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A big data Bayesian approach to earnings profitability in the S&P 500


Tan, Teik Kheong and Merouane, Lakehal-Ayat (2018) A big data Bayesian approach to earnings profitability in the S&P 500. PSU Research Review, 2 (1). pp. 35-58. ISSN 2399-1747

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Abstract

The impact of volatility crush can be devastating to an option buyer and results in a substantial capital loss, even with a directionally correct strategy. As a result, most volatility plays are for option sellers, but the profit they can achieve is limited and the sellers carry unlimited risk. This paper aims to demonstrate the dynamics of implied volatility (IV) as being influenced by effects of persistence, leverage, market sentiment and liquidity. From the exploratory factor analysis (EFA), they extract four constructs and the results from the confirmatory factor analysis (CFA) indicated a goodmodel fit for the constructs.

Item Type: Journal
Uncontrolled Keywords: Implied volatility; Factor analysis; Bayesian; Data analytics; Machine learning; Structured equation modeling
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HD Industries. Land use. Labor
Divisions: School of Graduate Studies
Depositing User: Ms Nur Liyana Abd Halil
Date Deposited: 29 Jun 2019 00:40
Last Modified: 29 Jun 2019 00:40
URI: http://ur.aeu.edu.my/id/eprint/542

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