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| Author: | van Gerwe, Thom |
| Title: | Root cause analysis of price behaviour of copper and copper market volatility |
| Publication type: | Master's thesis |
| Publication year: | 2016 |
| Pages: | 190+22 Language: eng |
| Department/School: | Insinööritieteiden korkeakoulu |
| Main subject: | European Mining Course (R3008) |
| Supervisor: | Rinne, Mikael |
| Instructor: | Buxton, Mike |
| Electronic version URL: | http://urn.fi/URN:NBN:fi:aalto-201612085836 |
| Location: | P1 Ark Aalto 6485 | Archive |
| Keywords: | copper market behaviour analysis volatility |
| Abstract (eng): | A decade of extremely high and volatile copper prices has disturbed industries and raised the need for an extensive understanding of current predictors by means of indicators, signals, events and developments concerning the copper market. The goal of this research is to find a suitable method to prioritise events (including developments) on their impact on the copper market and to identify the root causes for these impacts. In order to asses future scenarios, this study can be used to identify predictors, which will improve the understanding of the dynamics of the copper market. In this research a large set of open data sources was analysed. This data was retrieved from USGS, World Bank, company reports, commodity reports and scientific researches. Furthermore, 29 case studies were analysed on various topics. These case studies consist of time series analyses, logical reasonings and assessments on future potential impacts. By interviewing external experts, different perspectives on the copper market were identified. Events were prioritized on the impact each caused on the copper market. To quantify this impact, a new indicator was developed. This indicator was derived from a surprise component, which was defined from literature. The surprise component indicates the effect of economic news on the commodity markets. The surprise component includes the market uncertainty at a specific moment in time and the deviation of the actual price from the expected price. The general idea of the developed indicator is to include the duration of an event. This is realized by a summation of the consecutive surprise components within this duration. Because the deviations are generally larger for long term events, a linear bias occurs. This bias was eliminated making the newly developed indicator also suitable for expressing the impact of long term events. This indicator enabled the first step in the root cause analysis and identified the events which caused the most impact, such as major wars, economic booms and technological developments. However, other types of events have caused more severe price shocks (a deviation from the expected price which is more than the standard deviation). The cyclical nature of the market, financial crises and a rapidly transforming climate for investment in a supply region are considered to be events causing the most severe price shocks. To identify the root causes for the events' and developments' impacts, associated indicators and signals were determined. By means of the case studies, those indicators and signals could be objectively valued. From the identified root causes, awarenesses of additional complexity are revealed. For example, it is assumed that economic growth in China will affect the copper market significantly. However, due to China's current status in several economic indicators, the significance of this impact is questioned. Economic growth in underdeveloped regions, such as India or Sub-Saharan Africa, will affect the copper market more significantly. Another key example is the recycling industry, which is much less matured as common statements make one believe, since the recycling efficiency continues to stay below 35\%. The case studies verified the indicators and signals and have provided information on the likelihood, future progress and impact of events affecting the copper industry. In order to assess the current relevance and significance of the studied indicators and signals, each was brought into today's perspective. It is presumed that certain indicators and signals might have changed in significance. First; the oil price, this study proves that pre-2000 events on the oil market only caused minor impacts on the copper markets. However, causal relations were deduced between the recent oil peak and the high marginal costs of copper. This suggests a possible increase in relevance of the oil market affecting the copper market. Secondly, the newly developed incentive for a transition to a sustainable society with an efficient use of energy. This will require appliances with a high content of copper. Massive embracing of these new appliances could boost the demand for copper. Lastly, the impact of an increase in demand due to wars. While the copper market is growing rapidly, magnitude of war would need to increase to affect the market with the same impact. The assessments for today's significances show that new drivers will enter the market and old drivers could reduce. This study revealed that the copper market was subject to both random and non random events. Pattern recognition does not seem a suitable tool to provide an understanding the behaviour of the copper price, but comprehending the root causes and the consequences of the events is of use. This study defined a set of indicators and signals (e.g. U.S. dollar currency index, discount rate and gold price) which stakeholders can use to optimize risk analyses. Monitoring and stimulating the development of alternative sources for copper, including recycling and deep sea mining, will enable the possibility to bypass risks. Lastly, indicators and signals, related to the sustainable energy transition, economy, company strategies and new innovations in processing and extraction technologies, will indicate how the balance in supply and demand will develop. This study improves the understanding of current dynamics of the copper market and the identified set of predictors will benefit stakeholders to improve their strategies. Updating this study will ensure industries are prepared for future market fluctuations. |
| ED: | 2016-12-18 |
INSSI record number: 55139
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