Discussion Papers 2022

CIRJE-F-1205	"Big Data Applications with Theoretical Models and Social Media in Financial Management"
Author Name	Saito, Taiga and Shivam Gupta
Date	December 2022
Full Paper	PDF file
Remarks	Forthcoming in Annals of Operations Research.

Abstract
This study presents big data applications with quantitative theoretical models in financial management and investigates possible incorpora- tion of social media factors into the models. Specifically, we examine three models, a revenue management model, an interest rate model with market sentiments, and a high-frequency trading equity market model, and consider possible extensions of those models to include social media. Since social media plays a substantial role in promoting prod- ucts and services, engaging with customers, and sharing sentiments among market participants, it is important to include social media fac- tors in the stochastic optimization models for financial management. Moreover, we compare the three models from a qualitative and quan- titative point of view and provide managerial implications on how these models are synthetically used along with social media in financial management with a concrete case of a hotel REIT. The contribution of this research is that we investigate the possible incorporation of social media factors into the three models whose objectives are revenue management and debt and equity financing, essential areas in finan- cial management, which helps to estimate the effect and the impact of social media quantitatively if internal data necessary for parameter estimation are available, and provide managerial implications for the synthetic use of the three models from a higher viewpoint. The numer- ical experiment along with the proposition indicates that the model can be used in the revenue management of hotels, and by improving the social media factor, the hotel can work on maximizing its sales.
Keywords: Big data applications, Revenue management, Social media, Financial management

Abstract

This study presents big data applications with quantitative theoretical models in financial management and investigates possible incorpora- tion of social media factors into the models. Specifically, we examine three models, a revenue management model, an interest rate model with market sentiments, and a high-frequency trading equity market model, and consider possible extensions of those models to include social media. Since social media plays a substantial role in promoting prod- ucts and services, engaging with customers, and sharing sentiments among market participants, it is important to include social media fac- tors in the stochastic optimization models for financial management. Moreover, we compare the three models from a qualitative and quan- titative point of view and provide managerial implications on how these models are synthetically used along with social media in financial management with a concrete case of a hotel REIT. The contribution of this research is that we investigate the possible incorporation of social media factors into the three models whose objectives are revenue management and debt and equity financing, essential areas in finan- cial management, which helps to estimate the effect and the impact of social media quantitatively if internal data necessary for parameter estimation are available, and provide managerial implications for the synthetic use of the three models from a higher viewpoint. The numer- ical experiment along with the proposition indicates that the model can be used in the revenue management of hotels, and by improving the social media factor, the hotel can work on maximizing its sales.

Keywords: Big data applications, Revenue management, Social media, Financial management