Meta Analysis

To get the results of a backtest, call the ReadBacktest method with the project Id and backtest ID.

#load "../Initialize.csx"
#load "../QuantConnect.csx"

using QuantConnect;
using QuantConnect.Api;

var backtest = api.ReadBacktest(projectId, backtestId);

backtest = api.ReadBacktest(project_id, backtest_id)

To get the project Id, open the project in the Algorithm Lab and check the URL. For example, the project Id of https://www.quantconnect.com/project/13946911 is 13946911.

To get the backtest Id, open a backtest result in the Algorithm Lab and check the last line of its log file. An example backtest Id is 97e7717f387cadd070e4b77015aacece.

Note that this method returns a snapshot of the backtest at the current moment. If the backtest is still executing, the result won't include all of the backtest data.

The ReadBacktest method returns a Backtest object, which have the following attributes:

Follow these steps to plot the daily order fills of a backtest:

• Get the backtest orders.

orders = api.ReadBacktestOrders(project_id, backtest_id)

To get the project Id, open the project in the Algorithm Lab and check the URL. For example, the project Id of https://www.quantconnect.com/project/13946911 is 13946911.

To get the backtest Id, open a backtest result in the Algorithm Lab and check the last line of its log file. An example backtest Id is 97e7717f387cadd070e4b77015aacece.

The ReadBacktestOrders method returns a list of Order objects, which have the following properties:

• Organize the trade times and prices for each security into a dictionary.

  class OrderData:
      def __init__(self):
          self.buy_fill_times = []
          self.buy_fill_prices = []
          self.sell_fill_times = []
          self.sell_fill_prices = []
  
  order_data_by_symbol = {}
  for order in orders:
      if order.Symbol not in order_data_by_symbol:
          order_data_by_symbol[order.Symbol] = OrderData()
      order_data = order_data_by_symbol[order.Symbol]
      is_buy = order.Quantity > 0
      (order_data.buy_fill_times if is_buy else order_data.sell_fill_times).append(order.LastFillTime.date())
      (order_data.buy_fill_prices if is_buy else order_data.sell_fill_prices).append(order.Price)

• Get the price history of each security you traded.

  qb = QuantBook()
  start_date = datetime.max.date()
  end_date = datetime.min.date()
  for symbol, order_data in order_data_by_symbol.items():
      start_date = min(start_date, min(order_data.buy_fill_times), min(order_data.sell_fill_times))
      end_date = max(end_date, max(order_data.buy_fill_times), max(order_data.sell_fill_times))
  start_date -= timedelta(days=1)
  all_history = qb.History(list(order_data_by_symbol.keys()), start_date, end_date, Resolution.Daily)

• Create a candlestick plot for each security and annotate each plot with buy and sell markers.

  import plotly.express as px
  import plotly.graph_objects as go
  
  for symbol, order_data in order_data_by_symbol.items():
      history = all_history.loc[symbol]
  
      # Plot security price candlesticks
      candlestick = go.Candlestick(x=history.index,
                                  open=history['open'],
                                  high=history['high'],
                                  low=history['low'],
                                  close=history['close'],
                                  name='Price')
      layout = go.Layout(title=go.layout.Title(text=f'{symbol.Value} Trades'),
                      xaxis_title='Date',
                      yaxis_title='Price',
                      xaxis_rangeslider_visible=False,
                      height=600)
      fig = go.Figure(data=[candlestick], layout=layout)
  
      # Plot buys
      fig.add_trace(go.Scatter(
          x=order_data.buy_fill_times,
          y=order_data.buy_fill_prices,
          marker=go.scatter.Marker(color='aqua', symbol='triangle-up', size=10),
          mode='markers',
          name='Buys',
      ))
  
      # Plot sells
      fig.add_trace(go.Scatter(
          x=order_data.sell_fill_times,
          y=order_data.sell_fill_prices,
          marker=go.scatter.Marker(color='indigo', symbol='triangle-down', size=10),
          mode='markers',
          name='Sells',
      ))
  
  fig.show()



Note: The preceding plots only show the last fill of each trade. If your trade has partial fills, the plots only display the last fill.