qs_adapter module ¶

Adapter class for quantstats.

Note

Accessors do not utilize caching.

We can access the adapter from ReturnsAccessor:

>>> import numpy as np
>>> import pandas as pd
>>> import vectorbt as vbt
>>> import quantstats as qs

>>> np.random.seed(42)
>>> rets = pd.Series(np.random.uniform(-0.1, 0.1, size=(100,)))
>>> benchmark_rets = pd.Series(np.random.uniform(-0.1, 0.1, size=(100,)))

>>> rets.vbt.returns.qs.r_squared(benchmark=benchmark_rets)
0.0011582111228735541

Which is the same as:

>>> qs.stats.r_squared(rets, benchmark_rets)

So why not just using qs.stats?

First, we can define all parameters such as benchmark returns once and avoid passing them repeatedly to every function. Second, vectorbt automatically translates parameters passed to ReturnsAccessor for the use in quantstats.

>>> # Defaults that vectorbt understands
>>> ret_acc = rets.vbt.returns(
...     benchmark_rets=benchmark_rets,
...     freq='d',
...     year_freq='365d',
...     defaults=dict(risk_free=0.001)
... )

>>> ret_acc.qs.r_squared()
0.0011582111228735541

>>> ret_acc.qs.sharpe()
-1.9158923252075455

>>> # Defaults that only quantstats understands
>>> qs_defaults = dict(
...     benchmark=benchmark_rets,
...     periods=365,
...     periods_per_year=365,
...     rf=0.001
... )
>>> ret_acc_qs = rets.vbt.returns.qs(defaults=qs_defaults)

>>> ret_acc_qs.r_squared()
0.0011582111228735541

>>> ret_acc_qs.sharpe()
-1.9158923252075455

The adapter automatically passes the returns to the particular function. It also merges the defaults defined in the settings, the defaults passed to ReturnsAccessor, and the defaults passed to QSAdapter itself, and matches them with the argument names listed in the function's signature.

For example, the periods and periods_per_year arguments default to the annualization factor ReturnsAccessor.ann_factor, which itself is based on the freq argument. This makes the results produced by quantstats and vectorbt at least somewhat similar.

>>> vbt.settings.array_wrapper['freq'] = 'h'
>>> vbt.settings.returns['year_freq'] = '365d'

>>> rets.vbt.returns.sharpe_ratio()  # ReturnsAccessor
-9.38160953971508

>>> rets.vbt.returns.qs.sharpe()  # quantstats via QSAdapter
-9.38160953971508

We can still override any argument by overriding its default or by passing it directly to the function:

>>> rets.vbt.returns.qs(defaults=dict(periods=252)).sharpe()
-1.5912029345745982

>>> rets.vbt.returns.qs.sharpe(periods=252)
-1.5912029345745982

>>> qs.stats.sharpe(rets)
-1.5912029345745982

attach_qs_methods function ¶

attach_qs_methods(
    cls,
    replace_signature=True
)

Class decorator to attach quantstats methods.

QSAdapter class ¶

QSAdapter(
    returns_accessor,
    defaults=None,
    **kwargs
)

Adapter class for quantstats.

Superclasses

Inherited members

adjusted_sortino method ¶

QSAdapter.adjusted_sortino(
    *,
    rf=0,
    periods=252,
    annualize=True,
    smart=False
)

See quantstats.stats.adjusted_sortino.

aggregate_returns method ¶

QSAdapter.aggregate_returns(
    *,
    period=None,
    compounded=True
)

See quantstats.utils.aggregate_returns.

autocorr_penalty method ¶

QSAdapter.autocorr_penalty(
    *,
    prepare_returns=False
)

See quantstats.stats.autocorr_penalty.

avg_loss method ¶

QSAdapter.avg_loss(
    *,
    aggregate=None,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.avg_loss.

avg_return method ¶

QSAdapter.avg_return(
    *,
    aggregate=None,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.avg_return.

avg_win method ¶

QSAdapter.avg_win(
    *,
    aggregate=None,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.avg_win.

basic_report method ¶

QSAdapter.basic_report(
    *,
    benchmark=None,
    rf=0.0,
    grayscale=False,
    figsize=(8, 5),
    display=True,
    compounded=True,
    periods_per_year=252,
    match_dates=True,
    **kwargs
)

