Relative Strength Index on the Copper Futures Markets Research Paper

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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

DateCopperPlatinumSilverS&P 500
01-Jan-000.8441401
01-Feb-000.7871372
01-Mar-000.81515.25
01-Apr-000.791460
01-May-000.8111422.25
01-Jun-000.8161468
01-Jul-000.8711439
01-Aug-000.8851521.25
01-Sep-000.9151453.75
01-Oct-000.8471440.25
01-Nov-000.8411321.5
01-Dec-000.8471335
01-Jan-010.8491373
01-Feb-010.811242
01-Mar-010.7581169.25
01-Apr-010.7661254.25
01-May-010.7521257.5
01-Jun-010.7051231.75
01-Jul-010.6781215.25
01-Aug-010.6781135
01-Sep-010.6461043.75
01-Oct-010.6221060.75
01-Nov-010.7221140
01-Dec-010.6531149.2
01-Jan-020.7311130.4
01-Feb-020.7141107
01-Mar-020.761149.25
01-Apr-020.7331077.25
01-May-020.7611067.5
01-Jun-020.767990
01-Jul-020.677911.5
01-Aug-020.687916
01-Sep-020.66815
01-Oct-020.714885.5
01-Nov-020.736936
01-Dec-020.697879
01-Jan-030.791854.75
01-Feb-030.775841
01-Mar-030.7134.461847
01-Apr-030.7254.638916
01-May-030.784.526963.25
01-Jun-030.7484.52973.25
01-Jul-030.8185.116989.25
01-Aug-030.8035.1091007.75
01-Sep-030.8135.137994
01-Oct-030.9375.0591049.5
01-Nov-030.9075.3551057.75
01-Dec-031.0435.9531110.5
01-Jan-041.1436.2461130
01-Feb-041.3436.6961144.5
01-Mar-041.3597.9361125
01-Apr-041.215.8671106
01-May-041.2786.1051120.25
01-Jun-041.2055.7761140.5
01-Jul-041.3086.551101
01-Aug-041.2816.7711104
01-Sep-041.46.9161115
01-Oct-041.3477.2921130.25
01-Nov-041.4437.7231174
01-Dec-041.4876.8071213.75
01-Jan-051.4636.7371181.75
01-Feb-051.57.3591204
01-Mar-051.517.171184
01-Apr-051.4936.9031158.5
01-May-051.5057.4441192.25
01-Jun-051.5547.0281195.5
01-Jul-051.6887.2381236.75
01-Aug-051.716.7811221.5
01-Sep-051.8027.4581234.25
01-Oct-051.8967.551209.75
01-Nov-052.0758.281251
01-Dec-052.1628.821254.75
01-Jan-062.2369.851283.5
01-Feb-062.1869.721282.5
01-Mar-062.48811.481303.25
01-Apr-063.33613.511316
01-May-063.71612.3981272
01-Jun-063.46210.8331279.5
01-Jul-063.6111.3251281.75
01-Aug-063.46912.91305.5
01-Sep-063.45911.451345.4
01-Oct-063.33612.2121383.25
01-Nov-063.17113.9251403
01-Dec-062.85412.8181428.5
01-Jan-072.58313.5141443
01-Feb-072.73314.11409
01-Mar-073.14313.391431.25
01-Apr-073.54213.4451488.5
01-May-073.39313.4091533
01-Jun-073.45412.3531515.5
01-Jul-073.65412.951462
01-Aug-073.41112.0631476.75
01-Sep-073.63113.7941538
01-Oct-073.46814.3771554.9
01-Nov-073.15713.9631483.75
01-Dec-073.0314.7971477.25
01-Jan-083.28916.9481379.5
01-Feb-083.85219.8081331.25
01-Mar-083.86417.2751324
01-Apr-083.93416.5021386
01-May-083.62816.8271400.5
01-Jun-083.89617.421281
01-Jul-083.71617.751267
01-Aug-083.42913.6071282.5
01-Sep-082.88812.2311169
