首先，必须要说明的是，这个不影响 pyfolio 的正常使用。可以忽略或者使用忽略
import warnings
warnings.filterwarnings("ignore") 接下来，梳理一下，为啥会出现这样的警告信息。后面的大家不用看了，几乎没啥含金量。
pyfolio 和 zipline 都来自过去著名的量化平台 quantopian，zipline 是其回测和交易框架，pyfolio 是其绩效分析框架，pyfolio 是对 zipline 的支持，所以，虽然 zipline 和 pyfolio 都已经开源了，但是 pyfolio 还是保存着一些从 zipline 获取的依赖信息。
pos.py 中 import zipline.assets 中的 Equty 和 Future，用于确定资产的杠杆，如果没有 zipline 这个，资产的倍数就按照 1 倍来计算。实际上，我们从 backtrader 中的 analyzer 中获取的 postions 的信息是已经计算过杠杆的了，所以，这里不用考虑杠杆。
try:
from zipline.assets import Equity, Future
ZIPLINE = True
except ImportError:
ZIPLINE = False
warnings.warn(
'Module "zipline.assets" not found; mutltipliers will not be applied' +
' to position notionals.'
)
def extract_pos(positions, cash):
"""
Extract position values from backtest object as returned by
get_backtest() on the Quantopian research platform.
Parameters
----------
positions : pd.DataFrame
timeseries containing one row per symbol (and potentially
duplicate datetime indices) and columns for amount and
last_sale_price.
cash : pd.Series
timeseries containing cash in the portfolio.
Returns
-------
pd.DataFrame
Daily net position values.
- See full explanation in tears.create_full_tear_sheet.
"""
positions = positions.copy()
positions['values'] = positions.amount * positions.last_sale_price
cash.name = 'cash'
values = positions.reset_index().pivot_table(index='index',
columns='sid',
values='values')
if ZIPLINE:
for asset in values.columns:
if type(asset) in [Equity, Future]:
values[asset] = values[asset] * asset.price_multiplier
values = values.join(cash).fillna(0)
# NOTE: Set name of DataFrame.columns to sid, to match the behavior
# of DataFrame.join in earlier versions of pandas.
values.columns.name = 'sid'
return values 在 utils.py 中，有下面的几个函数:
第一个用于标准化资产的名字，第二个用于从 zipline 的回测结果中提收益率、持仓、交易和杠杆信息，在使用 pyfolio 对接 backtrader 的时候，我们是直接从 backtrader 的 analyzer 中直接获取的，没有用到 zipline.
def format_asset(asset):
"""
If zipline asset objects are used, we want to print them out prettily
within the tear sheet. This function should only be applied directly
before displaying.
"""
try:
import zipline.assets
except ImportError:
return asset
if isinstance(asset, zipline.assets.Asset):
return asset.symbol
else:
return asset
def extract_rets_pos_txn_from_zipline(backtest):
"""
Extract returns, positions, transactions and leverage from the
backtest data structure returned by zipline.TradingAlgorithm.run().
The returned data structures are in a format compatible with the
rest of pyfolio and can be directly passed to
e.g. tears.create_full_tear_sheet().
Parameters
----------
backtest : pd.DataFrame
DataFrame returned by zipline.TradingAlgorithm.run()
Returns
-------
returns : pd.Series
Daily returns of strategy.
- See full explanation in tears.create_full_tear_sheet.
positions : pd.DataFrame
Daily net position values.
- See full explanation in tears.create_full_tear_sheet.
transactions : pd.DataFrame
Prices and amounts of executed trades. One row per trade.
- See full explanation in tears.create_full_tear_sheet.
Example (on the Quantopian research platform)
---------------------------------------------
>>> backtest = my_algo.run()
>>> returns, positions, transactions =
>>> pyfolio.utils.extract_rets_pos_txn_from_zipline(backtest)
>>> pyfolio.tears.create_full_tear_sheet(returns,
>>> positions, transactions)
"""
backtest.index = backtest.index.normalize()
if backtest.index.tzinfo is None:
backtest.index = backtest.index.tz_localize('UTC')
returns = backtest.returns
raw_positions = []
for dt, pos_row in backtest.positions.iteritems():
df = pd.DataFrame(pos_row)
df.index = [dt] * len(df)
raw_positions.append(df)
if not raw_positions:
raise ValueError("The backtest does not have any positions.")
positions = pd.concat(raw_positions)
positions = pos.extract_pos(positions, backtest.ending_cash)
transactions = txn.make_transaction_frame(backtest.transactions)
if transactions.index.tzinfo is None:
transactions.index = transactions.index.tz_localize('utc')
return returns, positions, transactions