Imports & Functions Required For Backtests

Zipline Functions
- from zipline import run_algorithm #needed every time we run a backtest
- from zipline.api import order_target_percent #ability to place orders in terms of target percent
- from zipline.api import order_target #ability to place orders in terms of shares
- from zipline.api import symbol #ability to look at stocks based on ticker
- from zipline.api import record
- from zipline.api import set_benchmark
- from zipline.api import schedule_function
- from zipline.api import date_rules
- from zipline.api import time_rules

Visualization & Analysis
- import matplotlib.pyplot as plt
- import pyfolio as pf

Backtest Functions
- Initialize
  - Executed before the backtest starts
  - Sets the parameters
    - context.stock = symbol(‘AAPL’)
    - context.stocks_to_hold = 10
    - context.index_average_window = 100
    - set_benchmark(False)
    - schedule_function(handle_data, date_rules.month_start(), time_rules.market_close()) #Trading once per month
- Handle_data
  - Rules for when to buy, sell, and how much
- Analyze
  - Calculates analytics and visualize results
  - PyFolio has various types of built in tear sheets, ‘returns’ is one example
  - Custom analysis can be done by creating pie and bar charts using:
    - Make pie chart for allocations
      - fig, ax1 = plt.subplots(figsize=[12, 10])
      - ax1.pie(df[‘value’], labels=df.index, shadow=True, startangle=90)
      - ax1.axis(‘equal’)
      - ax1.set_title(‘Allocation on {}’.format(day))
      - plt.show()
    - Make bar chart for open PnL
      - fig, ax1 = plt.subplots(figsize=[12, 10])
      - pnl_df = df.drop(‘cash’)
      - ax1.barh( pnl_df.index, pnl_df[‘pnl’], align=’center’, color=’green’, ecolor=’black’)
      - ax1.set_title(‘Open PnL on {}’.format(day))
      - plt.show()