01-Oct-081.8449.73967.25
01-Nov-081.62310.185895.25
01-Dec-081.39511.27900
01-Jan-091.46212.56822.5
01-Feb-091.52613.085734.25
01-Mar-091.83912.975794.75
01-Apr-092.05312.305870
01-May-092.19715.6918
01-Jun-092.25813.574915.5
01-Jul-092.61613.933984.5
01-Aug-092.80814.8981019.75
01-Sep-092.80916.6361053
01-Oct-092.94716.2461033
01-Nov-093.1481460.1518.4951094.75
01-Dec-093.3281475.116.8221110.75
01-Jan-103.046150216.1831070.5
01-Feb-103.2681544.9516.51103.5
01-Mar-103.5461649.8517.5121165.25
01-Apr-103.3371743.318.6111183.5
01-May-103.0971564.818.4111088.5
01-Jun-102.9361535.618.6711026.5
01-Jul-103.3071575.5517.9871098.25
01-Aug-103.3611524.9519.3981048.25
01-Sep-103.6461660.6521.7981136.75
01-Oct-103.7321713.9524.561179.75
01-Nov-103.8231659.728.1851179.5
01-Dec-104.4391774.830.911253
01-Jan-114.4511796.1528.1741282.5
01-Feb-114.4781811.8533.8041326
01-Mar-114.31775.4537.8721321
01-Apr-114.1651875.0548.5841359.75
01-May-114.1731827.2538.3031344
01-Jun-114.2721723.5534.8121315.5
01-Jul-114.4741785.1540.0921288.5
01-Aug-114.1871849.7541.6991217.75
01-Sep-113.1451527.630.0411126
01-Oct-113.6291600.9534.3371249.25
01-Nov-113.5631564.432.7311246
01-Dec-113.4321403.2527.8751252.5
01-Jan-123.7881593.7533.2331308.25
01-Feb-123.871678.3534.5831364.5
01-Mar-123.8241643.1532.4691403.25
01-Apr-123.8331573.830.9591393.5
01-May-123.3621406.7527.7411309.25
01-Jun-123.491449.3527.581356.5
01-Jul-123.421410.527.8951374.5
01-Aug-123.4541540.1531.371405
01-Sep-123.7731656.4534.5171434.25
01-Oct-123.5271570.332.2881406.75
01-Nov-123.631603.833.2041414.5
01-Dec-123.641154330.1731420
01-Jan-133.7241677.131.3351493.25
01-Feb-133.5271585.2528.3951513.25
01-Mar-133.3951575.3528.2921562.75
01-Apr-133.1881506.624.1441592.25
01-May-133.2891456.7522.2281629
01-Jun-133.05134719.4511599.25
01-Jul-133.1191442.9519.6171680.5
01-Aug-133.2251523.4523.4631631.25
01-Sep-133.3211405.0521.6561674.25
01-Oct-133.295145221.8321751
01-Nov-133.2311362.819.9811804
01-Dec-133.442137119.3391841
01-Jan-143.221377.919.1051776.5
01-Feb-143.2391445.921.2041857.5
01-Mar-143.0461417.4519.7341864.5
01-Apr-143.031426.9519.1191878
01-May-143.1361453.5518.6531921.5
01-Jun-143.1881486.921.0071952.5
01-Jul-143.2231464.920.3731924.75
01-Aug-143.1351424.619.3982001.5
01-Sep-143.0061293.317.0061965.5
01-Oct-143.0611237.0516.0772011.5
01-Nov-142.861189.8515.4892066.25
01-Dec-142.8381209.1515.5652052.5
01-Jan-152.5281240.917.1921988.5
01-Feb-152.7161188.716.5132102.75
01-Mar-152.7471139.5516.5812060.75
01-Apr-152.8861142.3516.1242079
01-May-152.761111.5516.6842106
01-Jun-152.6231079.3515.5512054.5
01-Jul-152.368984.1514.7922098.5
01-Aug-152.3381007.3514.5861969.25
01-Sep-152.345907.7514.5661908.75

