Have you ever wondered if you could reduce your exposure to risk before it is too late? For decades individuals and scholars have been stumped trying to determine a key indicator for predicting stock market volatility. In this study the daily closing prices for the copper spot market were used to see if it has historically led the S&P 500. By using technical analysis techniques on a 5, 10, and 15-year chart of the copper spot market and the S&P 500 solid conclusions were able to come to light. 66% of the time over the past 15 years the spot market for copper has led the S&P 500. Key trends were also identified to foretell that the S&P 500 might experience a market correction in the near future, while also giving us a price floor for copper prices. These are strong indicators which, if followed, could allow an organisation to improve its bottom line and/or give it the potential to make a profit from future market fluctuations.
Stock market volatility has long been an issue to which companies have aimed to reduce their exposure. Unfortunately today’s financial markets are heavily integrated and it is difficult to avoid the dramatic effects of a market downturn no matter where your investments lie. The current global economic environment for large commodity-driven organisations is almost in a state of financial crisis. For decades gold has been idolised as the ultimate flight to safety instrument to hedge against market volatility. Gold historically has been popular due to it being a tangible asset that was once the cornerstone of various countries’ currencies. In the week of 8 November 2015 there were two Wall Street Journal articles highlighting the global rout in copper markets and how this could spell disaster for companies like Glencore. Glencore is currently ranked number 10 on Fortune’s 500 list of the largest companies in the world. These articles sparked a question: could this hardship that Glencore is now enduring been avoided or at the very least mitigated? Copper prices, which are denominated in US dollars, have been shaken to the core. The reasons for this stem from global supply outpacing demand, the US dollar continuing to appreciate against various currencies, and a dismal global economic outlook. These main factors have many countries and companies readjusting their future growth estimates.
Copper is the most actively traded base metal and is a key material in various industrial applications, from “electronics, electrical products, construction and infrastructure” (Erheriene; see references). Copper was chosen as the independent variable due to it being highly integrated with global industry. The goal of this study is to identify if there is a relationship between copper prices and stock market volatility. My research question is “do copper spot prices lead the S&P 500?” In 2010, according to the China Iron and Steel Association (CISA), “China, which is currently the world’s largest consumer of copper, accounted for half of the world’s total copper consumption in 2010.” China has reduced its economic growth forecasts for the coming years. The Wall Street Journal mentioned that copper is “reeling from a trifecta of weaker demand, growing supply and a rocketing dollar” (Erheriene). At current prices “15% to 20% global production capacity is loss making” (Erheriene). Companies like Glencore would benefit from this study because it would offer support and foresight into future market fluctuations so they can properly adjust asset allocations and utilise hedging techniques to protect their bottom line.
The primary purpose of this study is to examine the relationship between copper spot prices and the overall stock market to see if copper prices lead stock market price fluctuations. A literature review was performed using leading financial and economic journals to see if anyone had performed similar studies on copper prices and stock market price fluctuations within the past three years. The goal here was to find studies that are up to speed with current market conditions and academic findings.
Studies by Rutledge, Karim, & Wang (2013) began to examine the 5-year daily closing prices of copper futures contract data from the London Metals Exchange, Shanghai Futures Exchange, and the New York Mercantile Exchange division (p. 113). Their study utilised cointegration tests, a vector error correction model (VECM), followed by a test for Granger causality to provide an improved understanding of the cross-market interaction for the copper futures market. Their goal was to be able to assist investors in formulating better trading and asset allocations by providing correlations between the world’s copper futures and volatility. Rutledge and his team were also trying to determine if there were any opportunities for arbitrage in the copper futures market between the three main exchanges. Rutledge, Karim, & Wang (2013) concluded that the three main copper markets can be regarded as one continuous trading market, where information transmission is both efficient and effective (p.113). Their study also found that arbitrage opportunities are not available from cross-market trading. However, the LME and COMEX were found to have a reverse short-term effect on the SHFE market. SHFE copper future investors have opportunities to hedge their portfolio in the LME and COMEX markets and vice versa (Rutledge, Karim, & Wang 2013, p. 129).
