def cal_plot_cci(ticker, period):
print("Calculating CCI...")
stock_data = stock.stock_preprocess_arr_list(ticker)
cci = talib.CCI(stock_data[3], stock_data[4], stock_data[2], timeperiod=int(period))
##### plotting
fig, ax_list = plt.subplots(2, 1, figsize=(15,15))
name = stock.check_all_ticker(ticker)[0]
plt.suptitle('Commodity Channel Index {}({})'.format(name, ticker), fontsize = 20, fontweight='bold')
ax_list[0].plot(stock_data[0], stock_data[2], label='Price - '+name, color='black')
ax_list[0].get_xaxis().set_visible(False)
ax_list[1].plot(stock_data[0], cci, label='CCI - '+period+'-day period', color='#BB9F6D')
ax_list[1].axhline(y=100, color='red')
ax_list[1].axhline(y=-100, color='red')
for i in range(2):
ax_list[i].grid(True)
ax_list[i].legend()
ax_list[i].minorticks_on()
ax_list[i].tick_params(axis='x',which='minor',bottom='off')
fig.tight_layout()
fig.subplots_adjust(hspace=0, top=0.95)
#plt.show()
stock.save_plot('CCI', ticker)
def cal_plot_psar(ticker, step=0.02, max_step=0.2):
print("Calculating Parabolic SAR...")
stock_data = stock.stock_preprocess_arr_list(ticker)
psar = talib.SAR(stock_data[3],
stock_data[4],
acceleration=step,
maximum=max_step)
##### plotting
fig, ax = plt.subplots(1, 1, figsize=(15, 15))
name = stock.check_all_ticker(ticker)[0]
plt.suptitle('Parabolic Stop and Reverse of {}({})'.format(name, ticker),
fontsize=20,
fontweight='bold')
ax.plot(stock_data[0],
stock_data[2],
label='Price - ' + name,
color='black')
ax.plot(stock_data[0], psar, '.', label='Parabloic SAR', color='#708EB2')
ax.grid(True)
ax.legend()
ax.minorticks_on()
ax.tick_params(axis='x', which='minor', bottom='off')
fig.tight_layout()
fig.subplots_adjust(top=0.95)
#plt.show()
stock.save_plot('PSAR', ticker)
def get_client_tickers(cus_id):
id = 'scb_' + cus_id
customers_df = pd.read_csv(mp.DIR_DATA_CUSTOMERS +
'customer_trade_book.csv')
customers_df = customers_df[['ID', 'Symbol', 'Portfolio_Value']]
customers_df = customers_df[customers_df.ID == id]
customers_df = customers_df[customers_df.Portfolio_Value > 0]
ticker_list = list(set(customers_df['Symbol']))
if len(ticker_list) > 0:
ticker_list = [(4 - len(str(tk))) * '0' + str(tk) + '.HK'
for tk in ticker_list]
remove_tk_list = []
print("Customer {} has the following equities in his/her portfolio:".
format(id))
for i, tk in enumerate(sorted(ticker_list)):
found = stock.check_all_ticker(tk)
if found[1] == True:
print(str(i + 1) + ')', tk + ' - ' + found[0])
else:
print(str(i + 1) + ')', found[0])
remove_tk_list.append(tk)
for tk in remove_tk_list:
ticker_list.remove(tk)
print("\n")
return ticker_list
else:
return None
def cal_plot_rsi(ticker):
print("Calculating RSI...")
