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Merged
Akshat111111 merged 1 commit into from
Oct 17, 2023
Merged

Update pivots_points.py #1

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49 changes: 16 additions & 33 deletions technical/pivots_points.py
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Original file line number Diff line number Diff line change
@@ -1,23 +1,19 @@
import freqtrade.vendor.qtpylib.indicators as qtpylib
import pandas as pd

"""
Indicators for Freqtrade
author@: Gerald Lonlas
"""

import numpy as np
import pandas as pd

def pivots_points(dataframe: pd.DataFrame, timeperiod=30, levels=3) -> pd.DataFrame:
"""
Pivots Points

https://www.tradingview.com/support/solutions/43000521824-pivot-points-standard/

Formula:
Pivot = (Previous High + Previous Low + Previous Close)/3
Pivot = (Previous High + Previous Low + Previous Close) / 3

Resistance #1 = (2 x Pivot) - Previous Low
Support #1 = (2 x Pivot) - Previous High
Resistance #1 = (2 * Pivot) - Previous Low
Support #1 = (2 * Pivot) - Previous High

Resistance #2 = (Pivot - Support #1) + Resistance #1
Support #2 = Pivot - (Resistance #1 - Support #1)
Expand All @@ -32,34 +28,21 @@ def pivots_points(dataframe: pd.DataFrame, timeperiod=30, levels=3) -> pd.DataFr
:return: dataframe
"""

data = {}
typical_price = (dataframe['high'] + dataframe['low'] + dataframe['close']) / 3
data = {"pivot": typical_price}

low = qtpylib.rolling_mean(
series=pd.Series(index=dataframe.index, data=dataframe["low"]), window=timeperiod
)
for i in range(1, levels + 1):
data[f"r{i}"] = 2 * data["pivot"] - dataframe['low']
data[f"s{i}"] = 2 * data["pivot"] - dataframe['high']

high = qtpylib.rolling_mean(
series=pd.Series(index=dataframe.index, data=dataframe["high"]), window=timeperiod
)

# Pivot
data["pivot"] = qtpylib.rolling_mean(series=qtpylib.typical_price(dataframe), window=timeperiod)

# Resistance #1
data["r1"] = (2 * data["pivot"]) - low
for i in range(2, levels + 1):
prev_support = data[f"s{i - 1}"]
prev_resistance = data[f"r{i - 1}"]

# Resistance #2
data["s1"] = (2 * data["pivot"]) - high
data[f"r{i}"] = (data["pivot"] - prev_support) + prev_resistance
data[f"s{i}"] = data["pivot"] - (prev_resistance - prev_support)

# Calculate Resistances and Supports >1
for i in range(2, levels + 1):
prev_support = data["s" + str(i - 1)]
prev_resistance = data["r" + str(i - 1)]
return pd.DataFrame(data)

# Resitance
data["r" + str(i)] = (data["pivot"] - prev_support) + prev_resistance

# Support
data["s" + str(i)] = data["pivot"] - (prev_resistance - prev_support)

return pd.DataFrame(index=dataframe.index, data=data)