Hi! I’m trying to calculate Connor’s RSI (CRSI). I’m trying to do it this way. RSI and ROC give correct results, but due to streaks I get incorrect results for CRSI. Does anyone know how to calculate it correctly?
def get_streaks_rsi(self, closing_prices, length):
# logic tables
series = pd.DataFrame(closing_prices)
geq = series >= series.shift(1) # True if rising
eq = series == series.shift(1) # True if equal
logic_table = pd.concat([geq, eq], axis=1)
streaks = [0] # holds the streak duration, starts with 0
for row in logic_table.iloc[1:].itertuples(): # iterate through logic table
if row[2]: # same value as before
streaks.append(0)
continue
last_value = streaks[-1]
if row[1]: # higher value than before
streaks.append(last_value + 1 if last_value >= 0 else 1) # increase or reset to +1
else: # lower value than before
streaks.append(last_value - 1 if last_value < 0 else -1) # decrease or reset to -1
streaks_numpy = np.array(streaks, dtype=np.float)
streaks_rsi = talib.RSI(streaks_numpy, length)
return streaks_rsi[-1]
def get_connors_rsi(self, a, b, c):
candles = self.client.futures_klines(symbol=self.symbol,
interval=self.candles_time,
limit=1500)
closing_prices = np.array([float(candle[4]) for candle in candles])
first_rsi = self.get_rsi(closing_prices, a)
print('RSI:', first_rsi)
second_rsi = self.get_streaks_rsi(closing_prices, b)
print('STREAKS:', second_rsi)
third_rsi = self.get_percent_rank(closing_prices, c)
print('PERCENT_RANK:', third_rsi)
connors_rsi = (first_rsi + second_rsi + third_rsi) / 3
print('CONNORS RSI:', connors_rsi)
return connors_rsi