Sharadar offers a suite of complementary datasets for US equities, fully integrated with QuantRocket
Explore Sharadar data in the Data Library
Analyzing Sharadar data in QuantRocket is a snap
How have the top 20% of stocks by EPS performed?
# Get prices
>>> prices = get_prices("sharadar-us-1d", fields="Close")
>>> closes = prices.loc["Close"]
>>> returns = closes.pct_change()
# Rank stocks by EPS and get returns of top 20%
>>> eps = get_sharadar_fundamentals_reindexed_like(closes, fields="EPS").loc["EPS"]
>>> eps_ranks = eps.rank(axis=1, pct=True)
>>> winner_returns = returns.where(eps_ranks.shift() > 0.8)
What if we limit to stocks that were in the S&P 500 at the time?
>>> in_sp500 = get_sharadar_sp500_reindexed_like(closes)
>>> winner_returns.where(in_sp500)
Founded in 2013, Sharadar provides originally curated data for U.S. public companies, combining people, software and process to generate investment grade data.