(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.

Graph 1
Graph 1

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.

Graph 2
Graph 2

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.

DateCloseChangeGainLossAverage GainAverage LossRSRSI
01-Jan-000.844
01-Feb-000.787-0.05700.057
01-Mar-000.80.0130.0130
01-Apr-000.79-0.0100.01
01-May-000.8110.0210.0210
01-Jun-000.8160.0050.0050
01-Jul-000.8710.0550.0550
01-Aug-000.8850.0140.0140
01-Sep-000.9150.030.030
01-Oct-000.847-0.06800.068
01-Nov-000.841-0.00600.006
01-Dec-000.8470.0060.0060
01-Jan-010.8490.0020.0020
01-Feb-010.81-0.03900.039
01-Mar-010.758-0.05200.0520.01040.01660.629338.624
01-Apr-010.7660.0080.00800.01030.01540.666439.992
01-May-010.752-0.01400.0140.00950.01530.622938.38
01-Jun-010.705-0.04700.0470.00880.01760.503733.499
01-Jul-010.678-0.02700.0270.00820.01820.450431.055
01-Aug-010.6780000.00760.01690.450431.055
01-Sep-010.646-0.03200.0320.00710.0180.393328.225
01-Oct-010.622-0.02400.0240.00660.01840.356726.29
01-Nov-010.7220.10.100.01320.01710.77443.631
01-Dec-010.653-0.06900.0690.01230.02080.590837.139
01-Jan-020.7310.0780.07800.0170.01930.87946.779
01-Feb-020.714-0.01700.0170.01580.01920.823345.154
01-Mar-020.760.0460.04600.01790.01781.007950.197
01-Apr-020.733-0.02700.0270.01670.01850.902647.44
01-May-020.7610.0280.02800.01750.01711.019350.477
01-Jun-020.7670.0060.00600.01660.01591.046251.129
01-Jul-020.677-0.0900.090.01550.02120.72942.164
01-Aug-020.6870.010.0100.01510.01970.765343.353
01-Sep-020.66-0.02700.0270.0140.02020.692340.909
01-Oct-020.7140.0540.05400.01690.01880.897847.307
01-Nov-020.7360.0220.02200.01720.01740.98849.697
01-Dec-020.697-0.03900.0390.0160.0190.842945.737
01-Jan-030.7910.0940.09400.02160.01761.224155.037
01-Feb-030.775-0.01600.0160.020.01751.144153.361
01-Mar-030.713-0.06200.0620.01860.02070.899147.343
01-Apr-030.7250.0120.01200.01810.01920.943748.552
01-May-030.780.0550.05500.02080.01781.164153.791
01-Jun-030.748-0.03200.0320.01930.01881.022950.565
01-Jul-030.8180.070.0700.02290.01751.308656.684
01-Aug-030.803-0.01500.0150.02130.01731.227755.11
01-Sep-030.8130.010.0100.02050.01611.272155.988
01-Oct-030.9370.1240.12400.02790.01491.865365.099
01-Nov-030.907-0.0300.030.02590.0161.615661.768
01-Dec-031.0430.1360.13600.03370.01492.269169.411
01-Jan-041.1430.10.100.03850.01382.786673.591
01-Feb-041.3430.20.200.050.01283.901279.597
01-Mar-041.3590.0160.01600.04760.01193.997279.989
01-Apr-041.21-0.14900.1490.04420.02172.036267.065
01-May-041.2780.0680.06800.04590.02012.277469.488
01-Jun-041.205-0.07300.0730.04260.02391.780964.041
01-Jul-041.3080.1030.10300.04690.02222.112267.868
01-Aug-041.281-0.02700.0270.04360.02261.931565.888
01-Sep-041.40.1190.11900.0490.02092.337470.037
01-Oct-041.347-0.05300.0530.04550.02321.956566.177
01-Nov-041.4430.0960.09600.04910.02162.274469.46
01-Dec-041.4870.0440.04400.04870.022.431370.856
01-Jan-051.463-0.02400.0240.04520.02032.226169.003
01-Feb-051.50.0370.03700.04460.01892.366270.293
01-Mar-051.510.010.0100.04220.01752.40770.649
01-Apr-051.493-0.01700.0170.03920.01752.239869.134
01-May-051.5050.0120.01200.03720.01622.292669.629
