accessibility of daily moving average: Issue to get the current(today data if period is day) data ?

lf263820

I have created a daily moving average variable. But I could not get the current moving average data when the period is day. I am able to get yesterday moving average. Here is below for the code.

def on_start(self, md, order, service, account):

    daily_bars = md.bar.daily(start=-200)        ###moving average  0 for simple, 1 for ema
    dclose     = daily_bars.close

    self.realSMA21  = talib.MA(dclose , timeperiod=21, matype=0)
    self.realSMA50  = talib.MA(dclose , timeperiod=50, matype=0)

I can get access to self.realSMA21[-1] (yesterday MA) but self.realSMA21[0] gives NAN so how to get access to today MA data?

Leon

ptunney

A daily moving average is based on close prices..

So a 20 day MA price is the moving average of the previous 20 days.

It is super simple to calculate, you do not need TALIB, just sum the close prices for the last 20 days and divide by 20 (make sure you have 20 items in your list!!).

If you want it for the day before that, sum the close prices for the 20 days prior to that and divide by 20, easy.

Most of the time, for model decision making, when using a 20 day MA you are looking at something like.. current price is above or below the 20 day moving average price. ie the MA of the PREVIOUS 20 days.. You can't include today because you don't know today's close price until 4pm.
At the start of any day you do not have a close price for that day. If you did you would be forward-looking, that's a no, no.

So asking for the MA price for today is mute...

Now, saying that, there is a way of getting a 20 day MA including today.. live... you simply fold in the last traded price, put it as the last price in the list before you do your calculation.

But your code shows you are doing the calculation in on_start.. and depending on when you start your script and what type of symbol you are looking at you may not have a LAST price.

I am assuming you are doing some kind of beginning of the day calcuation.. if the price today is above or below the 20 day MA price then do this.

Hopefully this helps!

Paul

Some code!

from cloudquant.interfaces import Strategy
import talib
import numpy

class MovingAverage(Strategy):

    @classmethod
    def is_symbol_qualified(cls, symbol, md, service, account):
        return symbol== 'SPY'

    def on_start(self, md, order, service, account):
        print self.symbol

        # First we need some historic data so lets grab 30 daily bars
        daily_bars = md.bar.daily(start=-30,include_empty=False) 

        # most TALIB calls use OHLC (Open, High, Low, Close) in some form so lets pull those out so we have them ready
        open = daily_bars.open   
        high = daily_bars.high   
        low = daily_bars.low     
        close = daily_bars.close 
        volume = daily_bars.volume

        # TALIB.MA - Moving Average - matype=0 by default...
        # 0 = SMA (Simple Moving Average) (Default)
        # 1 = EMA (Exponential Moving Average)
        # 2 = WMA (Weighted Moving Average)
        # 3 = DEMA (Double Exponential Moving Average)
        # 4 = TEMA (Triple Exponential Moving Average)
        # 5 = TRIMA (Triangular Moving Average)
        # 6 = KAMA (Kaufman Adaptive Moving Average)
        # 7 = MAMA (MESA Adaptive Moving Average)
        # 8 = T3 (Triple Exponential Moving Average)            

        SMA = talib.MA(close,timeperiod=20)
        SMAlist = numpy.ndarray.tolist(SMA) 
        print "Simple Moving Average",SMAlist

        EMA = talib.MA(close,timeperiod=20,matype=1)
        EMAlist = numpy.ndarray.tolist(EMA) 
        print "Exponential Moving Average",EMAlist

        print "Simple Moving Average      (last 3 entries)",SMAlist[-3:]
        print "Exponential Moving Average (last 3 entries)",EMAlist[-3:]
        print "Average of last 20 close prices",sum(close[-20:])/len(close[-20:])
        print "Last Three close prices...", round(close[-3],2), round(close[-2],2), round(close[-1],2)
        print "last 20 close prices...",close[-20:]
        print
        service.terminate()
        return 

run on 12/23/2018 that that outputs the previous 20 days SPY close prices as follows...

283.2999878
286.5799866
284.6799927
281.7600098
281.8999939
281.5799866
275.4500122
263.9299927
269.1300049
267.6700134
257.6300049
261.5
265.3399963
266
269.5899963
273.0299988
273.1099854
271.3999939
270.0499878
270.3999939
SUM TOTAL 5454.029938 / 20 days = 272.7014969