# The Greenbrier Companies, Inc. (GBX)

the greenbrier companies is a leading supplier of marine and rail transportation equipment and services, powering the movement of products around the world. greenbrier’s innovation and engineering expertise pairs with our capacity to build and repair transportation equipment. this allows us to provide an unrivaled level of service to our customers across the americas, europe and the countries of the gcc. with a railcar lease fleet of over 10,300 railcars, greenbrier also provides asset management services for nearly 400,000 railcars. our unique railcar leasing syndication platform brings us into contact with the world’s leading fixed asset investors. we have delivered over 21,000 railcars in a single year and maintain the capacity to produce over 35,000 railcars annually. learn more about greenbrier at www.gbrx.com.

## Stock Price Trends

Stock price trends estimated using linear regression.

## Paying users area

#### Try for free

Stock pages available for free today:

The data is hidden behind and trends are not shown in the charts.

Unhide data and trends.

Get full access to the entire website.

This is a one-time payment. There is no automatic renewal.

#### Key facts

- The primary trend is decreasing.
- The decline rate of the primary trend is 21.42% per annum.
- GBX price at the close of November 28, 2023 was $36.36 and was higher than the top border of the primary price channel by $4.10 (12.70%). This indicates a possible reversal in the primary trend direction.
- The secondary trend is increasing.
- The growth rate of the secondary trend is 26.50% per annum.
- GBX price at the close of November 28, 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:

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 GBX 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:

End date:

a =

b =

s =

Annual growth rate:

Exp(365 × b) – 1

= Exp(365 × ) – 1

=

Price channel spread:

Exp(4 × s) – 1

= Exp(4 × ) – 1

=

#### February 5, 2021 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()

= $

#### June 28, 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

=

Price channel spread:

Exp(4 × s) – 1

= Exp(4 × ) – 1

=

#### July 8, 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()

= $

#### November 28, 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()

= $