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Stocks Quarterly FactorSignals

Quarterly factor exposures and scores for US equities.

763,836 rows over 22,791 symbols, 35 columns, covering 1998-03-31 to 2026-06-30. Refreshed monthly.

Strategies Built on This Data

53 papers in the Papers With Backtest catalogue declare this dataset as an input. 52 of them have been coded and run over their own full history. The median replicated Sharpe ratio is +0.52, and 58% clear a t-statistic of 1.96 on their own sample, against 48% across all 4,837 replications in the library.

Some of the strongest results that lean on it:

Strategy Sharpe t-stat Tested over
Reversal Patterns in Risk-Adjusted Anomaly Returns +0.71 3.8 28 years
Nonlinear Factor Attribution +0.69 3.6 28 years

A Sharpe ratio quoted without its t-statistic hides how much of the library cannot be distinguished from zero, which is why both are shown. The figures are in-sample over each strategy's own window and carry no transaction costs.

Why It Matters

This dataset accelerates factor investing research and portfolio design by:

  • Systematic ranking: Pre-computed factor scores accelerate cross-sectional ranking for long/short books.
  • Style tilts: Value, quality, growth, and volatility signals allow precise style targeting and risk budgeting.
  • Attribution: Consistent factor definitions simplify performance attribution and portfolio diagnostics.

Load It

Installation/Upgrade:

pip install --upgrade pwb-toolbox

Load the Dataset:

from pwb_toolbox import datasets as pwb_ds

df = pwb_ds.load_dataset("Stocks-Quarterly-FactorSignals", symbols=["AAPL"])
print(df.iloc[0, :])

Example Output:

symbol                                    AAPL
datetime                   1998-03-31 00:00:00
profitability                             50.0
value                                     10.0
solvency                                  53.0
cash_flow                                 61.0
illiquidity                               12.0
momentum_long_term                        22.0
momentum_medium_term                      19.0
short_term_reversal                       21.0
price_volatility                          62.0
dividend_yield                            62.0
earnings_consistency                      89.0
small_size                                 1.0
low_growth                                25.0
low_equity_issuance                      100.0
bounce_dip                                61.0
accrual_growth                            59.0
low_depreciation_growth                   35.0
current_liquidity                         91.0
low_rnd                                   36.0
momentum                                  20.0
market_risk                               32.0
business_risk                             36.0
political_risk                            56.0
inflation_fluctuation                     55.0
inflation_persistence                     48.0
returns                               0.020202
rsquared                                   NaN
rsquared_adj                               NaN
fvalue                                     NaN
aic                                        NaN
bic                                        NaN
mse_resid                                  NaN
mse_total                                  NaN

Columns

Column Name Description
symbol Stock ticker.
datetime Quarter-end timestamp.
profitability Profitability factor percentile.
value Value factor percentile.
solvency Solvency factor percentile.
cash_flow Cash flow factor percentile.
illiquidity Illiquidity factor percentile.
momentum_long_term Long-term momentum percentile.
momentum_medium_term Medium-term momentum percentile.
short_term_reversal Short-term reversal percentile.
price_volatility Price volatility percentile.
dividend_yield Dividend yield percentile.
earnings_consistency Earnings consistency percentile.
small_size Small size factor percentile.
low_growth Low growth factor percentile.
low_equity_issuance Low equity issuance percentile.
bounce_dip Bounce and dip factor percentile.
accrual_growth Accrual growth factor percentile.
low_depreciation_growth Low depreciation growth percentile.
current_liquidity Current liquidity percentile.
low_rnd Low R&D spending percentile.
momentum Aggregate momentum percentile.
market_risk Market risk percentile.
business_risk Business risk percentile.
political_risk Political risk percentile.
inflation_fluctuation Inflation fluctuation percentile.
inflation_persistence Inflation persistence percentile.
returns Quarterly return used in factor regressions.
rsquared Regression R-squared value.
rsquared_adj Regression adjusted R-squared value.
fvalue Regression F-statistic.
aic Akaike information criterion.
bic Bayesian information criterion.
mse_resid Residual mean squared error.
mse_total Total mean squared error.

Access

Browsing the card and the schema is open to anyone. Downloading the files needs an approved request, tied to a subscription: what each plan includes. The same subscription covers the other datasets in this organisation.

Elsewhere

Papers With Backtest publishes 32 datasets on the Hub and codes the papers that use them. Every strategy in the catalogue is run over its own full history before it is published, which is where the numbers above come from.

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