backtrader.indicators.pivotpoint module

Pivot Point Indicator Module - Support and resistance levels.

This module provides Pivot Point indicators for calculating support and resistance levels from previous period price data.

Classes:

PivotPoint: Standard pivot points with 2 support/resistance levels. FibonacciPivotPoint: Pivot points with Fibonacci-based levels. DemarkPivotPoint: Demark pivot point calculation.

示例

class MyStrategy(bt.Strategy):
def __init__(self):

# Calculate pivot points from resampled data (data1) self.pivot = bt.indicators.PivotPoint(self.data1)

def next(self):

# Buy when price breaks above resistance level 1 if self.data.close[0] > self.pivot.r1[0]:

self.buy()

# Sell when price breaks below support level 1 elif self.data.close[0] < self.pivot.s1[0]:

self.sell()

class backtrader.indicators.pivotpoint.PivotPoint[源代码]

基类：Indicator

Defines a level of significance by taking into account the average of price bar components of the past period of a larger timeframe. For example, when operating with days, the values are taking from the already "past" month fixed prices.

Example of using this indicator:

data = btfeeds.ADataFeed(dataname=x, timeframe=bt.TimeFrame.Days) cerebro.adddata(data) cerebro.resampledata(data, timeframe=bt.TimeFrame.Months)

In the __init__ method of the strategy:

pivotindicator = btind.PivotPoiont(self.data1) # the resampled data

The indicator will try to automatically plo to the non-resampled data. To disable this behavior, use the following during construction:

  • _autoplot=False

备注

The example shows days and months, but any combination of timeframes can be used. See the literature for recommended combinations

Formula:

  • pivot = (h + l + c) / 3 # variants duplicate close or add open

  • support1 = 2.0 * pivot - high

  • support2 = pivot - (high - low)

  • resistance1 = 2.0 * pivot - low

  • resistance2 = pivot + (high - low)

See:
plotinfo = <backtrader.metabase.plotinfo_obj object>
__init__(*args, **kwargs)
next()[源代码]

Calculate pivot point and support/resistance levels.

Standard formula: p = (h + l + c) / 3 Support/Resistance levels derived from pivot and high-low range.

once(start, end)[源代码]

Calculate pivot point levels in runonce mode.

Computes pivot, support, and resistance levels across all bars.

frompackages = ()
packages = ()
class backtrader.indicators.pivotpoint.FibonacciPivotPoint[源代码]

基类：Indicator

Defines a level of significance by taking into account the average of price bar components of the past period of a larger timeframe. For example, when operating with days, the values are taking from the already "past" month fixed prices.

Fibonacci levels (configurable) are used to define the support/resistance levels

Example of using this indicator:

data = btfeeds.ADataFeed(dataname=x, timeframe=bt.TimeFrame.Days) cerebro.adddata(data) cerebro.resampledata(data, timeframe=bt.TimeFrame.Months)

In the __init__ method of the strategy:

pivotindicator = btind.FibonacciPivotPoiont(self.data1) # the resampled data

The indicator will try to automatically plo to the non-resampled data. To disable this behavior, use the following during construction:

  • _autoplot=False

备注

The example shows days and months, but any combination of timeframes can be used. See the literature for recommended combinations

Formula:

  • pivot = (h + l + c) / 3 # variants duplicate close or add open

  • support1 = p - level1 * (high - low) # level1 0.382

  • support2 = p - level2 * (high - low) # level2 0.618

  • support3 = p - level3 * (high - low) # level3 1.000

  • resistance1 = p + level1 * (high - low) # level1 0.382

  • resistance2 = p + level2 * (high - low) # level2 0.618

  • resistance3 = p + level3 * (high - low) # level3 1.000

See:
plotinfo = <backtrader.metabase.plotinfo_obj object>
__init__(*args, **kwargs)
next()[源代码]

Calculate Fibonacci pivot point and support/resistance levels.

Uses Fibonacci ratios (0.382, 0.618, 1.0) to calculate support/resistance levels from pivot point.

once(start, end)[源代码]

Calculate Fibonacci pivot point levels in runonce mode.

Computes pivot and Fibonacci-based support/resistance levels across all bars.

frompackages = ()
packages = ()
class backtrader.indicators.pivotpoint.DemarkPivotPoint[源代码]

基类：Indicator

Defines a level of significance by taking into account the average of price bar components of the past period of a larger timeframe. For example, when operating with days, the values are taking from the already "past" month fixed prices.

Example of using this indicator:

data = btfeeds.ADataFeed(dataname=x, timeframe=bt.TimeFrame.Days) cerebro.adddata(data) cerebro.resampledata(data, timeframe=bt.TimeFrame.Months)

In the __init__ method of the strategy:

pivotindicator = btind.DemarkPivotPoiont(self.data1) # the resampled data

The indicator will try to automatically plo to the non-resampled data. To disable this behavior, use the following during construction:

  • _autoplot=False

备注

The example shows days and months, but any combination of timeframes can be used. See the literature for recommended combinations

Formula:

  • if close < open x = high + (2 x low) + close

  • If close > open x = (2 x high) + low + close

  • If Close == open x = high + low + (2 x close)

  • P = x / 4

  • Support1 = x / 2 - high

  • resistance1 = x / 2 - low

See:
plotinfo = <backtrader.metabase.plotinfo_obj object>
__init__(*args, **kwargs)
next()[源代码]

Calculate Demark pivot point and support/resistance levels.

Demark formula uses relationship between open and close to determine the calculation method.

once(start, end)[源代码]

Calculate Demark pivot point levels in runonce mode.

Computes Demark-style pivot, support, and resistance levels across all bars.

frompackages = ()
packages = ()