Re-examining the leverage effect and gold's safe haven properties with the utilization of the implied volatility of
1Department of Economics, University of Ioannina, Ioannina, Greece.
Abstract:
Gold as a tradable financial asset has acquired the reputation of a safe haven from market turbulence. The objective of this study is to investigate empirically the relationship between gold prices and implied volatility in the futures markets of gold, re-examine the leverage hypothesis and attempt to make inferences about gold's safe haven properties. In doing so, it utilizes the recently developed econometric tool of non-parametric quantile regressions. This is the first work to apply the flexible non-parametric quantile regressions on the exchange-traded funds (ETFs) of gold. The data used are daily returns of options of gold shares and implied volatility changes from June of 2008 to December of 2018. The empirical findings indicate that, for the total sample period as well as for almost all of the five sub-periods examined, changes in the implied volatility of gold are insensitive, and not statistically significant, to changes in the price returns of gold. The leverage hypothesis holds for a wide range in the third sub-period. Accordingly, investors in other ETFs (currency or oil) may choose to use gold as shelter during (extreme) economic downturns.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s43546-021-00092-3.
More Related Videos
13:04Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Published on: September 19, 2012
13:54A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
Published on: August 18, 2023
Related Concept Videos
01:14Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
01:19Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
01:12Quantitative Analysis
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...
01:16Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
01:02Quantifying and Rejecting Outliers: The Grubbs Test
01:09Empirical Method to Interpret Standard Deviation
This rule is used widely in statistics to calculate the proportion of data values...