# Cohu, Inc. (COHU)

cohu is a publicly traded (nasdaq: cohu) global company with headquarters in poway, ca in san diego county. we are a leader in the semiconductor test and inspection equipment industry. our customers are global leaders in industries that include automotive, computing, mobility, iot, communications, high-speed memory, industrial, and solid state lighting. the company offers the broadest portfolio of enabling technologies in the industry that can be integrated in any of its handler platforms to optimize semiconductor test and solve some of the most challenging customer requirements. our business groups and products include: digital test handlers – pick-and-place semiconductor test handlers, burn-in related equipment and thermal sub-systems (reference delta design products). analog test handlers – gravity feed, test-in-strip handlers and mems test units (reference rasco products) and turret-based test handling and back-end finishing equipment for ics, leds and discrete components (referenc

## 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 24.21% per annum.
- COHU price at the close of December 8, 2023 was $32.91 and was higher than the top border of the primary price channel by $10.32 (45.69%). This indicates a possible reversal in the primary trend direction.
- The secondary trend is increasing.
- The growth rate of the secondary trend is 31.48% per annum.
- COHU price at the close of December 8, 2023 was lower than the bottom border of the secondary price channel by $3.83 (10.43%). 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 COHU 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: December 3, 2020

End date: October 20, 2022

a = 4.3251

b = -0.0008

s = 0.0887

Annual growth rate:

Exp(365 × b) – 1

= Exp(365 × -0.0008) – 1

= -24.21%

Price channel spread:

Exp(4 × s) – 1

= Exp(4 × 0.0887) – 1

= 42.59%

#### December 3, 2020 calculations

Top border of price channel:

Exp(Y_{500})

= Exp(a + b × X_{500} + 2 × s)

= Exp(a + b × 724 + 2 × s)

= Exp(4.3251 + -0.0008 × 724 + 2 × 0.0887)

= Exp(3.9527)

= $52.08

Bottom border of price channel:

Exp(Y_{500})

= Exp(a + b × X_{500} – 2 × s)

= Exp(a + b × 724 – 2 × s)

= Exp(4.3251 + -0.0008 × 724 – 2 × 0.0887)

= Exp(3.5979)

= $36.52

#### October 20, 2022 calculations

Top border of price channel:

Exp(Y_{973})

= Exp(a + b × X_{973} + 2 × s)

= Exp(a + b × 1,410 + 2 × s)

= Exp(4.3251 + -0.0008 × 1,410 + 2 × 0.0887)

= Exp(3.4318)

= $30.93

Bottom border of price channel:

Exp(Y_{973})

= Exp(a + b × X_{973} – 2 × s)

= Exp(a + b × 1,410 – 2 × s)

= Exp(4.3251 + -0.0008 × 1,410 – 2 × 0.0887)

= Exp(3.0770)

= $21.69

### Secondary Trend

Start date: February 22, 2022

End date: September 6, 2023

a = 2.3924

b = 0.0007

s = 0.0781

Annual growth rate:

Exp(365 × b) – 1

= Exp(365 × 0.0007) – 1

= 31.48%

Price channel spread:

Exp(4 × s) – 1

= Exp(4 × 0.0781) – 1

= 36.70%

#### February 22, 2022 calculations

Top border of price channel:

Exp(Y_{806})

= Exp(a + b × X_{806} + 2 × s)

= Exp(a + b × 1,170 + 2 × s)

= Exp(2.3924 + 0.0007 × 1,170 + 2 × 0.0781)

= Exp(3.4261)

= $30.76

Bottom border of price channel:

Exp(Y_{806})

= Exp(a + b × X_{806} – 2 × s)

= Exp(a + b × 1,170 – 2 × s)

= Exp(2.3924 + 0.0007 × 1,170 – 2 × 0.0781)

= Exp(3.1135)

= $22.50

#### September 6, 2023 calculations

Top border of price channel:

Exp(Y_{1,192})

= Exp(a + b × X_{1,192} + 2 × s)

= Exp(a + b × 1,731 + 2 × s)

= Exp(2.3924 + 0.0007 × 1,731 + 2 × 0.0781)

= Exp(3.8468)

= $46.84

Bottom border of price channel:

Exp(Y_{1,192})

= Exp(a + b × X_{1,192} – 2 × s)

= Exp(a + b × 1,731 – 2 × s)

= Exp(2.3924 + 0.0007 × 1,731 – 2 × 0.0781)

= Exp(3.5342)

= $34.27