Overall Statistics
Total Orders
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Start Equity
100000.00
End Equity
100000
Net Profit
0%
Sharpe Ratio
0
Sortino Ratio
0
Probabilistic Sharpe Ratio
0%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
3.672
Tracking Error
0.05
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
Portfolio Turnover
0%
 
# region imports
from AlgorithmImports import *
# endregion

# Your New Python File

class TrailingDataSamplesHistoryAlgorithm(QCAlgorithm):

    def initialize(self) -> None:
        self.set_start_date(2021, 4, 30)
        self.set_end_date(2021, 5, 4)
        self.SetWarmUp(300)

        # Get the Symbol of an asset.
        self.ticker = 'EURHUF'
        self.symbol = self.add_forex(self.ticker, Resolution.DAILY).symbol
        self.sma200 = self.sma(self.symbol, 200, Resolution.DAILY)
        
        self.bar_period = timedelta(days=1)

        self.data = {}
        self.data[self.ticker] = SymbolData(self)

    def on_data(self, data):
        if self.is_warming_up: return

        if self.sma200.is_ready:
            # The current value of self.sma200 is represented by self.sma200.current.value
            self.plot("SimpleMovingAverage", "sma from automatic indicator", self.sma200.current.value)
            self.plot("SimpleMovingAverage", "sma from SymbolData (consolidated)", self.data[self.ticker].sma200.current.value)
            self.plot("SimpleMovingAverage", "sma from SymbolData registered with algorithm", self.data[self.ticker].sma200_algoregistered.current.value)

            if self.Time.date() == datetime(2021, 5, 2).date():
                history = self.history(self.symbol, 200, Resolution.DAILY)
                last = history['close'].rolling(200).mean().iloc[-1]
                self.log(f"sma from automatic indicator {self.sma200.current.value} , rolling sma from history call {last} , equal? {self.sma200.current.value == last}")
                self.log(f"sma from SymbolData (consolidated) {self.data[self.ticker].sma200} -> different from above? why?")
                self.log(f"sma from SymbolData registered with algorithm {self.data[self.ticker].sma200_algoregistered}")


class SymbolData:
    def __init__(self, algorithm):
        self.algorithm = algorithm
        self.bar_period = self.algorithm.bar_period
        self.bars = RollingWindow[QuoteBar](2)

        self.consolidator = QuoteBarConsolidator(self.bar_period)
        self.consolidator.data_consolidated += self.consolidation_handler
        self.algorithm.subscription_manager.add_consolidator(self.algorithm.symbol, self.consolidator)

        self.sma200 = SimpleMovingAverage(200)
        self.sma200_algoregistered = SimpleMovingAverage(200)
        self.algorithm.register_indicator(self.algorithm.ticker, self.sma200_algoregistered, Resolution.DAILY)
    
    def consolidation_handler(self, sender, bar: QuoteBar):
        self.bars.add(bar)
        self.sma200.update(bar.end_time, bar.close)