# iRobot Corporation (IRBT)

founded in 1990 by massachusetts institute of technology roboticists, irobot designs and builds some of the world’s most important robots. irobot’s home robots are revolutionizing the way people clean – inside and out. more than 10 million home robots have been sold worldwide, with the award-winning irobot roomba® floor vacuuming robot leading the charge. more than 5,000 of the company’s defense & security robots have been delivered to researchers, military and civil defense forces worldwide, performing thousands of dangerous search, reconnaissance and bomb-disposal missions while protecting those in harm’s way. leveraging its state-of-the-art ava® mobile robotics platform, irobot is bringing its solutions to new markets. the irobot ava® 500 delivers a new level of collaboration for office environments and other facilities, and rp-vita allows doctors to communicate with patients from virtually anywhere in the world. with two decades of leadership in the robot industry, irobot remains c

## 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 51.84% per annum.
- IRBT price at the close of November 28, 2023 was $35.48 and was higher than the top border of the primary price channel by $16.04 (82.53%). This indicates a possible reversal in the primary trend direction.
- The secondary trend is decreasing.
- The decline rate of the secondary trend is 32.80% per annum.
- IRBT price at the close of November 28, 2023 was inside the secondary price channel.

### 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 IRBT 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

=

#### January 20, 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()

= $

#### August 2, 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()

= $

### 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

=

#### May 3, 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()

= $

#### 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()

= $