Dual-Class Stocks: Can They Serve as Effective Predictors?
Abstract
Kardemir Karabuk Iron Steel Industry Trade & Co. Inc., ranked as the 24th largest industrial company in Turkey, offers three distinct stocks listed on the Borsa Istanbul: KRDMA, KRDMB, and KRDMD. These stocks, sharing the sole difference in voting power, have exhibited significant price divergence over an extended period. This paper conducts an in-depth analysis of the divergence patterns observed in these three stock prices from January 2001 to July 2023. Additionally, it introduces an innovative training set selection rule tailored for LSTM models, incorporating a rolling training set, and demonstrates its significant predictive superiority over the conventional use of LSTM models with large training sets. Despite their strong correlation, the study found no compelling evidence supporting the efficiency of dual-class stocks as predictors of each other's performance.
Cite
@article{arxiv.2310.16845,
title = {Dual-Class Stocks: Can They Serve as Effective Predictors?},
author = {Veli Safak},
journal= {arXiv preprint arXiv:2310.16845},
year = {2023}
}