ema_macd_rsi.py

import pandas as pd
import ta
import trading_strategies.visualise as v

# @author: vita

'''
This strategy combines ema_crossover_rsi_alternative and a modified ema_crossover_macd to determine buy and sell 
signals. Ema_crossover_macd was modified such that 9EMA only needs to be below/above 21EMA to fulfill sell/buy 
signals respectively rather than a crossover below or above. 
'''
class EMAMACDRSI:

    def __init__(self, file_path):
        self.df = pd.read_csv(file_path)
        # self.df = pd.DataFrame(inputs)
        self.close = self.df['close']

    def calculate_21_ema(self):
        self.df['21ema'] = self.df['close'].ewm(span=21, adjust=False).mean()

    def calculate_9_ema(self):
        self.df['9ema'] = self.df['close'].ewm(span=9, adjust=False).mean()

    def add_macd_diff(self):
        self.df['macd_histogram'] = ta.trend.MACD(close = self.close).macd_diff()

    def add_distance_between_21ema_and_close(self):
        self.df['distance'] = self.df['21ema'] - self.close

    def add_rsi(self):
        rsi_ind = ta.momentum.RSIIndicator(close=self.close, n=14)
        self.df['rsi'] = rsi_ind.rsi()

    def calculate_12_ema(self):
        self.df['12ema'] = self.df['close'].ewm(span=12, adjust=False).mean()

    def calculate_6_ema(self):
        self.df['6ema'] = self.df['close'].ewm(span=6, adjust=False).mean()

    def determine_signal(self, dframe):
        ema9 = dframe['9ema']
        ema21 = dframe['21ema']
        histogram = dframe['macd_histogram']
        close = dframe['close']
        ema6 = dframe['6ema']
        ema12 = dframe['12ema']
        rsi = dframe['rsi']

        action = 0

        # SELL CRITERIA: 9EMA crosses below 21EMA followed by a MACD histogram crossover into negatives
        if ((ema9.iloc[-2] < ema21.iloc[-2]) and (
                (histogram.iloc[-1] < 0 and histogram.iloc[-2] > 0) or (histogram.iloc[-1] > 0 and histogram.iloc[-2] < 0))) \
                or ((ema6.iloc[-1] < ema12.iloc[-1]) and (rsi.iloc[-1] < 50)):
            action = -1

        # BUY CRITERIA: 9EMA crosses above 21EMA followed by a MACD histogram crossover ito positives
        if ((ema9.iloc[-2] > ema21.iloc[-2]) and (
                (histogram.iloc[-1] > 0 and histogram.iloc[-2] < 0) or (histogram.iloc[-1] < 0 and histogram.iloc[-2] > 0))) \
                or ((ema6.iloc[-1] > ema12.iloc[-1]) and (rsi.iloc[-1] > 50)):
            action = 1

        return action, close.iloc[-1]-ema9.iloc[-1]

    def run_ema_macd_rsi(self):
        self.calculate_21_ema()
        self.calculate_9_ema()
        self.add_macd_diff()
        self.calculate_12_ema()
        self.calculate_6_ema()
        self.add_rsi()
        return self.determine_signal(self.df), self.df

    ''' The following methods are for plotting '''

    def find_all_signals(self, plot_df):
        # assign initial value of hold
        plot_df['signal'] = 0

        start = -1 * len(plot_df)
        end = start + 36

        # loop through data to determine all signals
        while end < 0:
            curr_window = plot_df[start:end]
            action = self.determine_signal(curr_window)[0]
            plot_df.loc[plot_df.index[end - 1], 'signal'] = action
            end += 1
            start += 1

        action = self.determine_signal(plot_df[-15:])[0]
        plot_df.loc[plot_df.index[-1], 'signal'] = action

    def plot_graph(self):
        # create shallow copy for plotting so as to not accidentally impact original df
        plot_df = self.df.copy(deep=False)

        self.find_all_signals(plot_df)

        plot_df = plot_df[120:220]

        # preparing values for horizontal line at rsi values 80 and 20 for visual purposes
        plot_df['50_line'] = 50

        # initialise visualisation object for plotting
        visualisation = v.Visualise(plot_df)

        # determining one buy signal example for plotting
        visualisation.determine_buy_marker()

        # determining one sell signal example for plotting
        visualisation.determine_sell_marker()

        # add subplots of RSI, 80 line and 20 line
        visualisation.add_subplot(plot_df['6ema'], panel=0, color='pink', width=0.75)
        visualisation.add_subplot(plot_df['12ema'], panel=0, color='b', width=0.75)
        visualisation.add_subplot(plot_df['rsi'], panel=1, color='m', width=0.75, ylabel='RSI')
        visualisation.add_subplot(plot_df['50_line'], panel=1, color='k', secondary_y=False, width=0.75,
                                  linestyle='solid')
        visualisation.add_subplot(plot_df['macd_histogram'], panel=2, color='b', type='bar')
        visualisation.add_subplot(plot_df['9ema'], panel=0, color='orange', width=0.75)
        visualisation.add_subplot(plot_df['21ema'], panel=0, color='turquoise', width=0.75)

        # create final plot with title
        visualisation.plot_graph("EMA with MACD and RSI strategy")