stock_data = stock.stock_preprocess_arr_list(ticker)
name = stock.check_all_ticker(ticker)[0]
rsi = talib.RSI(stock_data[2], timeperiod=14)
##### plotting
fig, ax_list = plt.subplots(2, 1, figsize=(15,15))
plt.suptitle('Relative Strength Index of {}({})'.format(name, ticker), fontsize = 20, fontweight='bold')
ax_list[0].plot(stock_data[0], stock_data[2], label='Price - '+name, color='black')
ax_list[1].plot(stock_data[0], rsi, label='RSI', color='#A139B3')
ax_list[1].fill_between(stock_data[0], 70, 30, color='#DED3E5')
ax_list[0].get_xaxis().set_visible(False)
for i in range(2):
ax_list[i].legend()
ax_list[i].grid(True)
ax_list[i].minorticks_on()
ax_list[i].tick_params(axis='x',which='minor',bottom='off')
ax_list[1].xaxis.set_major_locator(mdates.MonthLocator())
ax_list[1].xaxis.set_major_formatter(mdates.DateFormatter('%y-%b'))
fig.tight_layout()
fig.subplots_adjust(hspace=0, top=0.95)
#plt.show()
stock.save_plot('RSI', ticker)
def cal_plot_obv(ticker):
print("Calculating OBV...")
stock_data = stock.stock_preprocess_arr_list(ticker)
obv = talib.OBV(stock_data[2], stock_data[5].astype(float))
##### plotting
fig, ax_list = plt.subplots(2, 1, figsize=(15, 15))
name = stock.check_all_ticker(ticker)[0]
plt.suptitle('On-Balance Volume {}({})'.format(name, ticker),
fontsize=20,
fontweight='bold')
ax_list[0].plot(stock_data[0],
stock_data[2],
label='Price - ' + name,
color='black')
ax_list[0].get_xaxis().set_visible(False)
ax_list[1].plot(stock_data[0], obv, label='OBV', color='#BB9F6D')
for i in range(2):
ax_list[i].grid(True)
ax_list[i].legend()
ax_list[i].minorticks_on()
ax_list[i].tick_params(axis='x', which='minor', bottom='off')
fig.tight_layout()
fig.subplots_adjust(hspace=0, top=0.95)
#plt.show()
stock.save_plot('OBV', ticker)
def cal_plot_bband(ticker):
print("Calculating B-Bands...")
stock_data = stock.stock_preprocess_candlestick(ticker)
upper, middle, lower = talib.BBANDS(stock_data[2],
matype=talib.MA_Type.SMA)
##### plotting
fig, ax_list = plt.subplots(2, 1, figsize=(15, 15))
plt.suptitle('Bollinger Bands of {}({})'.format(
stock.check_all_ticker(ticker)[0], ticker),
fontsize=20,
fontweight='bold')
candlestick_ochl(ax_list[0],
stock_data[0],
width=0.8,
colorup='#53B987',
colordown='#EB4D5C')
ax_list[0].xaxis.set_major_locator(mdates.MonthLocator())
ax_list[0].xaxis.set_major_formatter(mdates.DateFormatter('%Y-%b-%d'))
ax_list[0].get_xaxis().set_visible(False)
volume_overlay(ax_list[1],
*stock_data[1:4],
width=0.8,
colorup='#53B987',
colordown='#EB4D5C')
#ax_list[1].xaxis.set_major_locator(mdates.MonthLocator())
#ax_list[1].xaxis.set_major_formatter(mdates.DateFormatter('%Y-%b-%d'))
ax_list[1].set_xticks(range(0, len(stock_data[4]), 30))
ax_list[1].set_xticklabels(stock_data[4][::30])
ax_list[0].plot(stock_data[4], upper, color='#85C0C0')
ax_list[0].plot(stock_data[4], middle, label='20-SMA', color='#AC7878')
ax_list[0].plot(stock_data[4], lower, color='#85C0C0')
ax_list[0].fill_between(stock_data[4], upper, lower, color='#F3F9F9')
for i in range(2):
ax_list[i].minorticks_on()
ax_list[i].tick_params(axis='x', which='minor', bottom='off')
ax_list[0].legend()
plt.setp(plt.gca().get_xticklabels())
fig.tight_layout()
