Joshua Della Vedova

Execution Edge Monitor

The algorithmic-minus-retail Prelec alpha gap. A behavioral proxy for execution-quality divergence.

As of 2026-04-20, the alpha gap stands at -0.052, with a 52-week rolling z-score of -1.38. Algorithmic Prelec alpha: 0.671. Active retail Prelec alpha: 0.723. Week based on 119,852 trades across all classes.

Weekly history

A positive gap indicates algorithmic wallets weight tails more heavily than active retail. The bold line is a 13-week moving average.

Current per-type alphas

Wallet classPrelec alpha
Algorithmic0.671
Active Retail0.723
Sophisticated0.721
Casualn/a
One-Shotn/a

52-week rolling statistics on the gap

StatisticValue
Mean0.106
SD0.115
Min-0.186
Max0.346

Methodology

For each wallet class (algorithmic, active retail, sophisticated, casual, one-shot), we fit a one-parameter Prelec weighting function to that class’s weekly calibration curve. The resulting alpha captures how strongly the class distorts probabilities away from the identity. The Execution Edge gap is alpha(algorithmic) minus alpha(active retail). In Paper 1, algorithmic wallets capture −4.25 bps effective spread on their trades while active retail pays +11.68 bps; the alpha gap is the behavioral signature of that divergence and tracks it week-by-week.

Data

execution_history.csv (wide, 173 weeks from 2022-12-12) · execution_by_type_history.csv (long) · execution_latest.json

Cite

@misc{dellavedova2026execution, title = {Execution Edge Monitor}, author = {Della Vedova, Joshua}, year = {2026}, version = {0.1.0}, publisher = {University of San Diego}, url = {https://jdellavedova.com/execution} }