Events#

Additional functions that attempt to identify states (above/below) or events (crossing).

Above

Determines if each x value is above (or >=) each y value.

Parameters:

Name	Type	Description	Default
`x`	`Series`	`x`	required
`y`	`Series`	`y`	required
`asint`	`bool`	Returns as `Int`.	`True`
`offset`	`Int`	Post shift. Default: `0`	`None`

Returns:

Type	Description
`Series`	State where `x >= y`.

Example

x = Series([4, 2, 0, -1, 1])
y = Series([1, 1, 1, 1, 1])

x_above_y = ta.above(x, y)
# x_above_y = Series([1, 1, 0, 0, 1])

Above Value

Determines if each x value is above (or >=) a constant value.

Parameters:

Name	Type	Description	Default
`x`	`Series`	`x`	required
`value`	`IntFloat`	Value to compare with `x`.	required
`asint`	`bool`	Returns as `Int`.	`True`

Returns:

Type	Description
`Series`	State where `x >= y`.

Example

x = Series([4, 2, 0, -1, 1])
x_above_1 = ta.above_value(x, 1)
# x_above_1 = Series([1, 1, 0, 0, 1])

Below

Determines if each x value is below (or <=) each y value.

Parameters:

Name	Type	Description	Default
`x`	`Series`	`x`	required
`y`	`Series`	`y`	required
`asint`	`bool`	Returns as `Int`.	`True`
`offset`	`Int`	Post shift. Default: `0`	`None`

Returns:

Type	Description
`Series`	State where `x <= y`.

Example

x = Series([4, 2, 0, -1, 1])
y = Series([1, 1, 1, 1, 1])

x_below_y = ta.below(x, y)
# x_below_y = Series([0, 0, 1, 1, 1])

Below Value

Determines if each x value is below (or <=) a constant value.

Parameters:

Name	Type	Description	Default
`x`	`Series`	`x`	required
`value`	`IntFloat`	Value to compare with `x`.	required
`asint`	`bool`	Returns as `Int`.	`True`
`offset`	`Int`	Post shift. Default: `0`	`None`

Returns:

Type	Description
`Series`	State where `x <= y`.

Example

x = Series([4, 2, 0, -1, 1])
x_below_1 = ta.below_value(x, 1)
# x_below_1 = Series([0, 0, 1, 1, 1])

NOTICE

Thanks to all those that have sponsored and dontated to the library in the past! Your support has been greatly appreciated!

However, future releases are on definite hold until 100+ donations of $150+ have been received via Buy Me a Coffee.

Help keep this library and application the best in it's class!

Cross

Determines where x crosses y, either above or below, strictly (equal) or not.

Parameters:

Name	Type	Description	Default
`x`	`Series`	`x`	required
`y`	`Series`	`y`	required
`above`	`bool`	Check above. Check below, set `above=False`	`True`
`equal`	`bool`	At least/most, `=`, check.	`True`
`asint`	`bool`	Returns as `Int`.	`True`
`offset`	`Int`	Post shift. Default: `0`	`None`

Returns:

Type	Description
`Series`	Values where `x` crosses `y`.

Example

x = Series([4, 2, 0, -1, 1])
y = Series([1, 1, 1, 1, 1])

# Cross Above Examples
x_xae_y = ta.cross(x, y, above=True, equal=True)
# x_xae_y = Series([0, 0, 0, 0, 1])

x_xa_y = ta.cross(x, y, above=True, equal=False)
# x_xa_y = Series([0, 0, 0, 0, 0])

# Cross Below Examples
x_xbe_y = ta.cross(x, y, above=False, equal=True)
# x_xbe_y = Series([0, 0, 1, 0, 1])

x_xb_y = ta.cross(x, y, above=False, equal=False)
# x_xb_y = Series([0, 0, 1, 0, 0])

Cross Value

Determines where x crosses a constant value, either above or below, strictly (equal) or not.

Parameters:

Name	Type	Description	Default
`x`	`Series`	`x`	required
`value`	`IntFloat`	Value to compare with `x`.	required
`above`	`bool`	Check above. Check below, set `above=False`	`True`
`equal`	`bool`	At least/most, `=`, check.	`True`
`asint`	`bool`	Returns as `Int`.	`True`
`offset`	`Int`	Post shift. Default: `0`	`None`

Returns:

Type	Description
`Series`	Values where `x` crosses `y`.

