Modeling Turning Points in the Global Equity Market

Daniel Felix Ahelegbey, Monica Billio and Roberto Casarin

Econometrics and Statistics, 2024, vol. 30, issue C, 60-75

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.

Keywords: Bayesian inference; Dynamic Programming; Turning points; Networks; VAR (search for similar items in EconPapers)
JEL-codes: C11 C15 C51 C52 C55 C58 G01 (search for similar items in EconPapers)
Date: 2024
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Working Paper: Modeling Turning Points In Global Equity Market (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:30:y:2024:i:c:p:60-75

DOI: 10.1016/j.ecosta.2021.10.004

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