Christopher Plantier’s (2013) study presented information on how the rise and fall of commodity prices on a monthly basis are strongly related to two things: the value of the US dollar and the world business cycle (p. 231). Furthermore, the world business cycle is strongly correlated with the strength and weakness of emerging market economies such as Brazil, Russia, India, and China (a.k.a. BRICs). “Widespread growth in emerging economies was marked by industrialisation and rapid expansion of living standards,” according to Plantier. “Resource-intensive processes led to huge increases in the physical demand for commodities like copper” (Plantier, 2013, p. 232). Supply and demand have always been key to price determination in any market. The essential take-away here is that emerging markets play the key role in price discovery because they are amongst the biggest customers and have a growing appetite. The second part of Plantier’s (2013) study details that the value of the US dollar plays a key role in a commodity’s price. Commodities, like copper, are priced in US dollars across the world (p. 235). If the US dollar appreciates, like it has recently, then copper, along with the other dollar-denominated commodities, will become more expensive to other countries.
Wang, Lin & Li, (2013) performed a study testing the correlation and hedging effects between commodity and stock markets. They ran cointegration and Granger causal relationship testing for each major segment contained within the Rogers International Commodity Index. Part of their study included a break-out for a metals index and, therefore, this part was the main focus in tying the authors’ research to this study. The authors noted in their conclusion that “a holistic commodities index cannot be used to identify the correlation between stock markets and different types of commodities, therefore preventing the development of clear hedging strategies for investors” (Wang, Lin & Li, 2013, p. 294). This means that there is an opportunity to determine hedging strategies by identifying specific commodities that correlate with the stock market. Wang, Lin & Li, (2013) were also able to determine that commodity metal markets generally led stock markets in the following countries and regions: China, India, Russia, South Korea, Taiwan, and Africa (p. 295), whereas the US stock market led the RICI Metals Index (p. 295). One could assume Wang, Lin & Li’s (2013) findings to be correct since the US is extremely integrated into the global economy. But this is something worth noting because this study will test Wang, Lin & Li’s (2013) findings.
Summarising the literature review, the results of one of the studies have shown us that the metals market generally leads the stock market in emerging markets such as China, India, Russia, South Korea, Taiwan, and Africa (Wang, Lin & Li’s, 2013,p. 295), whereas in the US the stock market tends to lead the metals market. Christopher Plantier’s (2013) article provided insight into price discovery in the commodities market. His research can be generalised to the copper industry as the copper market is a significant component in the UBS Commodities Index he used in his study. Plantier’s (2013) study coupled with results from Rutledge, Karim, & Wang’s (2013) article set a great foundation for understanding that copper markets are both efficient and effective. Also, they added how copper derives its value from the strength of the US dollar and growth outlooks of emerging market economies. The transfer of information within the global copper markets is both efficient and effective, plus commodities markets tend to lead stock markets in most emerging economies. This highlights a potential opportunity to identify the copper spot market as a key indicator for stock market volatility.
My primary method of analysis is Technical Analysis, which has not been as well used as statistics, regression analysis, Granger causality analysis, and/or cointegration. If this study showsthat copper prices do lead S&P 500 prices, a useful forecasting tool will have been identified. Technical Analysis is identified by the web site, Investopedia, as “a method of evaluating securities by analysing statistics generated by market activity, such as past prices and volume. Technical analysts do not attempt to measure a security’s intrinsic value, but instead use charts and other tools to identify patterns that can suggest future activity” (Investopedia). Technical analysis is often an overlooked tool. Other types of statistical analysis, although quite useful, sometimes get us lost in the numbers. 5, 10, and 15-year charts of daily closing spot market prices for copper and the S&P 500 are used. These 5, 10, and 15-year charts attempt to identify the short, medium, and long-term trends to help get a better understanding of the relationship between the two markets. The plan is to perform a full trend analysis to see if prices converge or diverge: does one lead another, do they move together or against each other? Ultimately this study is trying to get to a conclusion as to whether the copper spot market begins to react before the stock market. Identifying trends such as these will help to solidify the relationship between copper prices and price fluctuations in the stock market.
