Candlestick Patterns¶
Abandoned Baby - Bear¶
-
qufilab.abandoned_baby_bear(high, low, open_, close, periods=10)¶ Abandoned Baby Bear
- Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- patternndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Abandoned Baby - Bull¶
-
qufilab.abandoned_baby_bull(high, low, open_, close, periods=10)¶ Abandoned Baby Bull
- Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- patternndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Belt Hold - Bear¶
-
qufilab.belthold_bear(high, low, open_, close, periods=10, shadow_margin=5.0)¶ Belt Hold Bear
- Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- shadow_marginfloat, optional
Specify what margin should be allowed for the shadows. By using for example 5%, both the lower and upper shadow can be as high as 5% of the candlestick body size. This exist to allow some margin (not restrict to no shadow).
- Returns
- patternndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Belt Hold - Bull¶
-
qufilab.belthold_bull(high, low, open_, close, periods=10, shadow_margin=5.0)¶ Belt Hold Bull
- Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- shadow_marginfloat, optional
Specify what margin should be allowed for the shadows. By using for example 5%, both the lower and upper shadow can be as high as 5% of the candlestick body size. This exist to allow some margin (not restrict to no shadow).
- Returns
- patternndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Doji¶
-
qufilab.doji(high, low, open_, close, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- dojindarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Examples
>>> import qufilab as ql >>> import numpy as np ... >>> df = ql.load_sample('MSFT') >>> doji = ql.doji(df['high'], df['low'], df['open'], df['close']) >>> print(doji) [False False False ... False False False]
Dragonfly Doji¶
-
qufilab.dragonfly_doji(high, low, open_, close, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- dragonfly_dojindarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Examples
>>> import qufilab as ql >>> import numpy as np ... >>> df = ql.load_sample('MSFT') >>> dragonfly_doji = ql.dragonfly_doji(df['high'], df['low'], df['open'], df['close']) >>> print(dragonfly_doji) [False False False ... False False False]
Engulfing - Bear¶
-
qufilab.engulfing_bear(high, low, open_, close, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- engulfingndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Engulfing - Bull¶
-
qufilab.engulfing_bull(high, low, open_, close, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- engulfingndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Hammer¶
-
qufilab.hammer(high, low, open_, close, periods=10, shadow_margin=5.0)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- shadow_marginfloat, optional
Specify what margin should be allowed for the shadows. By using i.e. 5%, upper shadow can be as long as 5% of the candlestick body size. This exist to allow some margin and not exclude the shadows entirely.
- Returns
- hammerndarray
A numpy array of type bool specifying true whether a pattern has been found or false otherwise.
Notes
Observe that the lower shadow shall be bigger than 2x the body, but lower than 3x the body.
Examples
>>> import qufilab as ql >>> import numpy as np ... >>> df = ql.load_sample('MSFT') >>> hammer = ql.hammer(df['high'], df['low'], df['open'], df['close']) >>> print(hammer) [False False False ... False False False]
Harami - Bear¶
-
qufilab.harami_bear(high, low, open_, close, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- harami_bearndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Harami - Bull¶
-
qufilab.harami_bull(high, low, open_, close, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- harami_bullndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Inverted Hammer¶
-
qufilab.inverted_hammer(high, low, open_, close, periods=10, shadow_margin=5.0)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- shadow_marginfloat, optional
Specify what margin should be allowed for the shadows. By using i.e. 5%, lower shadow can be as long as 5% of the candlestick body size. This exist to allow some margin and not exclude the shadows entirely.
- Returns
- inverted_hammerndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Examples
>>> import qufilab as ql >>> import numpy as np ... >>> df = ql.load_sample('MSFT') >>> inverted_hammer = ql.inverted_hammer(df['high'], df['low'], df['open'], df['close']) >>> print(inverted_hammer) [False False False ... False False False]
Kicking - Bear¶
-
qufilab.kicking_bear(high, low, open_, close, periods=10, shadow_margin=5.0)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- shadow_marginfloat, optional
Specify what margin should be allowed for the shadows. By using for example 5%, both the lower and upper shadow can be as high as 5% of the candlestick body size. This exist to allow some margin (not restrict to no shadow).
- Returns
- kicking_bearndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Kicking - Bull¶
-
qufilab.kicking_bull(high, low, open_, close, periods=10, shadow_margin=5.0)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- shadow_marginfloat, optional
Specify what margin should be allowed for the shadows. By using for example 5%, both the lower and upper shadow can be as high as 5% of the candlestick body size. This exist to allow some margin (not restrict to no shadow).
- Returns
- kicking_bullndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Marubozu White¶
-
qufilab.marubozu_white(high, low, open_, close, shadow_margin=5.0, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- shadow_marginfloat, optional
Specify what margin should be allowed for the shadows. By using for example 5%, both the lower and upper shadow can be as high as 5% of the candlestick body size. This exist to allow some margin (not restrict to no shadow).
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- marubozu_whitendarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Examples
>>> import qufilab as ql >>> import numpy as np ... >>> df = ql.load_sample('MSFT') >>> marubozu_white = ql.marubozu_white(df['high'], df['low'], df['open'], df['close']) >>> print(marubozu_white) [False False False ... False False False]
Marubozu Black¶
-
qufilab.marubozu_black(high, low, open_, close, shadow_margin=5.0, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- shadow_marginfloat, optional
Specify what margin should be allowed for the shadows. By using for example 5%, both the lower and upper shadow can be as high as 5% of the candlestick body size. This exist to allow some margin (not restrict to no shadow).
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- marubozu_blackndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Piercing¶
-
qufilab.piercing(high, low, open_, close, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- piercingndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Spinning Top White¶
-
qufilab.spinning_top_white(high, low, open_, close, periods=10)¶ - Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- spinning_top_whitendarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.
Three White Soldiers¶
-
qufilab.tws(high, low, open_, close, periods=10)¶ Three White Soldiers
- Parameters
- highndarray
An array containing high prices.
- lowndarray
An array containing low prices.
- open_ndarray
An array containing open prices.
- closendarray
An array containing close prices.
- periodsint, optional
Specifying number of periods for trend identification.
- Returns
- twsndarray
A numpy ndarray of type bool specifying true whether a pattern has been found or false otherwise.