Module marketools.analysis.rsi
Expand source code
import pandas as pd
def relative_strength_index(prices: pd.DataFrame, window: int = 14):
"""
Calculates Relative Strength Index (RSI).
Parameters
----------
prices : pandas.DataFrame
DataFrame with 'Close' column containing closing prices of stock
window : int
size of the moving window.
Returns
-------
pandas.Series
"""
price_now = prices['Close']
price_prev = prices['Close'].shift(periods=1, fill_value=0) # assign to each day price from the previous day
price_changes = pd.DataFrame(columns=['Up', 'Down'])
price_changes['Up'] = price_now - price_prev # upward changes
price_changes['Down'] = price_prev - price_now # downward changes
price_changes[price_changes < 0] = 0
smma = price_changes.ewm(alpha=1/window, adjust=False).mean() # smoothed moving averages, alpha = 1/N (not 2/(N+1))
rs = smma['Up'] / smma['Down']
output_rsi = -100 / (rs+1)
output_rsi = output_rsi + 100
output_rsi = output_rsi.rename('RSI')
return output_rsi
def rsi_cross_signals(rsi_values: pd.Series,
cross_line: float,
direction: str='rise'):
"""
Calculates buy/sell signals for given RSI signal line. Returns table with
True values for days when signal appears.
Parameters
----------
rsi_values : pandas.Series
DataFrame with RSI column
cross_line : float
signal threshold line, when signal line crosses this line signal is set
direction : str
direction the signal line should cross threshold line
('rise' - signal increasing [default], 'fall' - signal decreasing)
Returns
-------
pandas.Series
"""
if not (0 < cross_line < 100):
raise ValueError('cross_line takes values from 0 to 100')
rsi_copy = pd.DataFrame()
rsi_copy['RSI'] = rsi_values
rsi_copy['RSI day before'] = rsi_values.shift(1)
if 'rise' == direction:
# True signal if RSI is increasing and crossing the threshold line
output = (rsi_copy['RSI'] >= cross_line ) & (rsi_copy['RSI day before'] < cross_line)
elif 'fall' == direction:
# True signal if RSI is decreasing and crossing the threshold line
output = (rsi_copy['RSI'] <= cross_line ) & (rsi_copy['RSI day before'] > cross_line)
else:
raise ValueError('wrong value for direction, must be "rise" or "fall"')
output = output.rename(f'Cross signal ({cross_line} on {direction})')
return outputFunctions
def relative_strength_index(prices: pandas.core.frame.DataFrame, window: int = 14)-
Calculates Relative Strength Index (RSI).
Parameters
prices:pandas.DataFrame- DataFrame with 'Close' column containing closing prices of stock
window:int- size of the moving window.
Returns
pandas.Series
Expand source code
def relative_strength_index(prices: pd.DataFrame, window: int = 14): """ Calculates Relative Strength Index (RSI). Parameters ---------- prices : pandas.DataFrame DataFrame with 'Close' column containing closing prices of stock window : int size of the moving window. Returns ------- pandas.Series """ price_now = prices['Close'] price_prev = prices['Close'].shift(periods=1, fill_value=0) # assign to each day price from the previous day price_changes = pd.DataFrame(columns=['Up', 'Down']) price_changes['Up'] = price_now - price_prev # upward changes price_changes['Down'] = price_prev - price_now # downward changes price_changes[price_changes < 0] = 0 smma = price_changes.ewm(alpha=1/window, adjust=False).mean() # smoothed moving averages, alpha = 1/N (not 2/(N+1)) rs = smma['Up'] / smma['Down'] output_rsi = -100 / (rs+1) output_rsi = output_rsi + 100 output_rsi = output_rsi.rename('RSI') return output_rsi def rsi_cross_signals(rsi_values: pandas.core.series.Series, cross_line: float, direction: str = 'rise')-
Calculates buy/sell signals for given RSI signal line. Returns table with True values for days when signal appears.
Parameters
rsi_values:pandas.Series- DataFrame with RSI column
cross_line:float- signal threshold line, when signal line crosses this line signal is set
direction:str- direction the signal line should cross threshold line ('rise' - signal increasing [default], 'fall' - signal decreasing)
Returns
pandas.Series
Expand source code
def rsi_cross_signals(rsi_values: pd.Series, cross_line: float, direction: str='rise'): """ Calculates buy/sell signals for given RSI signal line. Returns table with True values for days when signal appears. Parameters ---------- rsi_values : pandas.Series DataFrame with RSI column cross_line : float signal threshold line, when signal line crosses this line signal is set direction : str direction the signal line should cross threshold line ('rise' - signal increasing [default], 'fall' - signal decreasing) Returns ------- pandas.Series """ if not (0 < cross_line < 100): raise ValueError('cross_line takes values from 0 to 100') rsi_copy = pd.DataFrame() rsi_copy['RSI'] = rsi_values rsi_copy['RSI day before'] = rsi_values.shift(1) if 'rise' == direction: # True signal if RSI is increasing and crossing the threshold line output = (rsi_copy['RSI'] >= cross_line ) & (rsi_copy['RSI day before'] < cross_line) elif 'fall' == direction: # True signal if RSI is decreasing and crossing the threshold line output = (rsi_copy['RSI'] <= cross_line ) & (rsi_copy['RSI day before'] > cross_line) else: raise ValueError('wrong value for direction, must be "rise" or "fall"') output = output.rename(f'Cross signal ({cross_line} on {direction})') return output