Example

x = Series([4, 2, 0, -1, 1])

# Cross Above Examples
x_xae_y = ta.cross_value(x, 1, above=True, equal=True)
# x_xae_y = Series([0, 0, 0, 0, 1])

x_xa_y = ta.cross_value(x, 1, above=True, equal=False)
# x_xa_y = Series([0, 0, 0, 0, 0])

# Cross Below Examples
x_xbe_y = ta.cross_value(x, 1, above=False, equal=True)
# x_xbe_y = Series([0, 0, 1, 0, 1])

x_xb_y = ta.cross_value(x, 1, above=False, equal=False)
# x_xb_y = Series([0, 0, 1, 0, 0])

Trend Signals

This function creates Trend, Trades, Entries and Exit values per bar when given a trend condition e.g. trend = close > sma(close, 50).

Source

Kevin Johnson

Parameters:

Name	Type	Description	Default
`trend`	`Series`	`trend` Series. Boolean or integer values of `0` and `1`	required
`asbool`	`bool`	Return booleans. Default: `False`	`None`
`trade_offset`	`value`	Shift trade entries/exits with live: `0` and backesting: `1`. Default: `0`	`None`
`drift`	`int`	Difference amount. Default: `1`	`None`
`offset`	`int`	Post shift. Default: `0`	`None`

Other Parameters:

Name	Type	Description
`fillna`	`value`	`pd.DataFrame.fillna(value)`

Returns:

Type	Description
`DataFrame`	4 columns

Column Detail

Trends (trend: 1, no trend: 0)
Trades (Enter: 1, Exit: -1, Otherwise: 0)
Entries (entry: 1, nothing: 0)
Exits (exit: 1, nothing: 0)

Details

A trend is a state or condition, that is as simple as Close > MA or something more complex that has boolean or integer (trend: 1, no trend: 0) values.

VectorBT

For backtesting, set trade_offset=1.
Setting asbool=True is useful for backtesting with vectorbt's Portfolio.from_signal(close, entries, exits) method.

Example

These are two different outcomes for each (long/short) position and depends on the source and it's behavior.

Signals when Close > SMA50(Close)

ta.tsignals(close > ta.sma(close, 50), asbool=False)

Signals when EMA(Close, 8) > EMA(Close, 21)

ta.tsignals(ta.ema(close, 8) > ta.ema(close, 21), asbool=True)

Warning

Check ALL outcomes BEFORE making an Issue

Cross Signals

This function creates Trend, Trades, Entries and Exits values per bar for crossing events.

Sources

Kevin Johnson

Parameters:

Name	Type	Description	Default
`source`	`Series`	`source` Signal	required
`xa`	`Series`	Series the Signal crosses above if `above=True`	required
`xb`	`Series`	Series the Signal crosses below if `above=True`	required
`above`	`bool`	The `source` crossing; below is `False`. Default: `True`	`True`
`long`	`bool`	The `source` position; short is `False`. Default: `True`	`True`
`offset`	`int`	Post shift. Default: `0`	`None`
`asbool`	`bool`	Return booleans. Default: `False`	`None`
`trade_offset`	`value`	Shift trade entries/exits with live: `0` and backesting: `1`. Default: `0`	`None`

Other Parameters:

Name	Type	Description
`fillna`	`value`	`pd.DataFrame.fillna(value)`

Returns:

Type	Description
`DataFrame`	4 columns

Column Detail

Trends (trend: 1, no trend: 0)
Trades (Enter: 1, Exit: -1, Otherwise: 0)
Entries (entry: 1, nothing: 0)
Exits (exit: 1, nothing: 0)

VectorBT

For backtesting, set trade_offset=1.
Setting asbool=True is useful for backtesting with vectorbt's Portfolio.from_signal(close, entries, exits) method.

Example

These are two different outcomes for each (long/short) position and depends on the source and it's behavior.

rsi = df.ta.rsi()

When RSI crosses above 20 and then below 80 in a long position:

ta.xsignals(source=rsi, xa=20, xb=80, above=True, long=True)
# Simpler
# ta.xsignals(rsi, 20, 80, True, True)

When RSI crosses below 20 and then above 80 in a long position:

ta.xsignals(source=rsi, xa=20, xb=80, above=False, long=True)
# Simpler
# ta.xsignals(rsi, 20, 80, False, True)

Similarly, short positions (long=False) also differ depending on above state.

Warning

Check ALL parameter combination outcomes BEFORE making an Issue.

NOTICE

Thanks to all those that have sponsored and dontated to the library in the past! Your support has been greatly appreciated!

However, future releases are on definite hold until 100+ donations of $150+ have been received via Buy Me a Coffee.

Help keep this library and application the best in it's class!