def get_data_from_yahoo(market_type="nyse", reload=False, rewrite=True):
if reload:
tickers = save_all_tickers()
else:
with open(market_type + "tickers.pickle", "rb") as f:
tickers = pickle.load(f)
if not os.path.exists("stock_" + market_type):
os.makedirs("stock_" + market_type)
start = dt.datetime(2019, 1, 1)
end = dt.datetime.now()
for ticker in tickers:
print(ticker)
ticker = ticker.strip("\n")
if "." in ticker and "HK" not in ticker:
ticker = ticker.replace(".", "-")
#print(ticker)
# just in case your connection breaks, we'd like to save our progress!
if not os.path.exists("stock_" + market_type +
"/{}.csv".format(ticker)) or rewrite:
try:
#df = web.DataReader(ticker, 'yahoo', start, end)
#iex-tops econdb
#df.reset_index(inplace=True)
#df.set_index("Date", inplace=True)
#df = df.drop("Symbol", axis=1)
df = yf.download(ticker, start=start, end=end)
# Initialize ATR Indicator
indicator_atr = AverageTrueRange(high=df["High"],
low=df["Low"],
close=df["Close"])
# Add ATR
df['ATR'] = indicator_atr.average_true_range()
# Initialize ATR Indicator
indicator_atr_2 = AverageTrueRange(high=df["ATR"],
low=df["ATR"],
close=df["ATR"])
# Add ATR
df['ATR_2'] = indicator_atr_2.average_true_range()
df.to_csv("stock_" + market_type + "/{}.csv".format(ticker))
except:
continue
else:
print('Already have {}'.format(ticker))
def _get_all_ST(self) -> pd.DataFrame:
"""
ST Indicator, trading predictions, ST high/low
"""
m = self.close.size
dir_, trend = [1] * m, [0] * m
long, short = [np.NaN] * m, [np.NaN] * m
ATR = AverageTrueRange(high=self.high,
low=self.low,
close=self.close,
window=self.length)
hl2_ = (self.high + self.low) / 2
matr = ATR.average_true_range() * self.multiplier
upperband = hl2_ + matr
lowerband = hl2_ - matr
for i in range(1, m):
if self.close.iloc[i] > upperband.iloc[i - 1]:
dir_[i] = BUY
elif self.close.iloc[i] < lowerband.iloc[i - 1]:
dir_[i] = SELL
else:
dir_[i] = dir_[i - 1]
if dir_[i] == BUY and lowerband.iloc[i] < lowerband.iloc[i -
1]:
lowerband.iloc[i] = lowerband.iloc[i - 1]
if dir_[i] == SELL and upperband.iloc[i] > upperband.iloc[i -
1]:
upperband.iloc[i] = upperband.iloc[i - 1]
if dir_[i] > 0:
trend[i] = long[i] = lowerband.iloc[i]
else:
trend[i] = short[i] = upperband.iloc[i]
# Prepare DataFrame to return
df = pd.DataFrame(
{
f"ST": trend,
f"ST_strategy": dir_,
f"ST_lower": long,
f"ST_upper": short,
},
index=self.close.index)
return df
def supertrend(df:pd.DataFrame, period=10, multiplier=3)->pd.DataFrame:
#basic upper band = (high + low)/2 + (multipler * atr)
#basic lower band = (high + low)/2 - (multipler * atr)
atr = AverageTrueRange(high=df['high'], low=df['low'], close=df['close'], window=14)
df['atr'] = atr.average_true_range()
df['st_upperband'] = ((df['high']+df['low'])/2 + (multiplier*df['atr']))
df['st_lowerband'] = ((df['high']+df['low'])/2 - (multiplier*df['atr']))
df['in_uptrend'] = True
for current in range(1, len(df.index)):
previous = current-1
if df['close'][current] > df['st_upperband'][previous]:
df['in_uptrend'][current] = True
elif df['close'][current] < df['st_lowerband'][previous]:
df['in_uptrend'][current] = False
else:
df['in_uptrend'][current] = df['in_uptrend'][previous]
if df['in_uptrend'][current] and df['st_lowerband'][current] < df['st_lowerband'][previous]:
df['st_lowerband'][current] = df['st_lowerband'][previous]
if not df['in_uptrend'][current] and df['st_upperband'][current] > df['st_upperband'][previous]:
df['st_upperband'][current] = df['st_upperband'][previous]
return df