Do you need this or any other assignment done for you from scratch?
We have qualified writers to help you.
We assure you a quality paper that is 100% free from plagiarism and AI.
You can choose either format of your choice ( Apa, Mla, Havard, Chicago, or any other)
NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.
NB: All your data is kept safe from the public.
Introduction
Copper futures market
The market for copper future has been growing over the years just like the other commodities across the world. This can be attributed to the high demand for copper that is created by rapid industrialization in emerging markets. Thus, countries that endeavor to develop fast have a high demand for copper. Examples of these countries are China and India. It is estimated that China accounts for about 40% of world’s copper demand. Thus, movements of the demand for copper in the Chinese market have a significant impact on the global demand for copper. If this trend continues, it is expected that the demand for copper will exceed supply, and the prices will go up by a large margin. Copper metal trades as a future contract. In these contracts, “buyers agree to take delivery, from a seller, of a specific quantity of copper at a predetermined price on a future delivery price” (Copper Futures Trading Basics, 2009). The copper futures contracts are mainly traded on two markets. These are New York Mercantile Exchange (NYMEX) and London Metal Exchange (LME). On the NYMEX, the copper futures prices are quoted in dollars and cents per pound and are in units of 25000 pounds. On the LME, the prices of the contract are also quoted in dollars and cents per pound while units are 25,000 pounds (Copper Futures Trading Basics, 2009). The two major factors that influence the price of copper are the forces of demand and supply and Copper Development Association (Rutledge, Karim & Wang, 2013). The use of future contract in the market for copper has been quite significant in maintaining stable prices of copper. A study carried out by Souha Boutouria and Fathi Abid in 2012, indicated that hedging and the future contracts are effective in reducing the market risk of copper traded on the LME (Boutourian & Abid, 2012). Also, a study carried out by Sunita Arora and Narender Kumar in 2013 on the role of futures market in price discovery revealed that the futures market is effective in discounting new information (Arora & Kumar, 2013). This level of discounting is achieved because the copper market is well developed.
Relative strength index (RSI)
The index is a technical indicator that is used to study financial markets. The index makes use of the closing prices of stock or market to give information on the speed, velocity, strength and weaknesses of the markets being analyzed. It focuses on the rate of increase and decrease of prices. The tool also gives information on the general trend of a stock or market. Also, the index is used to generate signals. These signals are vital in determining whethere there is a need for a reaction or reversal. RSI is calculated on a 14-day time frame and it is measured on a scale that ranges between 0 and 100. In the paper, relative strength index will be used to analyze the copper futures market (Badge & Srivastava, 2010).
Data
The data for historical prices of Copper will be collected between 1st January 2000 and 1st September 2015. Further, both daily and monthly data for copper will be collected. A comparison will be made between the trend of copper, S&P 500 index, Silver and Platinum. The table presented below shows a summary of monthly data for the three commodities and the S&P 500 index.
Monthly prices for metals and S&P 500
(Source of data – Fusion Media Limited., 2015a; Fusion Media Limited., 2015b; Fusion Media Limited., 2015c; Fusion Media Limited., 2015d)
A review of the monthly prices shows that copper has a lower price than the other commodities. Platinum had the highest price followed by Silver. Graph 1 presented below shows that all the prices fluctuated during the period. There was no clear continuous trend that was exhibited during the period. The prices of the three metals and the market index had a similar trend between the years 2000 until 2012. The prices dropped between January 2000 and December 2002. Thereafter, there was an increase in the monthly prices until October 2008. The drop in price in 2008 can partly be attributed to the global financial crisis. There was a slight increase in prices of copper, platinum, silver, and S&P 500 unit mid 2012. After 2012, the monthly prices of the metals and S&P 500 index moved in the opposite direction. S&P 500 index continued to rise while the prices of the three metals dropped. The downward trend in the metal prices can be attributed to the contraction of the metal market. The trend of the monthly prices is displayed in graph 1 below.
Daily prices
The daily prices for copper, platinum, silver, and S&P 500 index is presented in the excel file. Graph 2 below shows that the trend of the daily prices of the four items is similar to that of the monthly prices. Thus, it can be noted that movement of metal prices is caused by factors that are industry specific.
