Highlights
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This paper analyzes and summarizes the various factors that affect global gold price.
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A reverse process of response surface methodology (RSM) is first used in this paper.
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The results show that all factors have a negative impact on the price of gold except CPI.
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The interraction effect between factors that include CPI and Oil price is complicated.
Abstract
As one of the most widely purchased investment products for global investors, the price of gold is increasingly attracting attention. This paper analyzes and summarizes the various factors that affect global gold price. A reverse process of response surface methodology(RSM) is first used to evaluate the impact of six different factors(namely, the dollar index, the federal funds rate, CPI, exchange rate, oil price and S&P500) on the gold price. The results show that all factors have a negative impact on the price of gold except CPI. Furthermore, the impact of CPI and Oil price on response variable is not significant at the 5% significance level, which also makes the interaction effect involving these two factors more complicated.
Introduction
Gold serves several functions in the world economy, and its link with financial and macroeconomic variables is well established (Pierdzioch et al., 2014a, b). It has monetary value and is sought after by central banks to be part of their international reserves(Gupta et al., 2014). It has industrial uses and can be transformed into jewellery. Gold has been traditionally used by investors as a hedge in portfolio diversification and a safe haven in times of extreme economic and political turbulence and severe market turmoil (Baur and Lucey, 2010; Baur and McDermott, 2010; Lau et al., 2017; O’Connor et al., 2015). Gold is also a special commodity that has financial and monetary functions. Although the monetary function of gold has been weakened since the collapse of the Bretton Woods System in February 1973, the financial asset function of gold has continued its importance (Wang et al., 2016). Gold has also other distinguished characteristics. Its supply is accumulated over the years, and its global annual physical production can be as small as 2% of total supply. So in contrast to other commodities, its annual production may not sway its price as other factors do. Given the significance of gold in the modern world, the ability to analyze the price of gold will be of utmost importance.
The global financial crisis that broke out at the end of 2007 has caused global capital markets to suffer, and the risks of various securities and futures have increased rapidly. However, the price of gold was showing an upward trend at the same time. The price of gold changed from $672 per ounce in August 2007 to $933 per ounce in March 2008. After 2012, the price of gold skyrocketed to $1700 per ounce due to the loose monetary policy adopted by many developed countries in order to stimulate the economy. In April 2013, the price of international gold fell to $1481 per ounce and suffered the biggest weekly decline during December. After that, the gold price basically went downward to $1059 per ounce by the end of November 2015. And then it continued to rise to $1350 per ounce in July 2016. Fig. 1 describes the trend of gold price from 1990 to 2018, of which the data are obtained from the WORLD GOLD COUNCIL. The large fluctuations in the price of gold have caused widespread concern in the market. And the current market has a wide divergence in the trend of future gold prices. In the new economic situation, why is the price of gold changing in this way? Motivated by this question, we first explore and select representative influencing factors considering the attributes of gold, and then use the measurement method to empirically analyze these factors.
A myriad of different global variables affect the price of gold(Pierdzioch et al., 2014a), which include the US dollar index, the interest rate, the inflation rate, the exchange rate, the oil price and the stock market. The relationship between gold prices and major individual variables is not stable and is time-varying. To the best of our knowledge, this is the first study to analyze the effects of six different factors on gold price fluctuations based on response surface method(RSM) (Li et al., 2015; Ren et al., 2016; Bartley et al., 2016), which uses a reasonable experimental design method and obtains certain data through experiments. The multivariate quadratic regression equation is used to fit the functional relationship between the factors and the response values. It is a statistical method for multivariate problems.
What is innovative is that we view our observations of gold price and the value of factors that may influence the price of gold as the results of multiple experiments. We restore the experimental design (Box–Behnken design,BBD; see e.g. Nam et al., 2018; Tak et al., 2015; Bakhtiari et al., 2016) from the experimental results, and then get the quadratic regression relationship between the dependent variable and the independent variable, the specific steps of which can be seen in section 4. The remainder of the paper is organized as follows. Section 2 presents a brief review of the literature. Section 3 discusses the factors that influence the global gold price. Section 4 describes methodology and empirical results. Section 5 concludes the paper.
Section snippets
Literature review
The literature on analyzing effects of different factors on the price of gold is not as generous as it is in analyzing gold return and volatility, and the methods employed are not as sophisticated either. O’Connor et al. (2015) provide a good review of relevant literature. Ewing and Malik (2013) examine the volatility of gold and oil futures incorporating structural breaks by employing univariate and bivariate GARCH models. They provide strong evidence of significant transmission of volatility
Data
The monthly data for the price of gold and the demand and supply of gold are obtained from the WORLD GOLD COUNCIL. The dollar index、the US federal funds rate are obtained from the Board of Governors of the Federal Reserve System. The monthly data for CPI are acquired from the BUREAU OF LABOR STATISTICS. The original monthly exchange rate is also used in this study, and the data are obtained from the Wind Database. The monthly data for the oil price are obtained from U.S. Energy Information
Data description
Our paper considers the price of gold as the dependent variable. Factors we analyze in this section include the US dollar index, the US federal funds rate, CPI, exchange rate, oil price and S&P500. The source of the data is the same as described in 3.1, but the sample interval we select in the empirical study is from January 2000 to December 2018.
Box–Behnken design
Box–Behnken design (BBD), a commonly used form of RSM, was used to analyze the factors affecting global gold price. We consider 6 factors including
Results and discussion
We performed multiple linear regression and binomial fitting on the experimental data in the above table by using Design Expert to obtain a multivariate quadratic regression response surface model. And the final estimated response model equation for the gold price in terms of coded factors is shown in the following equation:𝑌=869.41−122.25𝐴−181.25𝐵+55.68𝐶−233.53𝐷−3.5𝐸−73.41𝐹+151.17𝐴𝐸+164.77𝐵𝐷+436.66𝐶𝐷−59.53𝐶𝐸+153.12𝐴2+355.06𝐶2−124.84𝐹2
As can be clearly noted in Fig. 8, all of the predicted
Conclusion
This paper begins with a concise introduction relating to the importance of gold in the world economy. Motivated by this, we investigate the determinants of the price of gold with a particular attention on six different factors (i.e., the dollar index, federal funds rate, CPI, the exchage rate, oil price and S&P500). In the empirical study, we get a multivariate quadratic equation for the relationship between gold price and the six factors. The model fits well through the fitting figure between