01-Jun-051.5540.0490.04900.03810.01512.524871.63
01-Jul-051.6880.1340.13400.04490.0143.208776.24
01-Aug-051.710.0220.02200.04330.0133.329676.903
01-Sep-051.8020.0920.09200.04680.01213.874279.484
01-Oct-051.8960.0940.09400.05010.01124.473481.73
01-Nov-052.0750.1790.17900.05930.01045.702285.079
01-Dec-052.1620.0870.08700.06130.00976.345486.386
01-Jan-062.2360.0740.07400.06220.0096.934587.397
01-Feb-062.186-0.0500.050.05780.01194.853782.917
01-Mar-062.4880.3020.30200.07520.01116.805587.189
01-Apr-063.3360.8480.84800.13040.010312.70892.705
01-May-063.7160.380.3800.14820.009515.55693.96
01-Jun-063.462-0.25400.2540.13770.0275.099883.606
01-Jul-063.610.1480.14800.13840.02515.521684.666
01-Aug-063.469-0.14100.1410.12850.03333.853979.398
01-Sep-063.459-0.0100.010.11930.03173.76779.022
01-Oct-063.336-0.12300.1230.11080.03822.900674.363
01-Nov-063.171-0.16500.1650.10290.04732.177268.526
01-Dec-062.854-0.31700.3170.09550.06651.436258.952
01-Jan-072.583-0.27100.2710.08870.08111.093552.233
01-Feb-072.7330.150.1500.09310.07531.235755.272
01-Mar-073.1430.410.4100.11570.071.654462.326
01-Apr-073.5420.3990.39900.1360.0652.093167.67
01-May-073.393-0.14900.1490.12630.0711.779264.018
01-Jun-073.4540.0610.06100.12160.06591.845364.854
01-Jul-073.6540.20.200.12720.06122.078867.52
01-Aug-073.411-0.24300.2430.11810.07421.592361.425
01-Sep-073.6310.220.2200.12540.06891.820564.545
01-Oct-073.468-0.16300.1630.11640.07561.540160.632
01-Nov-073.157-0.31100.3110.10810.09241.169953.915
01-Dec-073.03-0.12700.1270.10040.09491.05851.41
01-Jan-083.2890.2590.25900.11170.08811.26855.909
01-Feb-083.8520.5630.56300.1440.08181.759663.762
01-Mar-083.8640.0120.01200.13450.0761.770963.91
01-Apr-083.9340.070.0700.12990.07051.841764.81
01-May-083.628-0.30600.3060.12060.08741.380958
01-Jun-083.8960.2680.26800.13120.08111.616961.787
01-Jul-083.716-0.1800.180.12180.08821.381258.004
01-Aug-083.429-0.28700.2870.11310.10241.104652.486
01-Sep-082.888-0.54100.5410.1050.13370.785443.99
01-Oct-081.844-1.04401.0440.09750.19870.490732.917
01-Nov-081.623-0.22100.2210.09060.20030.45231.131
01-Dec-081.395-0.22800.2280.08410.20230.415629.36
01-Jan-091.4620.0670.06700.08290.18790.441130.609
01-Feb-091.5260.0640.06400.08150.17440.467331.848
01-Mar-091.8390.3130.31300.09810.1620.605337.708
01-Apr-092.0530.2140.21400.10630.15040.70741.417
01-May-092.1970.1440.14400.1090.13970.780643.84
01-Jun-092.2580.0610.06100.10560.12970.814244.88
01-Jul-092.6160.3580.35800.12360.12041.026650.656
01-Aug-092.8080.1920.19200.12850.11181.149253.471
01-Sep-092.8090.0010.00100.11940.10381.149953.486
01-Oct-092.9470.1380.13800.12070.09641.252155.598
01-Nov-093.1480.2010.20100.12650.08951.412558.549
01-Dec-093.3280.180.1800.13030.08311.567261.046
01-Jan-103.046-0.28200.2820.1210.09731.242955.414
01-Feb-103.2680.2220.22200.12820.09041.418358.649
01-Mar-103.5460.2780.27800.13890.08391.654962.334
01-Apr-103.337-0.20900.2090.1290.09291.388858.139
01-May-103.097-0.2400.240.11980.10341.158553.672
01-Jun-102.936-0.16100.1610.11120.10751.034650.85
01-Jul-103.3070.3710.37100.12980.09981.300156.523
01-Aug-103.3610.0540.05400.12440.09271.341757.296