Methodology
Introduction
The relative strength index was developed by J. Welles Wilder in 1978 (Gitman, Joehnk & Smart, 2011). The index is an impetus oscillator that estimates the magnitude and direction of price movements (Stockcharts.com, Inc., 2015). As mentioned above, the relative strength index (RSI) technique will be used to analyze the movement of prices in the copper futures markets. The index will be constructed using both daily and monthly data of prices for copper futures.
Formula
The basic components of RSI are relative strength (RS), average gain, and average loss. These components are used in the calculation of RSI. The formula for calculating RSI is presented below.
RSI = 100 – 100
1 + RS
RS = Average gain / average loss
The first values of average gain and average loss are estimated using a simple average for 14 days/months. The formula is presented below.
Average gain (first value) = Sum of gains over the past 14 days / 14
Average loss (first value) = Sum of losses over the past 14 days / 14
The subsequent values are estimated using a different formula. The calculations of subsequent values are based on the values of current gain and loss and previous averages. The formula for calculating subsequent values is presented below.
Average gain = [(previous average gain) * 13 + current gain] / 14
Average loss = [(previous average loss) * 13 + current loss] / 14
These formulas will be used to generate values of RS and RSI using the data of prices. It is worth mentioning that the use of large data samples provides more accurate forecasts than small data samples because smoothing of RS values affects the values of relative strength index. This makes the value of RSI to differ depending on the sample size of the data points. Therefore, it is advisable to use a sample containing at least 250 data points. The smoothing process normalizes the values of RS in such a way that they oscillate between 0 and 100. This makes it easy to detect the extreme points (Elliot, 2014).
Constraints
The use of 14 days is the default value that was used in the original model. However, the value can be increased or decreased depending on the desired level of sensitivity. The choice of the number of periods depends on the volatility of the security or market that is being analyzed. In the calculations of RSI for copper futures market, 14 days/months period will be used.
Overbought and oversold
Based on the original model, RSI is overbought when it exceeds 70 and oversold when it falls below 30. Thus, the tops and the bottoms will be revealed when RSI exceeds these two values. However, these traditional limits can be altered to suit the security that is being analyzed. For instance, if the values are 80 for overbought and lowered to 20 for oversold, the number of oversold and overbought readings will reduce (Wang, 2011). When analyzing the market for copper, the traditional values will not be changed. The center line of 50 is also vital when analyzing RSI values. It acts as support and resistance mark for the RSI. Thus, if RSI lies below 50, it shows that the losses of the stock exceed the gains. Also, if RSI lies above 50, it indicates that the gains exceed the losses (Jawade, Naidu, & Agrawal, 2015).
When analyzing RSI, the prices can move up swiftly and it may be considered overbought. Also, when the prices move down swiftly, it may be considered oversold. Therefore, it is important to have a reaction or a reversal. The level of RSI gives information on the strength of the recent trading of a stock or a market. The distance travelled and slope of RSI gives information on the size and rate of change of the RSI (Prabhakaran & Nagarajan, 2012). Divergences between prices and RSI chart signal a point of reversal because the directional momentum does not confirm the price (Rajvanshi, 2014). RSI can experience both bearish and bullish divergence depending on the direction of movement of the index. Generally, increases cause bullish divergences while decreases in RSI cause bearish divergences. Therefore, divergences is a vital signal that RSI reveals. Another important use of RSI is an evaluation of trend. Generally, uptrends are traded between RSI values of 40 and 80 while downtrends are traded between 60 and 20 (Perchanok & Hrytsyuk, 2011).
Analysis
Assumptions
When estimating the values of RSI, a 14 period interval is used to calculate the average gain and average loss. Also, the overbought and oversold limits are 70 and 30 respectively.
Monthly RS and RSI
The data presented below show the estimated values of monthly RSI for copper futures market.
The graph presented below shows the trend of copper futures prices, RS and RSI.
Daily prices
The table presented below shows a summary of last fifteen values of RSI using the daily prices of copper futures.
