Strategy Lifecycle Structures¶

Core data structures automatically passed by the framework during strategy execution.

Context¶

Strategy execution context, automatically passed by the framework during callbacks.

Attribute	Type	Description
`current_dt`	`datetime`	Current simulation time
`start_date`	`date`	Backtest start date
`end_date`	`date`	Backtest end date
`frequency`	`str`	`'daily'` or `'minute'`
`portfolio`	`Portfolio`	Portfolio object
`universe`	`list[str]`	Current strategy stock universe
`run_params`	`dict`	Backtest parameter dictionary

Portfolio¶

Portfolio state, accessed via context.portfolio.

Attribute	Description	User Input
`starting_cash`	Initial capital	Set by `starting_cash` parameter
`available_cash`	Available cash	Automatically maintained by framework
`positions`	Position dictionary, keyed by stock code	Automatically maintained by framework
`total_value`	Total assets = cash + position market value	Automatically calculated by framework
`returns`	Total return	Read-only

Position¶

Individual stock position, accessed via context.portfolio.positions[code].

Attribute	Description	User Input
`security`	Stock code	Automatically set by framework
`amount`	Position amount (shares)	Automatically maintained by framework
`closeable_amount`	Amount available to sell today (T+1 restriction)	Automatically maintained by framework
`avg_cost`	Average cost	Automatically calculated by framework
`total_value`	Position market value	Automatically calculated by framework
`price`	Current price	Read-only

g — GlobalObject¶

Strategy-level global object for storing custom variables across trading days.

from eqlib import g

def initialize(context):
    g.security = '601390'
    g.ma_period = 20

def market_open(context):
    hist = attribute_history(g.security, g.ma_period, '1d', ['close'])