fig.subplots_adjust(hspace=0, top=0.95)
#plt.show()
stock.save_plot('BBANDS', ticker)
def plot_HSI_MACD(arr_date, close_prices, avg_fast, avg_slow, macd, macd_signal, histogram, ticker, fast=12, slow=26, signal=9, type='EMA'):
fig, ax_list = plt.subplots(2, 2, figsize=(15,10))
if ticker == 'HSI':
plt.suptitle('MACD-related plots of {}'.format(ticker), fontsize = 20, fontweight='bold')
else:
plt.suptitle('MACD-related plots of {}({})'.format(stock.check_all_ticker(ticker)[0], ticker), fontsize = 20, fontweight='bold')
ax_list[0][0].set_title('{}-days and {}-days {}'.format(fast, slow, type), fontstyle='italic')
ax_list[0][0].plot(arr_date, close_prices, label='^HSI', color='black')
ax_list[0][0].plot(arr_date, avg_fast, label=str(fast)+'-days(fast)')
ax_list[0][0].plot(arr_date, avg_slow, label=str(slow)+'-days(slow)')
ax_list[0][1].set_title('MACD/DIF (EMA)', fontstyle='italic')
ax_list[0][1].plot(arr_date, macd, label='{}-days - {}-days'.format(fast, slow), color='xkcd:purple')
ax_list[0][1].axhline(y=0, color='red')
ax_list[1][0].set_title('MACD/DIF & {}day-Signal'.format(signal), fontstyle='italic')
ax_list[1][0].plot(arr_date, macd, label='MACD/DIF', color='xkcd:purple')
ax_list[1][0].plot(arr_date, macd_signal, label='Signal', color='xkcd:orange')
ax_list[1][0].fill_between(arr_date, histogram, label='MACD/DIF - Signal', color='gray')
ax_list[1][0].axhline(y=0, color='red')
ax_list[1][1].set_title('MACD Histogram', fontstyle='italic')
ax_list[1][1].fill_between(arr_date, histogram, label='MACD/DIF - Signal', color='C9')
ax_list[1][0].axhline(y=0, color='red')
for row in range(len(ax_list)):
for col in range(len(ax_list[0])):
ax_list[row][col].legend()
ax_list[row][col].grid(True)
ax_list[row][col].minorticks_on()
ax_list[row][col].tick_params(axis='x',which='minor',bottom='off')
ax_list[row][col].xaxis.set_major_locator(mdates.MonthLocator())
ax_list[row][col].xaxis.set_major_formatter(mdates.DateFormatter('%y-%b'))
for major_tick in ax_list[row][col].xaxis.get_ticklabels():
major_tick.set_rotation(40)
plt.tight_layout() # prevent overlapping
fig.subplots_adjust(top=0.9)
#plt.show()
stock.save_plot('MACD', ticker)
def cal_plot_kdj(ticker):
print("Calculating KDJ...")
stock_data = stock.stock_preprocess_arr_list(ticker)
k, d = talib.STOCH(stock_data[3],
stock_data[4],
stock_data[2],
fastk_period=14,
slowk_period=3,
slowk_matype=0,
slowd_period=3,
slowd_matype=0)
j = 3 * k - 2 * d
##### plotting
fig, ax_list = plt.subplots(2, 1, figsize=(15, 15))
name = stock.check_all_ticker(ticker)[0]
plt.suptitle('Stochastic with J Line of {}({})'.format(name, ticker),
fontsize=20,
fontweight='bold')
ax_list[0].plot(stock_data[0],
stock_data[2],
label='Price - ' + name,
color='black')
ax_list[0].get_xaxis().set_visible(False)
ax_list[1].plot(stock_data[0], k, label='%K', color='#DC9F86')
ax_list[1].plot(stock_data[0], d, label='%D', color='#13F90D')
ax_list[1].plot(stock_data[0], j, label='%J', color='#E06FC4')
for i in range(2):
ax_list[i].grid(True)
ax_list[i].legend()
ax_list[i].minorticks_on()
ax_list[i].tick_params(axis='x', which='minor', bottom='off')
fig.tight_layout()
fig.subplots_adjust(hspace=0, top=0.95)
#plt.show()
stock.save_plot('KDJ', ticker)