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nb module

Numba-compiled functions for returns.

Provides an arsenal of Numba-compiled functions that are used by accessors and for measuring portfolio performance. These only accept NumPy arrays and other Numba-compatible types.

Note

vectorbt treats matrices as first-class citizens and expects input arrays to be 2-dim, unless function has suffix _1d or is meant to be input to another function. Data is processed along index (axis 0).

All functions passed as argument must be Numba-compiled.

alpha_1d_nb function

alpha_1d_nb(
    adj_rets,
    adj_bm_returns,
    ann_factor
)

Annualized alpha.

alpha_nb function

alpha_nb(
    adj_rets,
    adj_bm_returns,
    ann_factor
)

2-dim version of alpha_1d_nb().

alpha_rollmeta_nb function

alpha_rollmeta_nb(
    from_i,
    to_i,
    col,
    adj_rets,
    adj_bm_returns,
    ann_factor
)

Rolling apply meta function based on alpha_1d_nb().

annualized_return_1d_nb function

annualized_return_1d_nb(
    rets,
    ann_factor,
    period=None,
    log_returns=False
)

Annualized total return.

This is equivalent to the compound annual growth rate (CAGR).

annualized_return_nb function

annualized_return_nb(
    rets,
    ann_factor,
    period=None,
    log_returns=False
)

2-dim version of annualized_return_1d_nb().

annualized_volatility_1d_nb function

annualized_volatility_1d_nb(
    rets,
    ann_factor,
    levy_alpha=2.0,
    ddof=0
)

Annualized volatility of a strategy.

annualized_volatility_nb function

annualized_volatility_nb(
    rets,
    ann_factor,
    levy_alpha=2.0,
    ddof=0
)

2-dim version of annualized_volatility_1d_nb().

beta_1d_nb function

beta_1d_nb(
    rets,
    bm_returns,
    ddof=0
)

Beta.

beta_nb function

beta_nb(
    rets,
    bm_returns,
    ddof=0
)

2-dim version of beta_1d_nb().

beta_rollmeta_nb function

beta_rollmeta_nb(
    from_i,
    to_i,
    col,
    rets,
    bm_returns,
    ddof=0
)

Rolling apply meta function based on beta_1d_nb().

calmar_ratio_1d_nb function

calmar_ratio_1d_nb(
    rets,
    ann_factor,
    period=None,
    log_returns=False
)

Calmar ratio, or drawdown ratio, of a strategy.

calmar_ratio_nb function

calmar_ratio_nb(
    rets,
    ann_factor,
    period=None,
    log_returns=False
)

2-dim version of calmar_ratio_1d_nb().

capture_ratio_1d_nb function

capture_ratio_1d_nb(
    rets,
    bm_returns,
    ann_factor,
    period=None,
    log_returns=False
)

Capture ratio.

capture_ratio_nb function

capture_ratio_nb(
    rets,
    bm_returns,
    ann_factor,
    period=None,
    log_returns=False
)

2-dim version of capture_ratio_1d_nb().

capture_ratio_rollmeta_nb function

capture_ratio_rollmeta_nb(
    from_i,
    to_i,
    col,
    rets,
    bm_returns,
    ann_factor,
    period=None,
    log_returns=False
)

Rolling apply meta function based on capture_ratio_1d_nb().

common_sense_ratio_1d_nb function

common_sense_ratio_1d_nb(
    rets
)

Common Sense Ratio.

common_sense_ratio_nb function

common_sense_ratio_nb(
    rets
)

2-dim version of common_sense_ratio_1d_nb().

cond_value_at_risk_1d_nb function

cond_value_at_risk_1d_nb(
    rets,
    cutoff=0.05
)

Conditional value at risk (CVaR) of a returns stream.

cond_value_at_risk_nb function

cond_value_at_risk_nb(
    rets,
    cutoff=0.05
)

2-dim version of cond_value_at_risk_1d_nb().

cond_value_at_risk_noarr_1d_nb function

cond_value_at_risk_noarr_1d_nb(
    rets,
    cutoff=0.05
)

cond_value_at_risk_1d_nb() that does not allocate any arrays.

cum_returns_1d_nb function

cum_returns_1d_nb(
    rets,
    start_value=1.0,
    log_returns=False
)

Cumulative returns.

cum_returns_final_1d_nb function

cum_returns_final_1d_nb(
    rets,
    start_value=1.0,
    log_returns=False
)

Total return.

cum_returns_final_nb function

cum_returns_final_nb(
    rets,
    start_value=1.0,
    log_returns=False
)

2-dim version of cum_returns_final_1d_nb().

cum_returns_nb function

cum_returns_nb(
    rets,
    start_value=1.0,
    log_returns=False
)

2-dim version of cum_returns_1d_nb().

deannualized_return_nb function

deannualized_return_nb(
    ret,
    ann_factor
)

Deannualized return.

down_capture_ratio_1d_nb function

down_capture_ratio_1d_nb(
    rets,
    bm_returns,
    ann_factor,
    period=None,
    log_returns=False
)

Capture ratio for periods when the benchmark return is negative.

