StatisticsBuilder

QuantConnect.Statistics.StatisticsBuilder

Bases: Object

The StatisticsBuilder class creates summary and rolling statistics from trades, equity and benchmark points

create_benchmark_differences

create_benchmark_differences(
    points: List[KeyValuePair[datetime, float]],
    from_date: Union[datetime, date],
    to_date: Union[datetime, date],
) -> Iterable[KeyValuePair[datetime, float]]

Yields pairs of date and percentage change for the period

Parameters:

Name	Type	Description	Default
points	List[KeyValuePair[datetime, float]]	The values to calculate percentage change for	required
from_date	Union[datetime, date]	Starting date (inclusive)	required
to_date	Union[datetime, date]	Ending date (inclusive)	required

Returns:

Type	Description
Iterable[KeyValuePair[datetime, float]]	Pairs of date and percentage change.

generate

generate(
    trades: List[Trade],
    profit_loss: SortedDictionary[datetime, float],
    points_equity: List[ISeriesPoint],
    points_performance: List[ISeriesPoint],
    points_benchmark: List[ISeriesPoint],
    points_portfolio_turnover: List[ISeriesPoint],
    starting_capital: float,
    total_fees: float,
    total_orders: int,
    estimated_strategy_capacity: CapacityEstimate,
    account_currency_symbol: str,
    transactions: SecurityTransactionManager,
    risk_free_interest_rate_model: IRiskFreeInterestRateModel,
    trading_days_per_year: int,
) -> StatisticsResults

Generates the statistics and returns the results

Parameters:

Name	Type	Description	Default
trades	List[Trade]	The list of closed trades	required
profit_loss	SortedDictionary[datetime, float]	Trade record of profits and losses	required
points_equity	List[ISeriesPoint]	The list of daily equity values	required
points_performance	List[ISeriesPoint]	The list of algorithm performance values	required
points_benchmark	List[ISeriesPoint]	The list of benchmark values	required
points_portfolio_turnover	List[ISeriesPoint]	The list of portfolio turnover daily samples	required
starting_capital	float	The algorithm starting capital	required
total_fees	float	The total fees	required
total_orders	int	The total number of transactions	required
estimated_strategy_capacity	CapacityEstimate	The estimated capacity of this strategy	required
account_currency_symbol	str	The account currency symbol	required
transactions	SecurityTransactionManager	The transaction manager to get number of winning and losing transactions	required
risk_free_interest_rate_model	IRiskFreeInterestRateModel	The risk free interest rate model to use	required
trading_days_per_year	int	The number of trading days per year	required

Returns:

Type	Description
StatisticsResults	Returns a StatisticsResults object.

preprocess_performance_values

preprocess_performance_values(
    points: List[KeyValuePair[datetime, float]],
) -> Iterable[KeyValuePair[datetime, float]]

Skips the first two entries from the given points and divides each entry by 100

Parameters:

Name	Type	Description	Default
points	List[KeyValuePair[datetime, float]]	The values to divide by 100	required

Returns:

Type	Description
Iterable[KeyValuePair[datetime, float]]	Pairs of date and performance value divided by 100.