Discussion
The oversold and overbought points are clearly shown in the excel file. In the graphs above, it can be noted that there were several overbought and oversold points. Further, it can be observed that the prices of the metal were high when the commodity was overbought and low when the securities were oversold. Also, most of the RSI points lie above the center line. It shows that the gains exceeds the losses. The RSI chart also shows that there was a general upward trend, especially before the global financial crisis in 2008. After the global financial crisis, there was a downward trend observed in the RSI values. It can also be noted that there are higher highs and lower highs points in both the monthly and daily charts. The lower highs are indications of bearish divergence while the higher highs are indications of bullish divergence, as indicated in the excel file. Also, it can be observed that there are instances when the prices rise and decline at rates that are higher than the RSI. These are scenarios when the RSI cannot explain the movements in prices. The divergences that is observed in the charts calls for both positive and negative reversals. Graph 6 above shows the trend of RS, RSI, and the price of copper futures using the last 15 values of the daily copper prices. The graph shows that RSI is an accurate indicator of copper futures prices.
Conclusion
The paper used the RSI technique to forecast the prices of copper futures. The paper starts by analyzing the copper futures market. This section focuses on how copper is traded and the most common markets on which the commodity is traded on. Further, it also gives a summary of various studies that have been carried out on the copper futures market. A comparison of prices shows that copper has a lower price than both platinum and silver. Also, the charts show that the price of the three metals moved in the same direction during the period of analysis. This indicates that the external factors have a significant influence the prices of the metals. The RSI is calculated using an interval of 14 periods, both for the monthly and daily data. The oversold and overbought limits used in the analysis are 30 and 70 respectively. The RSI charts exhibit both upward and downward trend. Also, both bearish and bullish divergences were evident from the RSI charts. The analysis shows that RSI tool can be used to forecast the values of future copper prices accurately.
References
Arora, S. & Kumar, N. (2013). Role of futures markets in price discovery. Decision (0304 – 0941), 40(3), 165 – 179. Web.
Badge, J., & Srivastava, N. (2010). Asset value estimation through technical indicators and fuzzy time series model. International Journal of Computational & Applied Mathematics, 5(4), p.437. Web.
Boutourian, S. & Abid, F. (2012). Pricing and hedging copper futures on the London metal exchange. IUP Journal of Applied Finance, 18(1), 68-98. Web.
Copper Futures Trading Basics. (2009). Web.
Elliot, A. R. (2014). Stock strength: It’s all relative, and is reflected in the RS line. Web.
Fusion Media Limited. (2015a). Copper futures – Mar 16 (HGH6): Copper historical data. Web.
Fusion Media Limited. (2015b). Platinum futures – Jan 16 (PLF6): Platinum historical data. Web.
Fusion Media Limited. (2015c). S&P 500 futures – Mar 16: S&P 500 futures historical data. Web.
Fusion Media Limited. (2015d). Silver futures – Mar 16 (SIH6): Silver historical data. Web.
Gitman, L. J., Joehnk, M. D., & Smart, S. B. (2011). Fundamentals of investing (11th ed.). Boston, MA: Pearson. Web.
Jawade, A. A., Naidu, K., & Agrawal, A. (2015). Performance of oscillators: Index futures. SCMS Journal of Indian Management, 12(1), p.51-59. Web.
Perchanok, K., & Hrytsyuk, I. (2011). The encyclopedia of the indicator RSI (relative strength index).USA: CreateSpace Independent Publishing Platform. Web.
Prabhakaran, K., & Nagarajan, S. (2012). An effectiveness of technical indicators – a study on CNX IT indices. Journal of Management & Science, 2(2), p.11. Web.
Rajvanshi, V. (2014). Intraday trading activity and volatility: Evidence from energy and metal futures. IUP Journal of Applied Finance, 20(1), 57-74. Web.
Rutledge, R., W., Karim, K., & Wang, R. (2013). International copper futures market price linkage and information transmission empirical evidence from the primary world copper markets. Journal of International Business Research, 12(1), 113 – 131. Web.
Stockcharts.com, Inc. (2015). Relative strength index (RSI). Web.
Wang, J. (2011). Impact of investment horizon on the performance of value versus growth styles and style allocation. Journal of Asset Management, 12(6), 438–446. Web.
Do you need this or any other assignment done for you from scratch?
We have qualified writers to help you.
We assure you a quality paper that is 100% free from plagiarism and AI.
You can choose either format of your choice ( Apa, Mla, Havard, Chicago, or any other)
NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.
NB: All your data is kept safe from the public.