Function _prepare_benchmark

quantstats/utils.py:255–288

Fetch benchmark if ticker is provided, and pass through _prepare_returns() period can be options or (expected) _pd.DatetimeIndex range

(benchmark=None, period="max", rf=0.0, prepare_returns=True)

def _prepare_benchmark(benchmark=None, period="max", rf=0.0, prepare_returns=True):
    """
    Fetch benchmark if ticker is provided, and pass through
    _prepare_returns()

    period can be options or (expected) _pd.DatetimeIndex range
    """
    if benchmark is None:
        return None

    if isinstance(benchmark, str):
        benchmark = download_returns(benchmark)

    elif isinstance(benchmark, _pd.DataFrame):
        benchmark = benchmark[benchmark.columns[0]].copy()

    if isinstance(period, _pd.DatetimeIndex) and set(period) != set(benchmark.index):

        # Adjust Benchmark to Strategy frequency
        benchmark_prices = to_prices(benchmark, base=1)
        new_index = _pd.date_range(start=period[0], end=period[-1], freq="D")
        benchmark = (
            benchmark_prices.reindex(new_index, method="bfill")
            .reindex(period)
            .pct_change()
            .fillna(0)
        )
        benchmark = benchmark[benchmark.index.isin(period)]

    benchmark = benchmark.tz_localize(None)

    if prepare_returns:
        return _prepare_returns(benchmark.dropna(), rf=rf)
    return benchmark.dropna()


def _round_to_closest(val, res, decimals=None):