Historical data for indicators

After registering the indicators in the initialization step (using self.Indicator instead of qb.indicator), you can access it by calling the variable you assigned it to. For example,

self.STD = self.Indicator(StandardDeviation(36), spy.Symbol, start_time, end_time, Resolution.Minute)

for more info:

Excuse me Aaron, but "self.Indicator" is not supported in main.py.

Apologies, I should have done it in terms of RegisterIndicator (see this example in the docs )

where RegisterIndicator can be used with any of the following inputs:

Excuse me again Aaron, but I am not able to understand what do you mean.

* What statements is this ending in ":"? Is it an "if", or "for" or what?
self.RegisterIndicator(symbol, indicator, resolution = null):
    pass

* Should I write it in Initialize or in OnData?

* What consolidator are you talking about? Should I define a new one or it simulates one?

Could you show me an example, please?

I will be waiting for your answer

Thanks in advance and regards,

Apologies for any confusion,

1. In the above, the statements ending in ":" are the different ways to initialize an indicator from the self.Initialize portion of your algorithm. For example:

self.RegisterIndicator(spy.Symbol,StandardDeviation(36),Resolution.Minute)

was initialized using the form:

self.RegisterIndicator(symbol, indicator, resolution)

2. You register in Initialize. Following that, because OnData is called whenever new data is processed, this is when new data will be fed into the indicator.

3. In your example, no consolidator is needed. What a consolidator does is accumulate smaller resolutions of data in order to analyze them as TradeBars. For example, lets say I want to have each point of data for my indicator be the TradeBar (which allows us to look at its OHLC, volume, variance, etc) of thirty minutes. Note that there is no resolution of form "thirty minitues" -- there is minute data, second data, and hourly data, but to get an OHLC bar for each thirty minutes, I would need to accumulate minutely data.

Thus, I could write:

# request the equity data in minute resolution
self.AddEquity("SPY", Resolution.Minute)
# define a 10-period RSI indicator with indicator constructor
self.rsi = RelativeStrengthIndex(10, MovingAverageType.Simple)
# create the 30-minutes data consolidator
thirtyMinuteConsolidator = TradeBarConsolidator(timedelta(minutes=30))
self.SubscriptionManager.AddConsolidator("SPY", thirtyMinuteConsolidator)
# register the 30-minute consolidated bar data to automatically update the indicator
self.RegisterIndicator("SPY", self.rsi, thirtyMinuteConsolidator)

Dear Aaron,

I have tried to do my best up to where I understood you, but as you can see in the Debug file, the indicators value remain fixed without update themselves.

I attach backtest with the code..

I''l appreciate your new help.

Regards,

Mario

There seems to be a lot going on in your backtest. To keep it simple, I have attached one where

1. An indicator is registered + consolidated.

2. When the indicator is ready, it logs its current value.

where the initialization of the indicator is done using the code I sent beforehand. Hopefully this should make it clear exactly how to interact with a registered indicator. Note that it is getting the values without me needing to call "update"

Can't edit the prior post, but I have attached one here which logs less frequently than the backtest attached prior (so that you can conserve your log quota).

Hi Aaron,

it looks that I was not clear enough and we do not understand ouselves. Apologize for it.

I have found the solution after trying time after time, based on Update, as follow:

            start_time = datetime(2017, 7, 6, 9, 31) # start datetime for history call
            end_time = datetime(2017, 7, 6, 10, 39) # end datetime for history call
            df = self.History(["SPY"], start_time, end_time, Resolution.Minute)
            if not df.empty:
                history = df.loc["SPY"]
            history.drop(['askclose', 'askhigh', 'asklow', 'askopen', 'asksize', 'bidclose','bidhigh', 'bidlow', 'bidopen', 'bidsize', 'open', 'volume'], axis=1, inplace=True)
            for i in range(0,len(history)):
                if self.std.IsReady:
                    self.std.Update(history.index[i],history.loc[history.index[i],'close'])
                    history['STD']=self.std.Current.Value

Thanks anyway.

Best regards,

Mario

Dear Aaron,
I have tried to do what you have suggested to me, but I am getting only fixed values.
I'll really apprecite you new help.

    def Initialize(self):
        self.SetStartDate(2017, 7, 7)  # Set Start Date
        self.SetCash(100000)  # Set Strategy Cash
        self.AddEquity("SPY", Resolution.Minute)
        dict = {'close': [],
                'RSI': [],
        'EMA9': [], 
                }
        Tiempo=[]
        self.dfIndicators=pd.DataFrame(dict, index = Tiempo)
        self.rsi = self.RSI("SPY", 5)
        self.ema9 = self.EMA("SPY", 9)
        # create the 36-minutes data consolidator
        thirtyMinuteConsolidator = TradeBarConsolidator(timedelta(minutes=37))
        # create the 36-minutes data consolidator
        thirtyMinuteConsolidator = TradeBarConsolidator(timedelta(minutes=37))
        self.SubscriptionManager.AddConsolidator("SPY", thirtyMinuteConsolidator)
        # register the 30-minute consolidated bar data to automatically update the indicator
        self.RegisterIndicator("SPY", self.rsi, thirtyMinuteConsolidator)
        self.RegisterIndicator("SPY", self.ema9, thirtyMinuteConsolidator)

    def OnData(self, data):
        openhour = "10:08:51"
        openhour=parser.parse(openhour)
        tempodf = self.History(["SPY"], 390, Resolution.Minute)
        if not tempodf.empty: 
           history = tempodf.loc["SPY"]
           history.drop(['askclose', 'askhigh', 'asklow', 'askopen', 'asksize', 'bidclose','bidhigh', 'bidlow', 'bidopen', 'bidsize', 'open', 'low', 'high', 'volume'], axis=1, inplace=True) 
           for i in range(0,len(history)):
               horafila=history.index[i]
               if datetime.time(horafila) > datetime.time(openhour):
                  dictIndicators = {
                    'close': float(history.loc[history.index[i],'close']),
                    'RSI': float(self.rsi.Current.Value),
                    'EMA9': float(self.ema9.Current.Value),
                    'Tiempo': history.index[i]
                    }
                    self.dfIndicators=self.dfIndicators.append(dictIndicators,ignore_index=True)

OUTPUT:

same happens with other indicators I am trying to use liek BB, STD, MOM

                    Tiempo          close   RSI  MOM   EMA9       EMA36
180 2017-07-06 13:09:00 227.156097 100.0  0.0  226.789519  226.789519
181  2017-07-06 13:10:00 227.156097 100.0  0.0  226.789519  226.789519
182  2017-07-06 13:11:00 227.146698 100.0  0.0  226.789519  226.789519
183 2017-07-06 13:12:00 227.146698 100.0  0.0  226.789519  226.789519
184 2017-07-06 13:13:00 227.174896 100.0  0.0  226.789519  226.789519
185 2017-07-06 13:14:00 227.193695 100.0  0.0  226.789519  226.789519
186 2017-07-06 13:15:00 227.193695 100.0  0.0  226.789519  226.789519
187 2017-07-06 13:16:00 227.221893 100.0  0.0  226.789519  226.789519

Hi Mario,

The indicators aren't updated because `RegisterIndicator` needs to be passed a timedelta, not a `TradeBarConsolidator`. In addition, when consolidating data, we should use the full class name (`RelativeStrengthIndex`) instead of the shortcut methods (`self.RSI`). Otherwise, the indicator will be updated each minute bar and each consolidated bar.

See the attached backtest for a working example.

Best,
Derek Melchin