# Ormat Technologies, Inc. (ORA)

with over five decades of experience, ormat technologies, inc. is a leading geothermal company and the only vertically integrated company solely engaged in geothermal and recovered energy generation (reg), with the objective of becoming a leading global provider of renewable energy. the company owns, operates, designs, manufactures and sells geothermal and reg power plants primarily based on the ormat energy converter - a power generation unit that converts low-, medium- and high-temperature heat into electricity. with 69 u.s. patents, ormat’s power solutions have been refined and perfected under the most grueling environmental conditions. ormat has 470 employees in the united states and over 600 overseas. ormat’s flexible, modular solutions for geothermal power and reg are ideal for the vast range of resource characteristics. the company has engineered, manufactured and constructed power plants, which it currently owns or has installed to utilities and developers worldwide, totaling o

## 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 28.24% per annum.
• ORA price at the close of December 8, 2023 was \$70.68 and was inside the primary price channel.
• The secondary trend is increasing.
• The growth rate of the secondary trend is 275.02% per annum.
• ORA price at the close of December 8, 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 ORA 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 3, 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()
= \$

#### December 8, 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
=

Exp(4 × s) – 1
= Exp(4 × ) – 1
=

#### November 14, 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()
= \$

#### December 8, 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()
= \$