Quantile regression for capital asset pricing model | ||
| AUT Journal of Mathematics and Computing | ||
| دوره 7، شماره 1، 2026، صفحه 63-68 اصل مقاله (764.32 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajmc.2024.23203.1240 | ||
| نویسنده | ||
| Mohammaad Zare Mohammadkhani* | ||
| Department of Statistics, Faculty of Mathematical Sciences, Alzahra University, Tehran, Iran | ||
| چکیده | ||
| In this paper, we examine the Capital Asset Pricing Model (CAPM) and demonstrate that when the log returns of an asset are subject to extreme risks or outliers or nonlinear relationship, the Linear Regression (LR) model may not perform well in predicting future returns. Instead, we propose using Quantile Regression, which is more robust to such data anomalies and provides better predictions. | ||
| کلیدواژهها | ||
| CAPM؛ QCAPM؛ Linear Regression؛ Quantile regression | ||
| مراجع | ||
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