2. Simple equity basket strategy

A multi-instrument equity strategy in seven steps
In this example, you will create a simple basket strategy to hedge investment in Apple stock against market risk. The basket strategy will long Apple and short S&P 500 ETF.
In SigTech's Research environment, create a new notebook and run the following code blocks:
1. Set up environment
Note that for this tutorial we will need the pandas library:
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# Import necessary libraries
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import sigtech.framework as sig
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import datetime as dtm
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import pandas as pd
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from uuid import uuid4
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​
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# Initalise the environment
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sig.init()
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2. Define historical period
As you'll need to use the start and end dates multiple times, store them as variables:
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start_date = dtm.date(2016, 1, 1)
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end_date = dtm.date(2020, 12, 31)
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3. Define strategies and instruments
This time, you will define two ReinvestmentStrategy instances—one for the Apple stock and one for the S&P 500 ETF.
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apple_rs = sig.ReinvestmentStrategy(
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    start_date=start_date,
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    end_date=end_date,
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    currency='USD',
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    underlyer='1000045.SINGLE_STOCK.TRADABLE',
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    ticker=f'APPLE {str(uuid4())[:5]}'
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)
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​
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spy_rs = sig.ReinvestmentStrategy(
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    start_date=start_date,
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    end_date=end_date,
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    currency='USD',
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    underlyer='SPY UP EQUITY',
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    ticker=f'SPY {str(uuid4())[:5]}'
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)
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4. Build the BasketStrategy
The BasketStrategy building block is a strategy of strategies—it is a container for managing multiple sub-strategies. 
With the following code build a BasketStrategy to manage the two ReinvestmentStrategy instances created above:
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my_bs = sig.BasketStrategy(     
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    start_date=start_date,
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    end_date=end_date,
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​
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    # Long apple, short SPX, equal weighting
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    constituent_names=[apple_rs.name, spy_rs.name],
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    weights=[1, -1],
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​
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    # Rebalance the basket every month
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    rebalance_frequency='1M',
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​
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    currency='USD',
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    ticker=f'BASKET {str(uuid4())[:5]}',
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​
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    # Set the initial cash to be invested
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    initial_cash=1000,
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)
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5. Analyse performance in different ways
Plot the strategy's return
From a simple plot it looks like this strategy has performed well.
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my_bs.history().plot()
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Compare the strategy's return against a benchmark
As you will see from running this code, the return of your basket strategy is much worse than just investing in the Apple stock alone:
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# Compare the basket strategy's perfomance with that of the Apple stock alone
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pd.concat({
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    apple_rs.name:apple_rs.history(),
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    my_bs.name:my_bs.history()
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}, axis=1).dropna().plot()
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Compare the strategy's risk against a benchmark
Running the following two blocks of code will reveal deeper insights about the performance of both your basket strategy and the Apple stock. If you look at market risk instead of return, you can see that your basket strategy has partially hedged against market risk.
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my_bs.plot.performance()
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apple_rs.plot.performance()
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​👷
Your turn: customise the strategy
Add an additional instrument and indicate whether to long or short it.
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