Presentation Title

A New Population Analysis Approach for Analyzing Financial Markets under Crises

Advisor Information

Dr. Hesham Ali

Location

MBSC Dodge Room 302A - G

Presentation Type

Oral Presentation

Start Date

4-3-2022 2:00 PM

End Date

4-3-2022 3:15 PM

Abstract

Stock markets play an important role in shaping an economic portfolio of investors in many countries and are often used as critical ways to measure economic health and financial status in impactful studies. Financial markets are often volatile and can be influenced by a wide range of direct and indirect variables. Global crises, such as the current Covid-19 Pandemic, have severely impaired the economic markets in many parts of the world and negatively affected millions of investors. While some financial markets or stocks are expected to recover or partially recover from a major crisis, others may not. With recent crises, such as the 2008 economic crash or the economic impact of the 9/11 event, researchers are looking for innovative ways to analyze the behavior of financial markets under crisis. This study proposes a new network model and employs a population analysis approach to address such an important research question. We present the basic steps to illustrate how to construct correlation networks of financial stocks and how to utilize graph-theoretic properties of the constructed networks to analyze the behavior of stocks over a given period of time. We apply the correlation network analysis on different financial data and study the financial implications of two major events, the 2008 economic crash, and Covid-19. In particular, we use the network models to compare the behavior of different economic sectors and uncover the similarities and differences between sectors and their reactions or behavior during these two events. We were able to obtain certain patterns and extract useful information from the correlation networks. We observed that companies in finance sectors behave in a similar way under the effect of both events. We also identifies some similarities between the behavior of the energy sector during the current pandemic and the utility sector during the 2008 crash.

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Mar 4th, 2:00 PM Mar 4th, 3:15 PM

A New Population Analysis Approach for Analyzing Financial Markets under Crises

MBSC Dodge Room 302A - G

Stock markets play an important role in shaping an economic portfolio of investors in many countries and are often used as critical ways to measure economic health and financial status in impactful studies. Financial markets are often volatile and can be influenced by a wide range of direct and indirect variables. Global crises, such as the current Covid-19 Pandemic, have severely impaired the economic markets in many parts of the world and negatively affected millions of investors. While some financial markets or stocks are expected to recover or partially recover from a major crisis, others may not. With recent crises, such as the 2008 economic crash or the economic impact of the 9/11 event, researchers are looking for innovative ways to analyze the behavior of financial markets under crisis. This study proposes a new network model and employs a population analysis approach to address such an important research question. We present the basic steps to illustrate how to construct correlation networks of financial stocks and how to utilize graph-theoretic properties of the constructed networks to analyze the behavior of stocks over a given period of time. We apply the correlation network analysis on different financial data and study the financial implications of two major events, the 2008 economic crash, and Covid-19. In particular, we use the network models to compare the behavior of different economic sectors and uncover the similarities and differences between sectors and their reactions or behavior during these two events. We were able to obtain certain patterns and extract useful information from the correlation networks. We observed that companies in finance sectors behave in a similar way under the effect of both events. We also identifies some similarities between the behavior of the energy sector during the current pandemic and the utility sector during the 2008 crash.