A Stock Optimization Problem in Finance: Understanding Financial and Economic Indicators through Analytical Predictive Modeling

Aditya Chakraborty () and Chris Tsokos
Additional contact information
Aditya Chakraborty: Joint School of Public Health Initiative, Old Dominion University, Norfolk, VA 23529, USA
Chris Tsokos: Department of Mathematics & Statistics, University of South Florida, Tampa, FL 33620, USA

Mathematics, 2024, vol. 12, issue 15, 1-17

Abstract: Given the significant impact of healthcare stock changes on the global economy, including its GDP and other financial factors, we endeavored to create an analytical prediction model for forecasting the annual percentage change of these stocks. Our model, which is nonlinear, incorporates five key discoveries. We focused on predicting the average weekly closing price (pWCP) of AbbVie Inc. (North Chicago, IL, USA)’s healthcare stock (ABBV) from 1 August 2017 to 31 December 2019. The stock was chosen based on the low beta risk, high dividend yield, and high yearly percentage return criteria. Alongside predicting the weekly stock price, our model identifies the individual indicators and their interactions that notably influence the response. These indicators were ranked based on their contribution percentages to the response. The validity of the model was justified based on the root mean square error (RMSE) and R 2 value by performing 10-fold cross-validation. Furthermore, an optimization process using the desirability function was implemented to determine the optimal values of the indicators that maximize the response, along with the 95% confidence and 95% prediction interval. We also visually depicted the optimal ranges of any two indicators that affect the response AWCP. In our evaluation, we compared the original and predicted responses of AWCP using our analytical model. The results demonstrated a close alignment between the two sets of observations, highlighting the high accuracy of our model. Beyond these findings, our model provides additional valuable insights into the subject area. It has undergone thorough validation and testing, confirming its high quality and the precision of our weekly stock price predictions. The information derived from the modeling and analysis is important for constructive and accurate decision-making for individual investors, portfolio managers, and financial institutions concerning the financial and economic aspects of the healthcare industry. By identifying the optimum values of the controllable contributors through the optimization process, financial institutions can make the strategic changes needed for the company’s long-term viability.

Keywords: healthcare stocks; economic indicators; response optimization; desirability function; nonlinear analytical modeling (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/15/2407/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/15/2407/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:15:p:2407-:d:1448527

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().