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Modeling Nonlinear Time Series Patterns of Supply Chain Disruptions on Share Price Based Upon Firms' Account Giving and Nodal Position

2023
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Release : 2023
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Book Synopsis Modeling Nonlinear Time Series Patterns of Supply Chain Disruptions on Share Price Based Upon Firms' Account Giving and Nodal Position by : Amin Vahedian

Download or read book Modeling Nonlinear Time Series Patterns of Supply Chain Disruptions on Share Price Based Upon Firms' Account Giving and Nodal Position written by Amin Vahedian. This book was released on 2023. Available in PDF, EPUB and Kindle. Book excerpt: Organizations recognize disruptions can occur within supply chain networks with possible negative consequences. Given that the many firms are public entities, such disruptions can be flagged by the investor community and pull share prices down. In hoping to mitigate stock price erosion, organizations often employ various account giving strategies. However, to properly mitigate disruptions, organizations need to understand how disruptions along supply chains and account giving employed affect share prices over time. In this study, we rely upon Artificial Neural Networks (ANNs) to study the patterns of share price fluctuations over time (80 trading days) based upon the position of the disruption within the supply chain and the communication strategy employed. Using ANN, we go beyond prediction to plot the complex nonlinear patterns over the 80 days post disruption. Through our analysis, we demonstrate that nonlinear ANN provides greater accuracy relative to linear models. Furthermore, a time series analysis provides companies and investors with a greater degree of precision to deploy time-based hedging strategies not only to minizine losses, but also to possibly turn the disruptions into financial opportunities.

Supply Chain Disruptions and Stock Prices

2024-11-23 Business & Economics
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Release : 2024-11-23
Genre : Business & Economics
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Book Rating : 843/5 ( reviews)

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Book Synopsis Supply Chain Disruptions and Stock Prices by : Priscilla Schelp

Download or read book Supply Chain Disruptions and Stock Prices written by Priscilla Schelp. This book was released on 2024-11-23. Available in PDF, EPUB and Kindle. Book excerpt: Supply chain disruptions typically hurt stock prices, particularly if the disruption is caused by a natural disaster. While supply chains in the United States suffer from a wide range of supply chain disruptions induced by hurricanes, the impact of these disruptions on stock prices remains unexplored, even though the annual average damage in the US due to hurricanes is $54bn of which $9bn is to businesses. This book explores, classifies, and connects natural disasters, supply chain disruption (SCD), and firm financial performance. It identifies influencing factors and how they impact the effect of hurricanes on stock prices. It defines a statistical model to quantify the effect of hurricanes on stock prices and provides guidelines to managers who need to decide how to communicate supply chain disruptions to their customers and shareholders. It will be of great interest to scholars and students in supply chain management, disaster management, and finance.

Modelling Supply Chain Adaptation for Disruptions

2019
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Release : 2019
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Book Synopsis Modelling Supply Chain Adaptation for Disruptions by : Kang Zhao

Download or read book Modelling Supply Chain Adaptation for Disruptions written by Kang Zhao. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt: Through the development and usage of an agent-based model, this paper investigates firms' adaptive strategies against disruptions in a supply chain network. Viewing supply chain networks as complex adaptive systems (CAS), we first construct and analyze a real-world supply chain network among 2,971 firms spanning 90 industry sectors. We then develop an agent-based simulation to show how the model of firms' adaptive behaviors can leverage competition relationships within a supply chain network. The simulation also models how disruptions propagate in the supply chain network through cascading failures. With the simulation, we seek to understand if firms' adaptive behaviors can reduce the impact of disruptions in these networks. Therefore, we propose, evaluate, and analyze two types of adaptive strategies a firm can leverage to reduce the negative effects of supply chain network disruptions. First, we deploy in our model a reactive strategy, which restructures the network in response to a disruption event among first- tier suppliers. Next, we develop and propose proactive strategies which are used when a distant disruption is observed but has not yet hit the focal firm. We discuss the implications related to how and when firms can improve their resilience against supply disruptions by leveraging adaptive strategies.

Modeling the Impact of Large-scale Disruptions on Supply Chain Networks and Their Recovery

2019
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Release : 2019
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Book Synopsis Modeling the Impact of Large-scale Disruptions on Supply Chain Networks and Their Recovery by : Ni Ni

Download or read book Modeling the Impact of Large-scale Disruptions on Supply Chain Networks and Their Recovery written by Ni Ni. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt:

Non Linear Economic Time Series as a Testbed for Dynamic Macro Models

2019
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Release : 2019
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Book Synopsis Non Linear Economic Time Series as a Testbed for Dynamic Macro Models by : Michael Wood

Download or read book Non Linear Economic Time Series as a Testbed for Dynamic Macro Models written by Michael Wood. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt: This is a short exercise in using nonlinear time series analysis (NLTS) to assess the fit of a dynamic nonlinear macro economic process, the Goodwin model, against “realworld” nonlinear time series.The methodology follows the approach developed by Huffaker (2015 and variously) 1 After simulating the Goodwin model and generating plausible time series and an attractor a topologically equivalent attractor is extracted from a single dimension (unemployment) from the Goodwin model.Real US unemployment data is then subjected to SSA analysis to extract a signal from any background “noise” and this signal is then subject to time delay embedding. The attractor resulting from the SSA/Takens process to US unemployment data is topologically equivalent to the attractor from the Goodwin / Predator Prey phase portrait. This primae facie, suggests that the (assumed “black box”) nonlinear economic process which generated these statistics could well have had Goodwin characteristics. The solution is both a limit cycle but also the amplitude (ratio of profitability and unemployment) suddenly increases. This probably reflects that the time series covers the “great moderation” and the subsequent 07/08 crash. This is also a characteristic of more complex nonlinear models like Keen (1997) and suggests that a similar exercise with Keens model and private debt statistics would be interesting.

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