See quantstats.reports.basic.

best method ¶

QSAdapter.best(
    *,
    aggregate=None,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.best.

cagr method ¶

QSAdapter.cagr(
    *,
    rf=0.0,
    compounded=True,
    periods=252
)

See quantstats.stats.cagr.

calmar method ¶

QSAdapter.calmar(
    *,
    prepare_returns=True
)

See quantstats.stats.calmar.

common_sense_ratio method ¶

QSAdapter.common_sense_ratio(
    *,
    prepare_returns=True
)

See quantstats.stats.common_sense_ratio.

comp method ¶

QSAdapter.comp()

See quantstats.stats.comp.

compare method ¶

QSAdapter.compare(
    *,
    benchmark,
    aggregate=None,
    compounded=True,
    round_vals=None,
    prepare_returns=True
)

See quantstats.stats.compare.

compsum method ¶

QSAdapter.compsum()

See quantstats.stats.compsum.

conditional_value_at_risk method ¶

QSAdapter.conditional_value_at_risk(
    *,
    sigma=1,
    confidence=0.95,
    prepare_returns=True
)

See quantstats.stats.conditional_value_at_risk.

consecutive_losses method ¶

QSAdapter.consecutive_losses(
    *,
    aggregate=None,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.consecutive_losses.

consecutive_wins method ¶

QSAdapter.consecutive_wins(
    *,
    aggregate=None,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.consecutive_wins.

cpc_index method ¶

QSAdapter.cpc_index(
    *,
    prepare_returns=True
)

See quantstats.stats.cpc_index.

cvar method ¶

QSAdapter.cvar(
    *,
    sigma=1,
    confidence=0.95,
    prepare_returns=True
)

See quantstats.stats.cvar.

defaults property ¶

Defaults for QSAdapter.

Merges qs_adapter.defaults from settings, returns_accessor.defaults (with adapted naming), and defaults from QSAdapter.

defaults_mapping property ¶

Common argument names in quantstats mapped to ReturnsAccessor.defaults.

distribution method ¶

QSAdapter.distribution(
    *,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.distribution.

expected_return method ¶

QSAdapter.expected_return(
    *,
    aggregate=None,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.expected_return.

expected_shortfall method ¶

QSAdapter.expected_shortfall(
    *,
    sigma=1,
    confidence=0.95
)

See quantstats.stats.expected_shortfall.

exponential_stdev method ¶

QSAdapter.exponential_stdev(
    *,
    window=30,
    is_halflife=False
)

See quantstats.utils.exponential_stdev.

exposure method ¶

QSAdapter.exposure(
    *,
    prepare_returns=True
)

See quantstats.stats.exposure.

full_report method ¶

QSAdapter.full_report(
    *,
    benchmark=None,
    rf=0.0,
    grayscale=False,
    figsize=(8, 5),
    display=True,
    compounded=True,
    periods_per_year=252,
    match_dates=True,
    **kwargs
)

See quantstats.reports.full.

gain_to_pain_ratio method ¶

QSAdapter.gain_to_pain_ratio(
    *,
    rf=0,
    resolution='D'
)

See quantstats.stats.gain_to_pain_ratio.

geometric_mean method ¶

QSAdapter.geometric_mean(
    *,
    aggregate=None,
    compounded=True
)

See quantstats.stats.geometric_mean.

ghpr method ¶

QSAdapter.ghpr(
    *,
    aggregate=None,
    compounded=True
)

See quantstats.stats.ghpr.

greeks method ¶

QSAdapter.greeks(
    *,
    benchmark,
    periods=252.0,
    prepare_returns=True
)

See quantstats.stats.greeks.

group_returns method ¶

QSAdapter.group_returns(
    *,
    groupby,
    compounded=False
)

See quantstats.utils.group_returns.

html_report method ¶

QSAdapter.html_report(
    *,
    benchmark=None,
    rf=0.0,
    grayscale=False,
    title='Strategy Tearsheet',
    output=None,
    compounded=True,
    periods_per_year=252,
    download_filename='quantstats-tearsheet.html',
    figfmt='svg',
    template_path=None,
    match_dates=True,
    **kwargs
)

See quantstats.reports.html.

