Modeling Turning Points In Global Equity Market

Daniel Felix Ahelegbey, Monica Billio and Roberto Casarin

No 195, DEM Working Papers Series from University of Pavia, Department of Economics and Management

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. This paper develops a Bayesian technique to turning point detection in financial equity markets. We derive the interconnectedness among stock market returns from a piece-wise network vector autoregressive model. The empirical application examines turning points in global equity market over the past two decades. We also compare the Covid-19 induced interconnectedness with that of the global financial crisis in 2008 to identify similarities and the most central market for spillover propagation

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)
Pages: 18
Date: 2020-11
New Economics Papers: this item is included in nep-ecm, nep-fmk and nep-ore
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http://dem-web.unipv.it/web/docs/dipeco/quad/ps/RePEc/pav/demwpp/DEMWP0195.pdf (application/pdf)

Related works:
Journal Article: Modeling Turning Points in the Global Equity Market (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:pav:demwpp:demwp0195

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