There were 251 trading days in the year 2022 (including the day after Thanksgiving, November 26th, when the market closed at 1pm)
Below is a break down of the number of days the market was open for each month, then the python code used to generate this data, and finally a list of dates the market was open.
Days Market Was Closed in 2022
Data is found here: https://www.nasdaq.com/market-activity/2022-stock-market-holiday-calendar
List of dates market was closed in 2022:
Martin Luther King, Jr. Day January 17, 2022 Closed
Presidents Day February 21, 2022 Closed
Good Friday April 15, 2022 Closed
Memorial Day May 30, 2022 Closed
Juneteenth Holiday June 20, 2022 Closed
Independence Day July 4, 2022 Closed
Labor Day September 5, 2022 Closed
Thanksgiving Day November 24, 2022 Closed
Early Close November 25, 2022 1:00 p.m.
Christmas Holiday December 26, 2022 ClosedDays Market Was Open Each Month
January: 20
February: 19
March: 23
April: 20
May: 21
June: 21
July: 20
August: 23
September: 21
October: 21
November: 21 (20 if 1pm close considered)
December: 21
Python Code
'''
Code Written By AutomateBard.com
Generates list of dates American markets were open for trading.
List of dates market was closed in 2022: https://www.nasdaq.com/market-activity/2022-stock-market-holiday-calendar
Martin Luther King, Jr. Day January 17, 2022 Closed
Presidents Day February 21, 2022 Closed
Good Friday April 15, 2022 Closed
Memorial Day May 30, 2022 Closed
Juneteenth Holiday June 20, 2022 Closed
Independence Day July 4, 2022 Closed
Labor Day September 5, 2022 Closed
Thanksgiving Day November 24, 2022 Closed
Early Close November 25, 2022 1:00 p.m.
Christmas Holiday December 26, 2022 Closed
'''
import pandas as pd
year = 2022
market_closed = [
'2022-01-17',
'2022-02-21',
'2022-04-15',
'2022-05-30',
'2022-06-20',
'2022-07-04',
'2022-09-05',
'2022-11-24',
#'2022-11-25', # 1pm close
'2022-12-26'
]
def generate_all_dates(year):
start = pd.to_datetime(f'01-01-{year}')
end = pd.to_datetime(f'12-31-{year}')
df = pd.Series(pd.date_range(start, end))
return df
def filter_weekdays(series):
new_series = series[series.dt.dayofweek < 5]
return new_series
def filter_market_closed_days(series, list_market_closed_dates):
series = series[series.isin(list_market_closed_dates) == False]
return series
#
if __name__ == '__main__':
dates = (generate_all_dates(year))
#print(dates)
weekdays = filter_weekdays(dates)
#print(weekdays)
market_open = filter_market_closed_days(weekdays, market_closed)
print(market_open)
print(f"Total days open: {len(market_open)}")
List Of Dates Market Was Open
2022-01-03
2022-01-04
2022-01-05
2022-01-06
2022-01-07
2022-01-10
2022-01-11
2022-01-12
2022-01-13
2022-01-14
2022-01-18
2022-01-19
2022-01-20
2022-01-21
2022-01-24
2022-01-25
2022-01-26
2022-01-27
2022-01-28
2022-01-31
2022-02-01
2022-02-02
2022-02-03
2022-02-04
2022-02-07
2022-02-08
2022-02-09
2022-02-10
2022-02-11
2022-02-14
2022-02-15
2022-02-16
2022-02-17
2022-02-18
2022-02-22
2022-02-23
2022-02-24
2022-02-25
2022-02-28
2022-03-01
2022-03-02
2022-03-03
2022-03-04
2022-03-07
2022-03-08
2022-03-09
2022-03-10
2022-03-11
2022-03-14
2022-03-15
2022-03-16
2022-03-17
2022-03-18
2022-03-21
2022-03-22
2022-03-23
2022-03-24
2022-03-25
2022-03-28
2022-03-29
2022-03-30
2022-03-31
2022-04-01
2022-04-04
2022-04-05
2022-04-06
2022-04-07
2022-04-08
2022-04-11
2022-04-12
2022-04-13
2022-04-14
2022-04-18
2022-04-19
2022-04-20
2022-04-21
2022-04-22
2022-04-25
2022-04-26
2022-04-27
2022-04-28
2022-04-29
2022-05-02
2022-05-03
2022-05-04
2022-05-05
2022-05-06
2022-05-09
2022-05-10
2022-05-11
2022-05-12
2022-05-13
2022-05-16
2022-05-17
2022-05-18
2022-05-19
2022-05-20
2022-05-23
2022-05-24
2022-05-25
2022-05-26
2022-05-27
2022-05-31
2022-06-01
2022-06-02
2022-06-03
2022-06-06
2022-06-07
2022-06-08
2022-06-09
2022-06-10
2022-06-13
2022-06-14
2022-06-15
2022-06-16
2022-06-17
2022-06-21
2022-06-22
2022-06-23
2022-06-24
2022-06-27
2022-06-28
2022-06-29
2022-06-30
2022-07-01
2022-07-05
2022-07-06
2022-07-07
2022-07-08
2022-07-11
2022-07-12
2022-07-13
2022-07-14
2022-07-15
2022-07-18
2022-07-19
2022-07-20
2022-07-21
2022-07-22
2022-07-25
2022-07-26
2022-07-27
2022-07-28
2022-07-29
2022-08-01
2022-08-02
2022-08-03
2022-08-04
2022-08-05
2022-08-08
2022-08-09
2022-08-10
2022-08-11
2022-08-12
2022-08-15
2022-08-16
2022-08-17
2022-08-18
2022-08-19
2022-08-22
2022-08-23
2022-08-24
2022-08-25
2022-08-26
2022-08-29
2022-08-30
2022-08-31
2022-09-01
2022-09-02
2022-09-06
2022-09-07
2022-09-08
2022-09-09
2022-09-12
2022-09-13
2022-09-14
2022-09-15
2022-09-16
2022-09-19
2022-09-20
2022-09-21
2022-09-22
2022-09-23
2022-09-26
2022-09-27
2022-09-28
2022-09-29
2022-09-30
2022-10-03
2022-10-04
2022-10-05
2022-10-06
2022-10-07
2022-10-10
2022-10-11
2022-10-12
2022-10-13
2022-10-14
2022-10-17
2022-10-18
2022-10-19
2022-10-20
2022-10-21
2022-10-24
2022-10-25
2022-10-26
2022-10-27
2022-10-28
2022-10-31
2022-11-01
2022-11-02
2022-11-03
2022-11-04
2022-11-07
2022-11-08
2022-11-09
2022-11-10
2022-11-11
2022-11-14
2022-11-15
2022-11-16
2022-11-17
2022-11-18
2022-11-21
2022-11-22
2022-11-23
2022-11-25
2022-11-28
2022-11-29
2022-11-30
2022-12-01
2022-12-02
2022-12-05
2022-12-06
2022-12-07
2022-12-08
2022-12-09
2022-12-12
2022-12-13
2022-12-14
2022-12-15
2022-12-16
2022-12-19
2022-12-20
2022-12-21
2022-12-22
2022-12-23
2022-12-27
2022-12-28
2022-12-29
2022-12-30