implied_volatility method ¶

QSAdapter.implied_volatility(
    *,
    periods=252,
    annualize=True
)

See quantstats.stats.implied_volatility.

information_ratio method ¶

QSAdapter.information_ratio(
    *,
    benchmark,
    prepare_returns=True
)

See quantstats.stats.information_ratio.

kelly_criterion method ¶

QSAdapter.kelly_criterion(
    *,
    prepare_returns=True
)

See quantstats.stats.kelly_criterion.

kurtosis method ¶

QSAdapter.kurtosis(
    *,
    prepare_returns=True
)

See quantstats.stats.kurtosis.

log_returns method ¶

QSAdapter.log_returns(
    *,
    rf=0.0,
    nperiods=None
)

See quantstats.utils.log_returns.

make_index method ¶

QSAdapter.make_index(
    *,
    rebalance='1M',
    period='max',
    returns=None,
    match_dates=False
)

See quantstats.utils.make_index.

make_portfolio method ¶

QSAdapter.make_portfolio(
    *,
    start_balance=100000.0,
    mode='comp',
    round_to=None
)

See quantstats.utils.make_portfolio.

metrics_report method ¶

QSAdapter.metrics_report(
    *,
    benchmark=None,
    rf=0.0,
    display=True,
    mode='basic',
    sep=False,
    compounded=True,
    periods_per_year=252,
    prepare_returns=True,
    match_dates=True,
    **kwargs
)

See quantstats.reports.metrics.

monthly_returns method ¶

QSAdapter.monthly_returns(
    *,
    eoy=True,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.monthly_returns.

omega method ¶

QSAdapter.omega(
    *,
    rf=0.0,
    required_return=0.0,
    periods=252
)

See quantstats.stats.omega.

outlier_loss_ratio method ¶

QSAdapter.outlier_loss_ratio(
    *,
    quantile=0.01,
    prepare_returns=True
)

See quantstats.stats.outlier_loss_ratio.

outlier_win_ratio method ¶

QSAdapter.outlier_win_ratio(
    *,
    quantile=0.99,
    prepare_returns=True
)

See quantstats.stats.outlier_win_ratio.

outliers method ¶

QSAdapter.outliers(
    *,
    quantile=0.95
)

See quantstats.stats.outliers.

payoff_ratio method ¶

QSAdapter.payoff_ratio(
    *,
    prepare_returns=True
)

See quantstats.stats.payoff_ratio.

plot_daily_returns method ¶

QSAdapter.plot_daily_returns(
    *,
    benchmark,
    grayscale=False,
    figsize=(10, 4),
    fontname='Arial',
    lw=0.5,
    log_scale=False,
    ylabel='Returns',
    subtitle=True,
    savefig=None,
    show=True,
    prepare_returns=True,
    active=False
)

See quantstats.plots.daily_returns.

plot_distribution method ¶

QSAdapter.plot_distribution(
    *,
    fontname='Arial',
    grayscale=False,
    ylabel=True,
    figsize=(10, 6),
    subtitle=True,
    compounded=True,
    savefig=None,
    show=True,
    title=None,
    prepare_returns=True
)

See quantstats.plots.distribution.

plot_drawdown method ¶

QSAdapter.plot_drawdown(
    *,
    grayscale=False,
    figsize=(10, 5),
    fontname='Arial',
    lw=1,
    log_scale=False,
    match_volatility=False,
    compound=False,
    ylabel='Drawdown',
    resample=None,
    subtitle=True,
    savefig=None,
    show=True
)

See quantstats.plots.drawdown.

plot_drawdowns_periods method ¶

QSAdapter.plot_drawdowns_periods(
    *,
    periods=5,
    lw=1.5,
    log_scale=False,
    fontname='Arial',
    grayscale=False,
    title=None,
    figsize=(10, 5),
    ylabel=True,
    subtitle=True,
    compounded=True,
    savefig=None,
    show=True,
    prepare_returns=True
)

See quantstats.plots.drawdowns_periods.

plot_earnings method ¶

QSAdapter.plot_earnings(
    *,
    start_balance=100000.0,
    mode='comp',
    grayscale=False,
    figsize=(10, 6),
    title='Portfolio Earnings',
    fontname='Arial',
    lw=1.5,
    subtitle=True,
    savefig=None,
    show=True
)

