PortfolioStatistics

API documentation for tradeexecutor.state.statistics.PortfolioStatistics Python class in Trading Strategy framework.

class PortfolioStatistics

Bases: object

Portfolio statistics for each timepoint.

Updated with regular ticks for a live strategy.

If backtesting, only calculated_at and total_equity are necessary for later visualisations and metrics If livetrading, then all attributes should be specified so that for displaying updated metrics after each trade

See Statistics.portfolio for reading.

__init__(calculated_at, total_equity, net_asset_value=None, unrealised_profitability=None, free_cash=None, open_position_count=None, open_position_equity=None, frozen_position_count=None, frozen_position_equity=None, closed_position_count=None, unrealised_profit_usd=None, first_trade_at=None, last_trade_at=None, realised_profit_usd=0, summary=None)

Parameters:

• calculated_at (datetime) –

• total_equity (float) –

• net_asset_value (Optional[float]) –

• unrealised_profitability (Optional[float]) –

• free_cash (Optional[float]) –

• open_position_count (Optional[int]) –

• open_position_equity (Optional[float]) –

• frozen_position_count (Optional[int]) –

• frozen_position_equity (Optional[float]) –

• closed_position_count (Optional[int]) –

• unrealised_profit_usd (Optional[float]) –

• first_trade_at (Optional[datetime]) –

• last_trade_at (Optional[datetime]) –

• realised_profit_usd (Optional[float]) –

• summary (Optional[TradeSummary]) –

Return type:

None

Methods

__init__(calculated_at, total_equity[, ...])
from_dict(kvs, *[, infer_missing])
from_json(s, *[, parse_float, parse_int, ...])
get_value()
schema(*[, infer_missing, only, exclude, ...])
to_dict([encode_json])
to_json(*[, skipkeys, ensure_ascii, ...])

Attributes

closed_position_count
first_trade_at
free_cash
frozen_position_count
frozen_position_equity
last_trade_at
net_asset_value	How much was TVL equivalent
open_position_count
open_position_equity
realised_profit_usd
summary
unrealised_profit_usd
unrealised_profitability	The unrealised all-time profitability of this strategy at this point of time
calculated_at	Real-time clock when these stats were calculated
total_equity

calculated_at: datetime

Real-time clock when these stats were calculated

net_asset_value: Optional[float] = None

How much was TVL equivalent

unrealised_profitability: Optional[float] = None

The unrealised all-time profitability of this strategy at this point of time

See tradeexecutor.visualisation.equity_curve.calculate_compounding_unrealised_trading_profitability()

Set to 0 if cannot be calculated yet.

__init__(calculated_at, total_equity, net_asset_value=None, unrealised_profitability=None, free_cash=None, open_position_count=None, open_position_equity=None, frozen_position_count=None, frozen_position_equity=None, closed_position_count=None, unrealised_profit_usd=None, first_trade_at=None, last_trade_at=None, realised_profit_usd=0, summary=None)

Parameters:

• calculated_at (datetime) –

• total_equity (float) –

• net_asset_value (Optional[float]) –

• unrealised_profitability (Optional[float]) –

• free_cash (Optional[float]) –

• open_position_count (Optional[int]) –

• open_position_equity (Optional[float]) –

• frozen_position_count (Optional[int]) –

• frozen_position_equity (Optional[float]) –

• closed_position_count (Optional[int]) –

• unrealised_profit_usd (Optional[float]) –

• first_trade_at (Optional[datetime]) –

• last_trade_at (Optional[datetime]) –

• realised_profit_usd (Optional[float]) –

• summary (Optional[TradeSummary]) –

Return type:

None