S&P 500 Annual Returns Histogram¶

© 2025 Marek Ozana

Histogram of S&P 500 annual returns since 100 years back.

Out[8]:

In [9]:

# Get historical S&P 500 annual price returns

from polars_bloomberg import BQuery

bin_names: list = [
    "< -50",
    "-50 to -40",
    "-40 to -30",
    "-30 to -20",
    "-20 to -10",
    "-10 to 0",
    "0 to 10",
    "10 to 20",
    "20 to 30",
    "30 to 40",
    "40 to 50",
    "> 50",
]
bins = list(range(-50, 60, 10))

query = f"""
let(
    #rets = dropna(pct_diff(px_last(dates=range(-100Y, 0Y), per=Y)));
    #bins = bins(#rets, {bins}, bin_names={bin_names});
)
get(#rets, #bins)
for(['SPX Index'])
"""
with BQuery() as bq:
    df = bq.bql(query).combine()
df.head(3)

# Get historical S&P 500 annual price returns from polars_bloomberg import BQuery bin_names: list = [ "< -50", "-50 to -40", "-40 to -30", "-30 to -20", "-20 to -10", "-10 to 0", "0 to 10", "10 to 20", "20 to 30", "30 to 40", "40 to 50", "> 50", ] bins = list(range(-50, 60, 10)) query = f""" let( #rets = dropna(pct_diff(px_last(dates=range(-100Y, 0Y), per=Y))); #bins = bins(#rets, {bins}, bin_names={bin_names}); ) get(#rets, #bins) for(['SPX Index']) """ with BQuery() as bq: df = bq.bql(query).combine() df.head(3)

Out[9]:

shape: (3, 4)

ID	#rets	DATE	#bins
str	f64	date	str
"SPX Index"	37.88222	1928-12-31	"30 to 40"
"SPX Index"	-11.909651	1929-12-31	"-20 to -10"
"SPX Index"	-28.484848	1930-12-31	"-30 to -20"