See quantstats.plots.earnings.

plot_histogram method ¶

QSAdapter.plot_histogram(
    *,
    benchmark=None,
    resample='ME',
    fontname='Arial',
    grayscale=False,
    figsize=(10, 5),
    ylabel=True,
    subtitle=True,
    compounded=True,
    savefig=None,
    show=True,
    prepare_returns=True
)

See quantstats.plots.histogram.

plot_log_returns method ¶

QSAdapter.plot_log_returns(
    *,
    benchmark=None,
    grayscale=False,
    figsize=(10, 5),
    fontname='Arial',
    lw=1.5,
    match_volatility=False,
    compound=True,
    cumulative=True,
    resample=None,
    ylabel='Cumulative Returns',
    subtitle=True,
    savefig=None,
    show=True,
    prepare_returns=True
)

See quantstats.plots.log_returns.

plot_monthly_heatmap method ¶

QSAdapter.plot_monthly_heatmap(
    *,
    benchmark=None,
    annot_size=13,
    figsize=(8, 5),
    cbar=True,
    square=False,
    returns_label='Strategy',
    compounded=True,
    eoy=False,
    grayscale=False,
    fontname='Arial',
    ylabel=True,
    savefig=None,
    show=True,
    active=False
)

See quantstats.plots.monthly_heatmap.

plot_monthly_returns method ¶

QSAdapter.plot_monthly_returns(
    *,
    annot_size=9,
    figsize=(10, 5),
    cbar=True,
    square=False,
    compounded=True,
    eoy=False,
    grayscale=False,
    fontname='Arial',
    ylabel=True,
    savefig=None,
    show=True
)

See quantstats.plots.monthly_returns.

plot_returns method ¶

QSAdapter.plot_returns(
    *,
    benchmark=None,
    grayscale=False,
    figsize=(10, 6),
    fontname='Arial',
    lw=1.5,
    match_volatility=False,
    compound=True,
    cumulative=True,
    resample=None,
    ylabel='Cumulative Returns',
    subtitle=True,
    savefig=None,
    show=True,
    prepare_returns=True
)

See quantstats.plots.returns.

plot_rolling_beta method ¶

QSAdapter.plot_rolling_beta(
    *,
    benchmark,
    window1=126,
    window1_label='6-Months',
    window2=252,
    window2_label='12-Months',
    lw=1.5,
    fontname='Arial',
    grayscale=False,
    figsize=(10, 3),
    ylabel=True,
    subtitle=True,
    savefig=None,
    show=True,
    prepare_returns=True
)

See quantstats.plots.rolling_beta.

plot_rolling_sharpe method ¶

QSAdapter.plot_rolling_sharpe(
    *,
    benchmark=None,
    rf=0.0,
    period=126,
    period_label='6-Months',
    periods_per_year=252,
    lw=1.25,
    fontname='Arial',
    grayscale=False,
    figsize=(10, 3),
    ylabel='Sharpe',
    subtitle=True,
    savefig=None,
    show=True
)

See quantstats.plots.rolling_sharpe.

plot_rolling_sortino method ¶

QSAdapter.plot_rolling_sortino(
    *,
    benchmark=None,
    rf=0.0,
    period=126,
    period_label='6-Months',
    periods_per_year=252,
    lw=1.25,
    fontname='Arial',
    grayscale=False,
    figsize=(10, 3),
    ylabel='Sortino',
    subtitle=True,
    savefig=None,
    show=True
)

See quantstats.plots.rolling_sortino.

plot_rolling_volatility method ¶

QSAdapter.plot_rolling_volatility(
    *,
    benchmark=None,
    period=126,
    period_label='6-Months',
    periods_per_year=252,
    lw=1.5,
    fontname='Arial',
    grayscale=False,
    figsize=(10, 3),
    ylabel='Volatility',
    subtitle=True,
    savefig=None,
    show=True
)

See quantstats.plots.rolling_volatility.

plot_snapshot method ¶

QSAdapter.plot_snapshot(
    *,
    grayscale=False,
    figsize=(10, 8),
    title='Portfolio Summary',
    fontname='Arial',
    lw=1.5,
    mode='comp',
    subtitle=True,
    savefig=None,
    show=True,
    log_scale=False,
    **kwargs
)

