Abstract
This paper presents a pedagogically driven application of a quantitative investment signaling model based on two standard deviation bands. Deviations beyond the two standard deviation range are interpreted as potential mean reversion signals, triggering tactical shifts in asset allocation or trading actions. Students construct the models in Excel using live market data, overlaying asset returns against calculated deviation bands to inform decisions. The firsthand approach emphasizes applied learning and critical thinking, with students analyzing model results and presenting empirical findings. Evidence suggests this experiential method significantly enhances student engagement, comprehension, and retention of investment strategy concepts across diverse financial settings
Recommended Citation
(2026)
"An Empirical Implementation of a Two-Standard-Deviation Investment Signaling Framework Across Multiple Asset Classes,"
Journal of Economics and Finance Education: Vol. 24:
Iss.
1, Article 2.
Available at:
https://scholarship.rollins.edu/jefe/vol24/iss1/2
