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FAWP Alpha Index v2.1 — Information-Control Exclusion Principle detector

Project description

fawp-index

FAWP Alpha Index v2.1 — Python implementation of the Information-Control Exclusion Principle detector.

Based on research by Ralph Clayton (2026):


What is FAWP?

Future Access Without Presence (FAWP) is the condition where:

  • Predictive coupling persists — you can still forecast the future
  • Steering coupling has collapsed — you can no longer influence it

This is the Information-Control Exclusion Principle: in unstable regimes, prediction and control are conjugate variables. High predictive certainty is not a measure of mastery — it is a leading indicator of control failure.


Installation

pip install fawp-index

Or from source:

git clone https://github.com/ralphclayton/fawp-index
cd fawp-index
pip install -e .

Quick Start

From a CSV file

from fawp_index import FAWPAlphaIndex
from fawp_index.io.csv_loader import load_csv_simple

# Load data (only needs state + action columns)
data = load_csv_simple(
    "market_data.csv",
    state_col="price",
    action_col="trade_size",
    delta_pred=20,
)

# Run FAWP Alpha Index
detector = FAWPAlphaIndex(eta=1e-4, epsilon=1e-4, m_persist=5)
result = detector.compute(
    pred_series=data.pred_series,
    future_series=data.future_series,
    action_series=data.action_series,
    obs_series=data.obs_series,
)

print(result.summary())

Live data stream

from fawp_index import FAWPStreamDetector

def alert(result):
    print(f"⚠️  FAWP REGIME DETECTED at tau={result.peak_tau}, alpha={result.peak_alpha:.4f}")

detector = FAWPStreamDetector(
    window=500,
    delta_pred=20,
    on_fawp=alert,
)

# Feed data points as they arrive
for state, action in live_feed:
    detector.update(state=state, action=action)

Output

FAWPResult contains:

Field Description
tau Delay grid
alpha_index FAWP Alpha Index v2.1 at each tau
in_fawp Boolean array — True where FAWP regime detected
tau_h Empirical agency horizon
peak_alpha Maximum alpha index value
peak_tau Delay at peak alpha
pred_mi_corrected Null-corrected predictive MI
steer_mi_corrected Null-corrected steering MI

Applications

  • Financial systems — detect when forecast signal persists after execution leverage collapses
  • Weather prediction — flag when forecast certainty arrives after intervention window closes
  • Seismic monitoring — quantify predictive coupling vs zero steering (no earthquake off-switch)
  • Control systems — early warning of impending control failure via resonance spike

Citation

@misc{clayton2026fawp,
  author = {Clayton, Ralph},
  title  = {Future Access Without Presence (FAWP)},
  year   = {2026},
  doi    = {10.5281/zenodo.18673949},
}

License

MIT © Ralph Clayton 2026

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