See quantstats.plots.snapshot.

plot_yearly_returns method ¶

QSAdapter.plot_yearly_returns(
    *,
    benchmark=None,
    fontname='Arial',
    grayscale=False,
    hlw=1.5,
    hlcolor='red',
    hllabel='',
    match_volatility=False,
    log_scale=False,
    figsize=(10, 5),
    ylabel=True,
    subtitle=True,
    compounded=True,
    savefig=None,
    show=True,
    prepare_returns=True
)

See quantstats.plots.yearly_returns.

plots_report method ¶

QSAdapter.plots_report(
    *,
    benchmark=None,
    grayscale=False,
    figsize=(8, 5),
    mode='basic',
    compounded=True,
    periods_per_year=252,
    prepare_returns=True,
    match_dates=True,
    **kwargs
)

See quantstats.reports.plots.

profit_factor method ¶

QSAdapter.profit_factor(
    *,
    prepare_returns=True
)

See quantstats.stats.profit_factor.

profit_ratio method ¶

QSAdapter.profit_ratio(
    *,
    prepare_returns=True
)

See quantstats.stats.profit_ratio.

r2 method ¶

QSAdapter.r2(
    *,
    benchmark
)

See quantstats.stats.r2.

r_squared method ¶

QSAdapter.r_squared(
    *,
    benchmark,
    prepare_returns=True
)

See quantstats.stats.r_squared.

rar method ¶

QSAdapter.rar(
    *,
    rf=0.0
)

See quantstats.stats.rar.

recovery_factor method ¶

QSAdapter.recovery_factor(
    *,
    rf=0.0,
    prepare_returns=True
)

See quantstats.stats.recovery_factor.

remove_outliers method ¶

QSAdapter.remove_outliers(
    *,
    quantile=0.95
)

See quantstats.stats.remove_outliers.

returns_accessor property ¶

Returns accessor.

risk_of_ruin method ¶

QSAdapter.risk_of_ruin(
    *,
    prepare_returns=True
)

See quantstats.stats.risk_of_ruin.

risk_return_ratio method ¶

QSAdapter.risk_return_ratio(
    *,
    prepare_returns=True
)

See quantstats.stats.risk_return_ratio.

rolling_greeks method ¶

QSAdapter.rolling_greeks(
    *,
    benchmark,
    periods=252,
    prepare_returns=True
)

See quantstats.stats.rolling_greeks.

rolling_sharpe method ¶

QSAdapter.rolling_sharpe(
    *,
    rf=0.0,
    rolling_period=126,
    annualize=True,
    periods_per_year=252,
    prepare_returns=True
)

See quantstats.stats.rolling_sharpe.

rolling_sortino method ¶

QSAdapter.rolling_sortino(
    *,
    rf=0,
    rolling_period=126,
    annualize=True,
    periods_per_year=252,
    **kwargs
)

See quantstats.stats.rolling_sortino.

rolling_volatility method ¶

QSAdapter.rolling_volatility(
    *,
    rolling_period=126,
    periods_per_year=252,
    prepare_returns=True
)

See quantstats.stats.rolling_volatility.

ror method ¶

QSAdapter.ror()

See quantstats.stats.ror.

serenity_index method ¶

QSAdapter.serenity_index(
    *,
    rf=0
)

See quantstats.stats.serenity_index.

sharpe method ¶

QSAdapter.sharpe(
    *,
    rf=0.0,
    periods=252,
    annualize=True,
    smart=False
)

See quantstats.stats.sharpe.

skew method ¶

QSAdapter.skew(
    *,
    prepare_returns=True
)

See quantstats.stats.skew.

smart_sharpe method ¶

QSAdapter.smart_sharpe(
    *,
    rf=0.0,
    periods=252,
    annualize=True
)

See quantstats.stats.smart_sharpe.

smart_sortino method ¶

QSAdapter.smart_sortino(
    *,
    rf=0,
    periods=252,
    annualize=True
)

See quantstats.stats.smart_sortino.

sortino method ¶

QSAdapter.sortino(
    *,
    rf=0,
    periods=252,
    annualize=True,
    smart=False
)

See quantstats.stats.sortino.

