Evaluating the Nonlinear Linkage between Gold Prices and Stock Market Index Using Markov-Switching Bayesian VAR Models

Abstract

This study makes a contribution to the literature by applying the Markov-Switching Bayesian VAR models for the first time to investigate the nonlinear linkage between gold prices and stock market index. Analyses have been done in the period from 1986:04 to 2013:11. The Bayesian approach to econometrics provides a general method for combining modeller's beliefs with the evidence contained in the data. In contrast to the classical approach to estimate a set of parameters, Bayesian statistic presupposes a set of prior probabilities about the underlying parameters to be estimated. We use gold prices (USD/oz.) and S&P 500 Stock Price Index as an endogenous, the crude oil prices (Brent-$/barrel) as an exogenous variable in the analysis. We investigate the number of regime by LR test and The Markov Chain Monte Carlo (MCMC) algorithm and Sims & Zha (1998) prior distribution are employed to estimate the models.

Dependence between the global gold market and emerging stock markets (E7+1): Evidence from Granger causality using quantile and quantile‐on‐quantile regression methods

“…The literature on the dynamic relations among various commodity prices and the stock market is extensive and widespread across major regions of the world. These relations have been explored for the global market (Kang, McIver, & Yoon, ; Reboredo & Ugolini, ; Sadorsky, ), cross countries (Ciner, Gurdgiev, & Lucey, ; Choudhry, Hassan, & Shabi, ; Raza, Shahzad, Tiwari, and Shahbaz (), Asia (Arouri, Lahiani, & Nguyen, ; Bouri, Jain, Biswal, & Roubaud, 2017a; Bouri, Roubaud, Jammazi, & Assaf, 2017b; Huang, An, Gao, & Huang, ; Kumar, ; Mensi, Hammoudeh, Reboredo, & Nguyen, ; Ziaei, ), Europe (Charlot & Marimoutou, ; Hoang, Lean, & Wong, ; Shahzad, Raza, Shahbaz, & Ali, ), United States (Akgül, Bildirici, & Özdemir, ; Baruník, Kočenda, & Vácha, ; Baumöhl & Lyócsa, ; Bekiros, Nguyen, Uddin, & Sjö, ; Creti, Joëts, & Mignon, ; Gokmenoglu & Fazlollahi, ; Hood & Malik, ; Mensi, Beljid, Boubaker, & Managi, ) and Australia (Bekiros, Hernandez, Hammoudeh, & Nguyen, ).…”

“…Moreover, Akgül et al. () suggested that Markov‐Switching Bayesian VAR models can be used to evaluate the non‐linear association between gold prices and the stock market index using data covering the period from April 1986 to November 2013. They discovered that in the pre‐crisis and crisis periods, gold prices exhibited a diminishing response to S&P 500 shocks, although the response reversed in the second period, the growth period.…”

Time-Varying Effect of Gold and Crude Oil prices to Stock Price Index

“…In the empirical research studies, there are many evidences presenting the relationships or dependences between stock price index and other commodity market particularly gold market and crude oil market. For example, Akgül et al [1], Basher et al [2] and Philip et al [3] have confirmed the evidence of the relationship between oil price, gold and stock price index. Fig.…”

“…The co-movements among these price indexes have attracted to increase the attention of financial managers and researchers to examine their linkages because the relationships are importantly implicated in economy as well as in financial markets. In addition, Akgül et al [1], Basher et al [2], Philip et al [3] indicated that the relationships of gold and crude oil price to stock price index are differently in the different situation or regimes. The research study is to consider the time-varying effect of gold and crude oil price to stock price index by applying Markov switching state-space model.…”

Do Global Financial, Oil and Gold Volatility Shocks Affect the GCC Stock Markets?

“…He showed that there is tail independence between the oil and gold markets, meaning that gold can work as an effective hedge against the fluctuation of oil price. Other studies that investigated on this subject matter were Akgül, Bildirici, and Özdemir (2015), Basher and Sadorsky (2006), Chkili (2016), Hassan and Shabi (2015), Kumar (2017), Le and Chang (2012), and Mollick and Assefa (2012).…”