Turning points in financial markets are often characterized by changes in the direction and/or magnitude of market movements with short-to-long term impacts on investors’ decisions. A Bayesian technique is developed for turning point detection in financial equity markets. The interconnectedness among stock market returns from a piece-wise network vector autoregressive model is derived. The turning points in the global equity market over the past two decades are examined in the empirical application. The level of interconnectedness during the Covid-19 pandemic and the 2008 global financial crisis are compared. Similarities and most central markets responsible for spillover propagation emerged from the analysis.

Modeling Turning Points in the Global Equity Market

Daniel Felix Ahelegbey
Conceptualization
;
2021

Abstract

Turning points in financial markets are often characterized by changes in the direction and/or magnitude of market movements with short-to-long term impacts on investors’ decisions. A Bayesian technique is developed for turning point detection in financial equity markets. The interconnectedness among stock market returns from a piece-wise network vector autoregressive model is derived. The turning points in the global equity market over the past two decades are examined in the empirical application. The level of interconnectedness during the Covid-19 pandemic and the 2008 global financial crisis are compared. Similarities and most central markets responsible for spillover propagation emerged from the analysis.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11571/1444054
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