The goal was to obtain up to 15 years’ worth of daily closing prices for copper and the S&P 500 index with the plan of graphing them against one another. A long time period was chosen to analyse in order to be able to address any long and short-term trends between the two variables. The first attempt fell short, utilising a website called StockCharts.com. The two variables were able to be graphed, but the optics that were produced were not what was expected. When searching for another source to obtain our graphs Infomine.com was discovered. Both StockCharts and InfoMine have the historical data dating back more than 15 years. By inputting the essential criteria into the InfoMine website it was able to produce a graph with copper prices on one Y-axis and the S&P 500 on a secondary Y-Axis. The result is that copper prices were laid nicely over the S&P 500 for a better trend analysis.
Findings and analysis
As discussed above, three charts were obtained from Infomine.com that display the daily closing prices of copper versus the S&P 500 index for 5, 10, and 15-year time ranges. Utilising Technical Analysis skills, which are commonplace among chartists across the world, certain trends were identified that support the contention that the copper spot market does in fact lead the S&P 500.
In the 5 year chart (see Fig.1) we can see how copper prices are running almost in line with the S&P 500. However, from the end of 2011 we can see copper prices begin to converge with the S&P 500. From January 2010 to July 2012 there is a noticeable head and shoulders effect occurring in the copper spot market. This is a key indicator that copper prices are beginning to reverse their recent up-trend pattern. The decrease in price is said to go as low as the difference between the bottom of the shoulders and the top of the head. We could soon be seeing copper prices reaching an all time low of $1.50/lb. In the beginning of 2013 copper prices cross paths with the S&P 500 which has a steady up trend. In this time frame the Federal Reserve Bank announced that it would begin to ease off its quantitative easing in 2013. This caused the greenback to begin to appreciate against various currencies, making copper become more expensive to emerging economies. Copper prices began to drop to new lows, while the S&P 500, which is heavily weighted on the US stock market, was reaching new highs. The S&P 500’s new highs were attributed to the overall health of the US economy.
Fig.1, although displaying a short time frame, is showing us the strengths of technical analysis. As of late 2015 the S&P 500 has broken its upward trend. US-based multinational companies have some exposure to global growth outlooks, as they do not solely receive their revenues from within US borders. Copper, a global commodity, is showing its strength as a key indicator. The strong dollar is making copper more expensive while emerging economies’ demand for the metal is diminishing as supply continues to grow. Based on the technical analysis the S&P 500 might be seeing a correction very soon. It is also worth mentioning that there is also a four-year downward trend in copper spot prices with resistance at $2.75 per pound. If and/or when the copper spot price breaks through that downward trend line we could be seeing a rally in copper prices over a period of time.
The 10-year chart (see Fig.2) offers more data to help analyse key trends. Here we can see that the copper market moves somewhat in tandem with the S&P 500 from 2005 through 2012. With an extra five years of historical data we can begin to see other indicators from the copper market which predicted a market downturn. We can see the noticeable double top pattern with resistance at $4 per pound. A double top indicates a top to the market. Between late 2006 and the beginning of 2008, copper prices began to see resistance at around $4 per pound. Shortly after the stock market collapsed to usher in the 2008 financial crisis. Roughly three years after the market downturn in 2008, the copper market rebounded to $4.50 per pound, penetrating the original resistance level of $4 per pound. The head and shoulders pattern with the head top at $4.50 per pound has proved too much resistance to overcome. $4.50 per pound recently has been the top of the market for the past five years. In search for a fundamental reason as to why copper broke through the original resistance level of $4 per pound I stumbled upon an article from BBC News. The article contended that copper’s all-time high was tied to a strong global economic recovery and the fact that most countries held low stockpiles as demand outpaced supply (“Copper Enters 2011 at Record High”). Less than a year after reaching its all-time high, copper prices began to tumble. CNNMoney said that the tumble in copper prices was due to sluggish global growth, the worsening European debt crisis, the Federal Reserve’s dismal outlook, and indications of slowing manufacturing activity in both China and the Eurozone (CNNMoney, “The sky is falling!”). Commodities need inflation to rise in order to support prices, but when you have a global economic slowdown it creates deflation.
