How to Plot results from backtest in research.ipynb

Hello Brendon,

To programmatically analyze orders, you can use the read_backtest_orders method or the /backtests/orders/read endpoint as mentioned in the QuantConnect documentation. This allows you to access the orders generated by your backtest.

To create a candlestick plot with buy and sell markers, you can use the plotly library as shown in the QuantConnect documentation. Here is a code snippet from the documentation:

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)

Regarding your question about creating your algorithm in the research notebook, you can use the QuantBook class to access data and perform analysis. You can then use this analysis to inform the design of your algorithm. However, to actually execute the algorithm, you would need to use the main.py file.

I hope this helps! Let me know if you have any other questions.