# F.N.B. Corporation (FNB)

f.n.b. corporation (nyse: fnb), headquartered in pittsburgh, pennsylvania, is a diversified financial services company operating in six states and three major metropolitan areas. it holds a top retail deposit market share in pittsburgh, pa, baltimore, md, and cleveland, oh. the company has total assets of \$16.8 billion and nearly 290 banking offices throughout pennsylvania, maryland, ohio and west virginia. f.n.b. provides a full range of commercial banking, consumer banking and wealth management solutions through its subsidiary network which is led by its largest affiliate, first national bank of pennsylvania, founded in 1864. commercial banking solutions include corporate banking, small business banking, investment real estate financing, international banking, business credit, capital markets and lease financing. the consumer banking segment provides a full line of consumer banking products and services including deposit products, mortgage lending, consumer lending and a complete s

## 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 21.84% per annum.
• FNB price at the close of November 28, 2023 was \$11.68 and was inside the primary price channel.
• The secondary trend is increasing.
• The growth rate of the secondary trend is 83.21% per annum.
• FNB 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:
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 FNB 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
=

#### October 17, 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 13, 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
=

#### September 21, 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()
= \$

#### 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()
= \$