Datasets:

paperswithbacktest
/

Stocks-Quarterly-FactorSignals

pretty_name: Stocks Quarterly FactorSignals
language:
  - en
license: other
task_categories:
  - time-series-forecasting
  - tabular-regression
tags:
  - finance
  - quantitative-trading
  - backtesting
  - algorithmic-trading
  - stocks
  - equities
  - quarterly
  - fundamentals
size_categories:
  - 100K<n<1M
extra_gated_prompt: >-
  This dataset is free to browse and gated for download. Approval is tied to a
  Papers With Backtest subscription, which also covers the other datasets in
  this organisation and the strategy catalogue at
  https://paperswithbacktest.com. Plans and what each one includes:
  https://paperswithbacktest.com/pricing
dataset_info:
  features:
    - name: symbol
      dtype: string
    - name: datetime
      dtype: string
    - name: profitability
      dtype: float64
    - name: value
      dtype: float64
    - name: solvency
      dtype: float64
    - name: cash_flow
      dtype: float64
    - name: illiquidity
      dtype: float64
    - name: momentum_long_term
      dtype: float64
    - name: momentum_medium_term
      dtype: float64
    - name: short_term_reversal
      dtype: float64
    - name: price_volatility
      dtype: float64
    - name: dividend_yield
      dtype: float64
    - name: earnings_consistency
      dtype: float64
    - name: small_size
      dtype: float64
    - name: low_growth
      dtype: float64
    - name: low_equity_issuance
      dtype: float64
    - name: bounce_dip
      dtype: float64
    - name: accrual_growth
      dtype: float64
    - name: low_depreciation_growth
      dtype: float64
    - name: current_liquidity
      dtype: float64
    - name: low_rnd
      dtype: float64
    - name: momentum
      dtype: float64
    - name: market_risk
      dtype: float64
    - name: business_risk
      dtype: float64
    - name: political_risk
      dtype: float64
    - name: inflation_fluctuation
      dtype: float64
    - name: inflation_persistence
      dtype: float64
    - name: returns
      dtype: float64
    - name: rsquared
      dtype: float64
    - name: rsquared_adj
      dtype: float64
    - name: fvalue
      dtype: float64
    - name: aic
      dtype: float64
    - name: bic
      dtype: float64
    - name: mse_resid
      dtype: float64
    - name: mse_total
      dtype: float64
  splits:
    - name: train
      num_examples: 763836

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

Dataset page and coverage charts
The strategy catalogue, 3,806 papers and 4,837 replicated strategies
pwb-toolbox, the loader used in the snippet above
awesome-systematic-trading, the replicated strategies with their measured Sharpe
Every dataset in this organisation

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.