tail_ratio method ¶

QSAdapter.tail_ratio(
    *,
    cutoff=0.95,
    prepare_returns=True
)

See quantstats.stats.tail_ratio.

to_drawdown_series method ¶

QSAdapter.to_drawdown_series()

See quantstats.stats.to_drawdown_series.

to_excess_returns method ¶

QSAdapter.to_excess_returns(
    *,
    rf,
    nperiods=None
)

See quantstats.utils.to_excess_returns.

to_log_returns method ¶

QSAdapter.to_log_returns(
    *,
    rf=0.0,
    nperiods=None
)

See quantstats.utils.to_log_returns.

to_prices method ¶

QSAdapter.to_prices(
    *,
    base=100000.0
)

See quantstats.utils.to_prices.

treynor_ratio method ¶

QSAdapter.treynor_ratio(
    *,
    benchmark,
    periods=252.0,
    rf=0.0
)

See quantstats.stats.treynor_ratio.

ulcer_index method ¶

QSAdapter.ulcer_index()

See quantstats.stats.ulcer_index.

ulcer_performance_index method ¶

QSAdapter.ulcer_performance_index(
    *,
    rf=0
)

See quantstats.stats.ulcer_performance_index.

upi method ¶

QSAdapter.upi(
    *,
    rf=0
)

See quantstats.stats.upi.

value_at_risk method ¶

QSAdapter.value_at_risk(
    *,
    sigma=1,
    confidence=0.95,
    prepare_returns=True
)

See quantstats.stats.value_at_risk.

var method ¶

QSAdapter.var(
    *,
    sigma=1,
    confidence=0.95,
    prepare_returns=True
)

See quantstats.stats.var.

volatility method ¶

QSAdapter.volatility(
    *,
    periods=252,
    annualize=True,
    prepare_returns=True
)

See quantstats.stats.volatility.

win_loss_ratio method ¶

QSAdapter.win_loss_ratio(
    *,
    prepare_returns=True
)

See quantstats.stats.win_loss_ratio.

win_rate method ¶

QSAdapter.win_rate(
    *,
    aggregate=None,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.win_rate.

worst method ¶

QSAdapter.worst(
    *,
    aggregate=None,
    compounded=True,
    prepare_returns=True
)

See quantstats.stats.worst.

qs_adapter module¶

attach_qs_methods function¶

QSAdapter class¶

adjusted_sortino method¶

aggregate_returns method¶

autocorr_penalty method¶

avg_loss method¶

avg_return method¶

avg_win method¶

basic_report method¶

best method¶

cagr method¶

calmar method¶

common_sense_ratio method¶

comp method¶

compare method¶

compsum method¶

conditional_value_at_risk method¶

consecutive_losses method¶

consecutive_wins method¶

cpc_index method¶

cvar method¶

defaults property¶

defaults_mapping property¶

distribution method¶

expected_return method¶

expected_shortfall method¶

exponential_stdev method¶

exposure method¶

full_report method¶

gain_to_pain_ratio method¶

geometric_mean method¶

ghpr method¶

greeks method¶

group_returns method¶

html_report method¶

implied_volatility method¶

information_ratio method¶

kelly_criterion method¶

kurtosis method¶

log_returns method¶

make_index method¶

make_portfolio method¶

metrics_report method¶

monthly_returns method¶

omega method¶

outlier_loss_ratio method¶

outlier_win_ratio method¶

outliers method¶

payoff_ratio method¶

plot_daily_returns method¶

plot_distribution method¶

plot_drawdown method¶

plot_drawdowns_periods method¶

plot_earnings method¶

plot_histogram method¶

plot_log_returns method¶

plot_monthly_heatmap method¶

plot_monthly_returns method¶

plot_returns method¶

plot_rolling_beta method¶

plot_rolling_sharpe method¶

plot_rolling_sortino method¶

plot_rolling_volatility method¶

plot_snapshot method¶

plot_yearly_returns method¶

plots_report method¶

profit_factor method¶

profit_ratio method¶

r2 method¶

r_squared method¶

rar method¶

recovery_factor method¶

remove_outliers method¶

returns_accessor property¶

risk_of_ruin method¶

risk_return_ratio method¶

rolling_greeks method¶

rolling_sharpe method¶

rolling_sortino method¶