In the 15-year chart (see Fig.3) we gain another five years of historical data. This chart is the most interesting of the three charts due to the larger time frame in which the data is displayed. The first thing that becomes apparent is that in mid-2000 through early 2004 there is a down channel for the S&P 500, which (once the trend was broken) resulted in leading copper prices. Between April 2004 and towards the end of 2004 there is an ascending triangle present in the copper markets, which is a notably strong bullish indicator. The result was that copper prices skyrocketed from $1.5 to $3.5/lb over the next two years, and in the same time frame the S&P 500 jumped roughly 400 points from 1,200 to 1,600.
Another item worth noting to further support the idea that the copper spot market leads the stock market is the pattern of rising wedges apparent for copper and the S&P 500. The rising wedge for copper is leading the rising wedge for the S&P 500. A rising wedge is a strong bearish indicator, where two trend lines are converging in an upward direction. Copper ended up hitting the lower trend line, indicating a reversal in its upward trend. Shortly after, from 2011 onward, copper prices have been on a downward trend – further supporting the analysis conducted for the 5-year chart. Using the full 15-year scope, it is apparent that the S&P 500 has a rising wedge as well. If the S&P 500 breaks the lower trend line then we will see the S&P follow the same pattern we saw in 2011 with copper prices. This offers support to the analysis conducted on the 10-year chart. The S&P 500 is due to go through the last stage of its normal cycle; therefore, a correction is likely. This would further strengthen the contention that the copper spot market leads the stock market. Conversely, if the S&P 500 breaks the upper trend line then we will see the continuation of the current pattern. Due to recent developments in terms of global economic growth, over the next few years it would seem that a continuation of the S&P 500’s upward trend would be unlikely for the short to medium term.
This study concludes that copper prices do, in many cases, lead the stock market. Unlike other similar studies where researchers utilised various forms of statistical analysis to come to their conclusions, this study utilised technical analysis to arrive at conclusions. It was the ideal method for identifying the research question of whether the copper market has historically led the stock market. Utilising well-known chart patterns, the study identified that copper spot prices either led or, at the very least, gave strong indications of a reversal in a current pattern for the S&P 500. There was one case where the S&P 500 led the copper prices based on a down channel pattern from 2000 through 2003. Shortly after this occurrence a rising triangle was identified in the copper spot market, which is a bullish indicator. The stock market gained roughly 400 points over the next two years, a 33% increase.
From the analysis conducted we can also see that the S&P 500 is about due for the next stage in its normal cycle, which is a market correction. Copper prices have been on a downward trend since 2011, highlighting diminishing global demand for the industrial commodity and global growth outlooks. In the same time frame the S&P 500 has had a steady up trend, which it has recently broken. Additionally, a significant rising wedge, which is a bearish indicator, was identified. If the S&P breaks through the bottom trend line of the wedge we could see a decline in the S&P 500 for a period of time. This theory gains its support from the historical findings over the past 15 years. If we do see the S&P make a correction in the very near future it will further strengthen this study. The goal here was to provide support that copper prices can be used as a key indicator of stock market volatility. This study has provided sufficient evidence to support this relationship. Companies should take notice of these findings and utilise them to hedge against future fluctuations in the stock market.
There is sufficient evidence to support the contention that the copper market leads the S&P 500, but there are still some bases left uncovered. A continuation of this study should be considered to further strengthen its results. This would involve charting historical copper spot prices against the strength of the US dollar, the Dow Jones Industrial Average, other major stock indices, and also the trading volumes between copper and the other variables being analysed. Furthermore, obtaining more than 15 years’ worth of historical data is strongly recommended. A larger data set will help to identify more trends to expand the validity and reliability of the study.
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• “Copper enters 2011 at record high”, BBC News. (n.d.). Retrieved January 31, 2016, from http://www.bbc.com/news/business-12098576
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