Dual-Class Stocks: Can They Serve as Effective Predictors?

ArXiv ID: 2310.16845 “View on arXiv”

Authors: Unknown

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.

Keywords: Long Short-Term Memory (LSTM), Rolling training set, Dual-class stocks, Price divergence, Time series prediction, Equities

Complexity vs Empirical Score

• Math Complexity: 6.5/10
• Empirical Rigor: 7.0/10
• Quadrant: Holy Grail
• Why: The paper applies advanced mathematical techniques like continuous wavelet transform (CWT) and LSTM architecture with detailed mathematical formulations, showing significant math density. Empirically, it uses a long historical dataset (2001-2023), introduces a novel rolling training set methodology for LSTM, and compares approaches with clear quantitative evaluation, indicating strong backtest-readiness.

  flowchart TD
    A["Research Goal: Assess if dual-class stocks are effective predictors of each other"] --> B["Data Acquisition<br>3 Stocks KRDMA/KRDMB/KRDMD<br>Jan 2001 - Jul 2023"]
    B --> C["Methodology: LSTM Models with Rolling vs. Fixed Training Sets"]
    C --> D{"Computational Analysis"}
    D --> E["Price Divergence Analysis"]
    D --> F["Predictive Accuracy Comparison"]
    E --> G["Key Findings: Significant Price Divergence"]
    F --> H["Key Findings: Rolling Set Superior to Fixed Set"]
    H --> I["Key Findings: No Evidence of Dual-Class Stock Predictive Efficiency"]
    G --> I