import argparse import pandas_ta as ta from helper_funcs import * from pandas.plotting import register_matplotlib_converters register_matplotlib_converters() # ----------------------------------------------------- ADX ----------------------------------------------------- def adx(l_args, s_ticker, s_interval, df_stock): parser = argparse.ArgumentParser(prog='adx', description=""" The ADX is a Welles Wilder style moving average of the Directional Movement Index (DX). The values range from 0 to 100, but rarely get above 60. To interpret the ADX, consider a high number to be a strong trend, and a low number, a weak trend. """) parser.add_argument('-l', "--length", action="store", dest="n_length", type=check_positive, default=14, help='length') parser.add_argument('-s', "--scalar", action="store", dest="n_scalar", type=check_positive, default=100, help='scalar') parser.add_argument('-d', "--drift", action="store", dest="n_drift", type=check_positive, default=1, help='drift') parser.add_argument('-o', "--offset", action="store", dest="n_offset", type=check_positive, default=0, help='offset') try: (ns_parser, l_unknown_args) = parser.parse_known_args(l_args) if l_unknown_args: print(f"The following args couldn't be interpreted: {l_unknown_args}\n") return # Daily if s_interval == "1440min": df_ta = ta.adx(high=df_stock['2. high'], low=df_stock['3. low'], close=df_stock['5. adjusted close'], length=ns_parser.n_length, scalar=ns_parser.n_scalar, drift=ns_parser.n_drift, offset=ns_parser.n_offset).dropna() plt.subplot(211) plt.plot(df_stock.index, df_stock['5. adjusted close'].values, 'k', lw=2) plt.title(f"Average Directional Movement Index (ADX) on {s_ticker}") plt.xlim(df_stock.index[0], df_stock.index[-1]) plt.ylabel(f'Share Price ($)') plt.grid(b=True, which='major', color='#666666', linestyle='-') plt.minorticks_on() plt.grid(b=True, which='minor', color='#999999', linestyle='-', alpha=0.2) plt.subplot(212) plt.plot(df_ta.index, df_ta.iloc[:,0].values, 'b', lw=2) plt.plot(df_ta.index, df_ta.iloc[:,1].values, 'g', lw=1) plt.plot(df_ta.index, df_ta.iloc[:,2].values, 'r', lw=1) plt.xlim(df_stock.index[0], df_stock.index[-1]) plt.axhline(25, linewidth=3, color='k', ls='--') plt.legend([f'ADX ({df_ta.columns[0]})', f'+DI ({df_ta.columns[1]})', f'- DI ({df_ta.columns[2]})']) plt.xlabel('Time') plt.grid(b=True, which='major', color='#666666', linestyle='-') plt.minorticks_on() plt.grid(b=True, which='minor', color='#999999', linestyle='-', alpha=0.2) plt.ylim([0, 100]) plt.show() # Intraday else: df_ta = ta.adx(high=df_stock['2. high'], low=df_stock['3. low'], close=df_stock['4. close'], length=ns_parser.n_length, scalar=ns_parser.n_scalar, drift=ns_parser.n_drift, offset=ns_parser.n_offset).dropna() plt.subplot(211) plt.plot(df_stock.index, df_stock['4. close'].values, 'k', lw=2) plt.title(f"Average Directional Movement Index (ADX) on {s_ticker}") plt.xlim(df_stock.index[0], df_stock.index[-1]) plt.ylabel(f'Share Price ($)') plt.grid(b=True, which='major', color='#666666', linestyle='-') plt.minorticks_on() plt.grid(b=True, which='minor', color='#999999', linestyle='-', alpha=0.2) plt.subplot(212) plt.plot(df_ta.index, df_ta.iloc[:,0].values, 'b', lw=2) plt.plot(df_ta.index, df_ta.iloc[:,1].values, 'g', lw=1) plt.plot(df_ta.index, df_ta.iloc[:,2].values, 'r', lw=1) plt.xlim(df_stock.index[0], df_stock.index[-1]) plt.axhline(25, linewidth=3, color='k', ls='--') plt.legend([f'ADX ({df_ta.columns[0]})', f'+DI ({df_ta.columns[1]})', f'- DI ({df_ta.columns[2]})']) plt.xlabel('Time') plt.grid(b=True, which='major', color='#666666', linestyle='-') plt.minorticks_on() plt.grid(b=True, which='minor', color='#999999', linestyle='-', alpha=0.2) plt.ylim([0, 100]) plt.show() print("") except: print("") # ----------------------------------------------------- AROON ----------------------------------------------------- def aroon(l_args, s_ticker, s_interval, df_stock): parser = argparse.ArgumentParser(prog='aroon', description=""" The word aroon is Sanskrit for "dawn's early light." The Aroon indicator attempts to show when a new trend is dawning. The indicator consists of two lines (Up and Down) that measure how long it has been since the highest high/lowest low has occurred within an n period range. \n \n When the Aroon Up is staying between 70 and 100 then it indicates an upward trend. When the Aroon Down is staying between 70 and 100 then it indicates an downward trend. A strong upward trend is indicated when the Aroon Up is above 70 while the Aroon Down is below 30. Likewise, a strong downward trend is indicated when the Aroon Down is above 70 while the Aroon Up is below 30. Also look for crossovers. When the Aroon Down crosses above the Aroon Up, it indicates a weakening of the upward trend (and vice versa). """) parser.add_argument('-l', "--length", action="store", dest="n_length", type=check_positive, default=25, help='length') parser.add_argument('-s', "--scalar", action="store", dest="n_scalar", type=check_positive, default=100, help='scalar') parser.add_argument('-o', "--offset", action="store", dest="n_offset", type=check_positive, default=0, help='offset') try: (ns_parser, l_unknown_args) = parser.parse_known_args(l_args) if l_unknown_args: print(f"The following args couldn't be interpreted: {l_unknown_args}\n") return df_ta = ta.aroon(high=df_stock['2. high'], low=df_stock['3. low'], length=ns_parser.n_length, scalar=ns_parser.n_scalar, offset=ns_parser.n_offset).dropna() plt.subplot(311) # Daily if s_interval == "1440min": #plot_stock_and_ta(df_stock['5. adjusted close'], s_ticker, df_ta.iloc[:,-1], "AROON") plt.plot(df_stock.index, df_stock['5. adjusted close'].values, 'k', lw=2) # Intraday else: #plot_stock_and_ta(df_stock['4. close'], s_ticker, df_ta.iloc[:,-1], "AROON") plt.plot(df_stock.index, df_stock['4. close'].values, 'k', lw=2) plt.title(f"Aroon on {s_ticker}") plt.xlim(df_stock.index[0], df_stock.index[-1]) plt.ylabel(f'Share Price ($)') plt.grid(b=True, which='major', color='#666666', linestyle='-') plt.minorticks_on() plt.grid(b=True, which='minor', color='#999999', linestyle='-', alpha=0.2) plt.subplot(312) plt.plot(df_ta.index, df_ta.iloc[:,0].values, 'r', lw=2) plt.plot(df_ta.index, df_ta.iloc[:,1].values, 'g', lw=2) plt.xlim(df_stock.index[0], df_stock.index[-1]) plt.axhline(50, linewidth=1, color='k', ls='--') plt.legend([f'Aroon DOWN ({df_ta.columns[0]})', f'Aroon UP ({df_ta.columns[1]})']) plt.grid(b=True, which='major', color='#666666', linestyle='-') plt.minorticks_on() plt.grid(b=True, which='minor', color='#999999', linestyle='-', alpha=0.2) plt.ylim([0, 100]) plt.subplot(313) plt.plot(df_ta.index, df_ta.iloc[:,2].values, 'b', lw=2) plt.xlabel('Time') plt.legend([f'Aroon OSC ({df_ta.columns[2]})']) plt.grid(b=True, which='major', color='#666666', linestyle='-') plt.minorticks_on() plt.grid(b=True, which='minor', color='#999999', linestyle='-', alpha=0.2) plt.ylim([-100, 100]) plt.show() print("") except: print("")