code: def benchmark_3():
      # Similar to benchmark_1, but with trading in only a small subset of assets
      # However, because the "multipier" is used, we can't just pass the string
      # names to the constructor, and so the solution is to use the lazy_add flag.
      # Changing lazy_add to False demonstrates the performance gain.
      # i.e. on Win32, it went from 4.3s with the flag to 10.9s without.
  
      x = np.random.randn(10000, 1000) * 0.01
      idx = pd.date_range("1990-01-01", freq="B", periods=x.shape[0])
      data = np.exp(pd.DataFrame(x, index=idx).cumsum())
      children = [
          bt.Security(name=i, multiplier=10, lazy_add=False)
          for i in range(1000)
      ]
      s = bt.Strategy(
          "s",
          [
              bt.algos.RunMonthly(),
              bt.algos.SelectThese([0, 1]),
              bt.algos.WeighRandomly(),
              bt.algos.Rebalance(),
          ],
          children=children,
      )
  
      t = bt.Backtest(s, data)
      return bt.run(t)
  
imports: import numpy
  import pandas
  import bt
  import cProfile
label_desc: Use image node_id 3 for calling a global function with example usage: benchmark_3() and returns: bt