I have been trying for hours to implement talib.RSI and failing. I have been trying to hack an algorithm that uses
context.stocks = symbols('IWM','RWM')
...
prices = history(15, '1d', 'price')
rsi = prices.apply(talib.RSI, timeperiod=14).iloc[-1] but I haven't been able to make that work for me, especially while using data.history method instead of just history (which is deprecated).
Does anyone know of any non-talib solutions to calculate RSI?
Thanks!
Jim,
talib RSI is working for me
import talib
def initialize(context):
context.stock = symbol('SPY')
schedule_function(trade, date_rules.every_day(), time_rules.market_close(minutes = 15))
def trade(context, data):
stock=context.stock
W = 50
UB = 65
LB =UB*0.8
C = data.history(stock, 'price',W+2, '1d')
# L = data.history(stock, 'low',W+2, '1d')
# H = data.history(stock, 'high',W+2, '1d')
rsi_one = talib.RSI(C, timeperiod=W)[-1]
rsi_two = talib.RSI(C, timeperiod=W)[-2]
record(RSI1=rsi_one, RSI2=rsi_two, ub=UB) Or use this:
#Relative Strength Index
def RSI(df, n):
i = 0
UpI = [0]
DoI = [0]
while i + 1 <= df.index[-1]:
UpMove = df.get_value(i + 1, 'High') - df.get_value(i, 'High')
DoMove = df.get_value(i, 'Low') - df.get_value(i + 1, 'Low')
if UpMove > DoMove and UpMove > 0:
UpD = UpMove
else: UpD = 0
UpI.append(UpD)
if DoMove > UpMove and DoMove > 0:
DoD = DoMove
else: DoD = 0
DoI.append(DoD)
i = i + 1
UpI = pd.Series(UpI)
DoI = pd.Series(DoI)
PosDI = pd.Series(pd.ewma(UpI, span = n, min_periods = n - 1))
NegDI = pd.Series(pd.ewma(DoI, span = n, min_periods = n - 1))
RSI = pd.Series(PosDI / (PosDI + NegDI), name = 'RSI_' + str(n))
df = df.join(RSI)
return df 
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