down_capture_ratio_nb function

down_capture_ratio_nb(
    rets,
    bm_returns,
    ann_factor,
    period=None,
    log_returns=False
)

2-dim version of down_capture_ratio_1d_nb().

down_capture_ratio_rollmeta_nb function

down_capture_ratio_rollmeta_nb(
    from_i,
    to_i,
    col,
    rets,
    bm_returns,
    ann_factor,
    period=None,
    log_returns=False
)

Rolling apply meta function based on down_capture_ratio_1d_nb().

downside_risk_1d_nb function

downside_risk_1d_nb(
    adj_rets,
    ann_factor
)

Downside deviation below a threshold.

downside_risk_nb function

downside_risk_nb(
    adj_rets,
    ann_factor
)

2-dim version of downside_risk_1d_nb().

get_return_nb function

get_return_nb(
    input_value,
    output_value,
    log_returns=False,
    inf_to_nan=False,
    nan_to_zero=False
)

Calculate return from input and output value.

information_ratio_1d_nb function

information_ratio_1d_nb(
    adj_rets,
    ddof=0
)

Information ratio of a strategy.

information_ratio_nb function

information_ratio_nb(
    adj_rets,
    ddof=0
)

2-dim version of information_ratio_1d_nb().

max_drawdown_1d_nb function

max_drawdown_1d_nb(
    rets,
    log_returns=False
)

Total maximum drawdown (MDD).

max_drawdown_nb function

max_drawdown_nb(
    rets,
    log_returns=False
)

2-dim version of max_drawdown_1d_nb().

omega_ratio_1d_nb function

omega_ratio_1d_nb(
    adj_rets
)

Omega ratio of a strategy.

omega_ratio_nb function

omega_ratio_nb(
    adj_rets
)

2-dim version of omega_ratio_1d_nb().

profit_factor_1d_nb function

profit_factor_1d_nb(
    rets
)

Profit factor.

profit_factor_nb function

profit_factor_nb(
    rets
)

2-dim version of profit_factor_1d_nb().

returns_1d_nb function

returns_1d_nb(
    arr,
    init_value=nan,
    log_returns=False
)

Calculate returns.

returns_nb function

returns_nb(
    arr,
    init_value=nan,
    log_returns=False
)

2-dim version of returns_1d_nb().

rolling_sharpe_acc_nb function

rolling_sharpe_acc_nb(
    in_state
)

Accumulator of rolling_sharpe_nb.

Takes a state of type RollSharpeAIS and returns a state of type RollSharpeAOS.

rolling_sharpe_ratio_nb function

rolling_sharpe_ratio_nb(
    returns,
    window,
    ann_factor,
    minp=None,
    ddof=0
)

Calculate rolling Sharpe ratio.

Uses rolling_sharpe_acc_nb() at each iteration.

sharpe_ratio_1d_nb function

sharpe_ratio_1d_nb(
    adj_rets,
    ann_factor,
    ddof=0
)

Sharpe ratio of a strategy.

sharpe_ratio_nb function

sharpe_ratio_nb(
    adj_rets,
    ann_factor,
    ddof=0
)

2-dim version of sharpe_ratio_1d_nb().

sortino_ratio_1d_nb function

sortino_ratio_1d_nb(
    adj_rets,
    ann_factor
)

Sortino ratio of a strategy.

sortino_ratio_nb function

sortino_ratio_nb(
    adj_rets,
    ann_factor
)

2-dim version of sortino_ratio_1d_nb().

tail_ratio_1d_nb function

tail_ratio_1d_nb(
    rets
)

Ratio between the right (95%) and left tail (5%).

tail_ratio_nb function

tail_ratio_nb(
    rets
)

2-dim version of tail_ratio_1d_nb().

tail_ratio_noarr_1d_nb function

tail_ratio_noarr_1d_nb(
    rets
)

tail_ratio_1d_nb() that does not allocate any arrays.

up_capture_ratio_1d_nb function

up_capture_ratio_1d_nb(
    rets,
    bm_returns,
    ann_factor,
    period=None,
    log_returns=False
)

Capture ratio for periods when the benchmark return is positive.

up_capture_ratio_nb function

up_capture_ratio_nb(
    rets,
    bm_returns,
    ann_factor,
    period=None,
    log_returns=False
)

2-dim version of up_capture_ratio_1d_nb().

up_capture_ratio_rollmeta_nb function

up_capture_ratio_rollmeta_nb(
    from_i,
    to_i,
    col,
    rets,
    bm_returns,
    ann_factor,
    period=None,
    log_returns=False
)

Rolling apply meta function based on up_capture_ratio_1d_nb().

value_at_risk_1d_nb function

value_at_risk_1d_nb(
    rets,
    cutoff=0.05
)

Value at risk (VaR) of a returns stream.

value_at_risk_nb function

value_at_risk_nb(
    rets,
    cutoff=0.05
)

2-dim version of value_at_risk_1d_nb().

value_at_risk_noarr_1d_nb function

value_at_risk_noarr_1d_nb(
    rets,
    cutoff=0.05
)

value_at_risk_1d_nb() that does not allocate any arrays.