The decline rate of the primary trend is 79.79% per annum.
- SLAB price at the close of November 28, 2023 was $101.06 and was higher than the top border of the primary price channel by $7.03 (7.47%). This indicates a possible reversal in the primary trend direction.
- The secondary trend is increasing.
- The growth rate of the secondary trend is 878.27% per annum.
- SLAB price at the close of November 28, 2023 was lower than the bottom border of the secondary price channel by $0.89 (0.88%). This indicates a possible reversal in the secondary trend direction.
- 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:

Y_{i} = α + β × X_{i} + ε_{i}

Top border of price channel:

Exp(Y_{i}) = Exp(a + b × X_{i} + 2 × s)

Bottom border of price channel:

Exp(Y_{i}) = Exp(a + b × X_{i} – 2 × s)

where:

i - observation number

Y_{i} - natural logarithm of SLAB price

X_{i} - time index, 1 day interval

σ - standard deviation of ε_{i}

a - estimator of α

b - estimator of β

s - estimator of σ

Exp() - calculates the exponent of e

### Primary Trend

Start date: June 29, 2023

End date: November 13, 2023

a = 12.4589

b = -0.0044

s = 0.0398

Annual growth rate:

Exp(365 × b) – 1

= Exp(365 × -0.0044) – 1

= -79.79%

Price channel spread:

Exp(4 × s) – 1

= Exp(4 × 0.0398) – 1

= 17.25%

#### June 29, 2023 calculations

Top border of price channel:

Exp(Y_{1,151})

= Exp(a + b × X_{1,151} + 2 × s)

= Exp(a + b × 1,673 + 2 × s)

= Exp(12.4589 + -0.0044 × 1,673 + 2 × 0.0398)

= Exp(5.2095)

= $183.01

Bottom border of price channel:

Exp(Y_{1,151})

= Exp(a + b × X_{1,151} – 2 × s)

= Exp(a + b × 1,673 – 2 × s)

= Exp(12.4589 + -0.0044 × 1,673 – 2 × 0.0398)

= Exp(5.0504)

= $156.08

#### November 13, 2023 calculations

Top border of price channel:

Exp(Y_{1,246})

= Exp(a + b × X_{1,246} + 2 × s)

= Exp(a + b × 1,810 + 2 × s)

= Exp(12.4589 + -0.0044 × 1,810 + 2 × 0.0398)

= Exp(4.6094)

= $100.42

Bottom border of price channel:

Exp(Y_{1,246})

= Exp(a + b × X_{1,246} – 2 × s)

= Exp(a + b × 1,810 – 2 × s)

= Exp(12.4589 + -0.0044 × 1,810 – 2 × 0.0398)

= Exp(4.4502)

= $85.65

### Secondary Trend

Start date: October 30, 2023

End date: November 24, 2023

a = -6.7325

b = 0.0062

s = 0.0230

Annual growth rate:

Exp(365 × b) – 1

= Exp(365 × 0.0062) – 1

= 878.27%

Price channel spread:

Exp(4 × s) – 1

= Exp(4 × 0.0230) – 1

= 9.66%

#### October 30, 2023 calculations

Top border of price channel:

Exp(Y_{1,236})

= Exp(a + b × X_{1,236} + 2 × s)

= Exp(a + b × 1,796 + 2 × s)

= Exp(-6.7325 + 0.0062 × 1,796 + 2 × 0.0230)

= Exp(4.5355)

= $93.27

Bottom border of price channel:

Exp(Y_{1,236})

= Exp(a + b × X_{1,236} – 2 × s)

= Exp(a + b × 1,796 – 2 × s)

= Exp(-6.7325 + 0.0062 × 1,796 – 2 × 0.0230)

= Exp(4.4433)

= $85.06

#### November 24, 2023 calculations

Top border of price channel:

Exp(Y_{1,254})

= Exp(a + b × X_{1,254} + 2 × s)

= Exp(a + b × 1,821 + 2 × s)

= Exp(-6.7325 + 0.0062 × 1,821 + 2 × 0.0230)

= Exp(4.6917)

= $109.04

Bottom border of price channel:

Exp(Y_{1,254})

= Exp(a + b × X_{1,254} – 2 × s)

= Exp(a + b × 1,821 – 2 × s)

= Exp(-6.7325 + 0.0062 × 1,821 – 2 × 0.0230)

= Exp(4.5995)

= $99.44