Moving averages are one of the core indicators in technical analysis. A Simple Moving Average (SMA) is simply the arithmetic average of stock price over a period. It is calculated by adding a selected range of prices, usually closing prices, and then dividing that figure by the number of time periods in that range.
The 50-Day SMA calculates the average price over 50 days. And the 20-Day SMA and 200-Day SMA calculates the average price over 20 days and 200 days separately.
As of today (2024-04-30), Penns Woods Bancorp's 50-Day SMA is $18.71. It's 20-Day SMA is $18.04 and 200-Day SMA is $21.55.
Competitive Comparison of Penns Woods Bancorp's 50-Day SMA
For the Banks - Regional subindustry, Penns Woods Bancorp's 50-Day SMA, along with its competitors' market caps and 50-Day SMA data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Penns Woods Bancorp's 50-Day SMA Distribution in the Banks Industry
For the Banks industry and Financial Services sector, Penns Woods Bancorp's 50-Day SMA distribution charts can be found below:
* The bar in red indicates where Penns Woods Bancorp's 50-Day SMA falls into.
Penns Woods Bancorp (NAS:PWOD) 50-Day SMA Calculation
The formula for calculating SMA is:
SMA
=
( P1 + P2 + ... + Pn )
/
n
where:
Pn is the price of the stock at period n.
n is the total number of periods.
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD. * For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
Penns Woods Bancorp (NAS:PWOD) 50-Day SMA Explanation
Simple Moving Average (SMA) is the arithmetic average of stock price over a period. The 20-Day SMA calculates the average price over 20 days. And the 50-Day SMA and 200-Day SMA calculates the average price over 50 days and 200 days separately. SMAs are often used to determine the price trend direction. A 200-Day SMA is usually a proxy for the long-term trend, while shorter periods indicate short-term trend.
SMA are commonly compared with stock price or different period SMAs to indicate a trading signal. Generally speaking, if the price goes above the SMA, or a short-term SMA crosses above a long-term SMA, an uptrend is expected, investors may want to go long or cover short. Conversely, if the price goes below the SMA, or the short-term SMA crosses below a long-term SMA, a downtrend is expected, investors may want to go short or exit long.
Two popular trading patterns that use SMA include the death cross and a golden cross. A death cross occurs when the 50-day SMA crosses below the 200-day SMA. This is considered a bearish signal, that further losses are in store. The golden cross is a bullish signal which occurs when a short-term SMA crosses above a long-term SMA.
Penns Woods Bancorp 50-Day SMA Related Terms
Thank you for viewing the detailed overview of Penns Woods Bancorp's 50-Day SMA provided by GuruFocus.com. Please click on the following links to see related term pages.
Penns Woods Bancorp (Penns Woods Bancorp) Business Description
Penns Woods Bancorp Inc is the bank holding company for Jersey Shore State Bank and Luzerne Bank. The banks serve customers in North Central and North Eastern Pennsylvania through their retail banking, commercial banking, mortgage services and financial services divisions. The Banks are engaged in commercial and retail banking which includes the acceptance of time, savings, and demand deposits, the funding of commercial, consumer, and mortgage loans, and safe deposit services. Utilizing a branch office network, ATMs, Internet, and telephone banking delivery channels, the Banks deliver their products and services to the communities residing in.
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