technicators 1.0.1

Library for calculating diverse financial metrics

Technicators

Technicators provides a collection of methods for calculating various technical indicators commonly used in financial analysis.

Installation

pip install technicators

Usage

import pandas as pd
from technicators import Technicators

# Sample time series data
data = pd.Series([...])

# Calculate ALMA
alma_values = Technicators.ALMA(data, period=14)

# Calculate EMA
ema_values = Technicators.EMA(data, period=14)

# Calculate HMA
hma_values = Technicators.HMA(data, period=14)

# Calculate SMMA
smma_values = Technicators.SMMA(data, period=14)

# Calculate TEMA
tema_values = Technicators.TEMA(data, period=14)

# Calculate WMA
wma_values = Technicators.WMA(data, period=14)

Method Details

ALMA

• Calculates the Arnaud Legoux Moving Average (ALMA) using a variable window.
• Parameters:
  • dataset (pd.Series): The input time series data.
  • period (int): The period over which to calculate the ALMA.
  • offset (float): Offset multiplier for ALMA calculation. Default is 0.85.
  • sigma (float): Standard deviation factor for ALMA calculation. Default is 6.
• Returns:
  • pd.Series: A time series representing the ALMA values.

EMA

• Calculates the Exponential Moving Average (EMA) of a given time series.
• Parameters:
  • dataset (pd.Series): The input time series data.
  • period (int): The period over which to calculate the EMA.
  • adjust (bool): Whether to adjust the EMA calculation. Default is True.
• Returns:
  • pd.Series: A time series representing the EMA values.

HMA

• Calculates the Hull Moving Average (HMA) using weighted moving averages.
• Parameters:
  • dataset (pd.Series): The input time series data.
  • period (int): The period over which to calculate the HMA.
• Returns:
  • pd.Series: A time series representing the HMA values.

SMMA

• Calculates the Smoothed Moving Average (SMMA) using exponential smoothing.
• Parameters:
  • dataset (pd.Series): The input time series data.
  • period (int): The period over which to calculate the SMMA.
  • adjust (bool): Whether to adjust the SMMA calculation. Default is True.
• Returns:
  • pd.Series: A time series representing the SMMA values.

TEMA

• Calculates the Triple Exponential Moving Average (TEMA) using triple exponential smoothing.
• Parameters:
  • dataset (pd.Series): The input time series data.
  • period (int): The period over which to calculate the TEMA.
  • adjust (bool): Whether to adjust the TEMA calculation. Default is True.
• Returns:
  • pd.Series: A time series representing the TEMA values.

WMA

• Calculates the Weighted Moving Average (WMA) using weighted averages.
• Parameters:
  • dataset (pd.Series): The input time series data.
  • period (int): The period over which to calculate the WMA.
• Returns:
  • pd.Series: A time series representing the WMA values.