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

PSU Research Review

Teik-Kheong Tan¹ 

关键词: Implied volatility;    Factor analysis;    Bayesian;    Data analytics;    Machine learning;    Structured equation modeling;   

DOI  :  10.1108/PRR-04-2017-0023

学科分类：社会科学、人文和艺术（综合）

来源: Emerald Publishing

【 摘 要 】

Purpose 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 good model fit for the constructs. Design/methodology/approach This section describes the methodology used for conducting the study. This includes the study area, study approach, sources of data, sampling technique and the method of data analysis. Findings Although there is extensive literature on methods for estimating IV dynamics during earnings announcement, few researchers have looked at the impact of ex...

【 授权许可】

CC BY