01-Sep-103.6460.2850.28500.13580.08611.578261.214
01-Oct-103.7320.0860.08600.13230.07991.655162.337
01-Nov-103.8230.0910.09100.12930.07421.742763.54
01-Dec-104.4390.6160.61600.16410.06892.381270.425
01-Jan-114.4510.0120.01200.15320.0642.394670.542
01-Feb-114.4780.0270.02700.14420.05942.427170.821
01-Mar-114.3-0.17800.1780.13390.06791.972566.359
01-Apr-114.165-0.13500.1350.12430.07271.710863.111
01-May-114.1730.0080.00800.1160.06751.719363.226
01-Jun-114.2720.0990.09900.11480.06271.832164.691
01-Jul-114.4740.2020.20200.1210.05822.080167.533
01-Aug-114.187-0.28700.2870.11240.07451.50860.127
01-Sep-113.145-1.04201.0420.10440.14360.726642.082
01-Oct-113.6290.4840.48400.13150.13340.985849.642
01-Nov-113.563-0.06600.0660.12210.12860.949648.709
01-Dec-113.432-0.13100.1310.11340.12870.880646.826
01-Jan-123.7880.3560.35600.13070.11951.093352.229
01-Feb-123.870.0820.08200.12720.1111.146153.404
01-Mar-123.824-0.04600.0460.11810.10641.110752.622
01-Apr-123.8330.0090.00900.11030.09881.117252.768
01-May-123.362-0.47100.4710.10250.12540.817444.975
01-Jun-123.490.1280.12800.10430.11640.895947.255
01-Jul-123.42-0.0700.070.09680.11310.856346.129
01-Aug-123.4540.0340.03400.09230.1050.879446.792
01-Sep-123.7730.3190.31900.10850.09751.113152.676
01-Oct-123.527-0.24600.2460.10080.10810.932248.245
01-Nov-123.630.1030.10300.10090.10041.005550.137
01-Dec-123.6410.0110.01100.09450.09321.013950.345
01-Jan-133.7240.0830.08300.09370.08661.082451.978
01-Feb-133.527-0.19700.1970.0870.09450.921147.948
01-Mar-133.395-0.13200.1320.08080.09710.831745.407
01-Apr-133.188-0.20700.2070.0750.1050.714641.677
01-May-133.2890.1010.10100.07690.09750.788644.09
01-Jun-133.05-0.23900.2390.07140.10760.663539.884
01-Jul-133.1190.0690.06900.07120.09990.712841.616
01-Aug-133.2250.1060.10600.07370.09280.794444.271
01-Sep-133.3210.0960.09600.07530.08610.87446.639
01-Oct-133.295-0.02600.0260.06990.08180.854246.068
01-Nov-133.231-0.06400.0640.06490.08060.805744.62
01-Dec-133.4420.2110.21100.07540.07481.007250.178
01-Jan-143.22-0.22200.2220.070.08530.8245.055
01-Feb-143.2390.0190.01900.06630.07920.837145.567
01-Mar-143.046-0.19300.1930.06160.08740.70541.35
01-Apr-143.03-0.01600.0160.05720.08230.695241.011
01-May-143.1360.1060.10600.06070.07640.794444.27
01-Jun-143.1880.0520.05200.06010.07090.846745.85
01-Jul-143.2230.0350.03500.05830.06590.884746.94
01-Aug-143.135-0.08800.0880.05410.06740.802244.513
01-Sep-143.006-0.12900.1290.05020.07180.699341.153
01-Oct-143.0610.0550.05500.05060.06670.758243.124
01-Nov-142.86-0.20100.2010.0470.07630.615638.102
01-Dec-142.838-0.02200.0220.04360.07240.602237.586
01-Jan-152.528-0.3100.310.04050.08940.45331.179
01-Feb-152.7160.1880.18800.0510.0830.614838.073
01-Mar-152.7470.0310.03100.04960.07710.643539.156
01-Apr-152.8860.1390.13900.0560.07160.782343.891
01-May-152.76-0.12600.1260.0520.07550.68940.792
01-Jun-152.623-0.13700.1370.04830.07990.604537.677
01-Jul-152.368-0.25500.2550.04480.09240.485332.675
01-Aug-152.338-0.0300.030.04160.08790.473532.134
01-Sep-152.3450.0070.00700.03920.08160.479632.415

The graph presented below shows the trend of copper futures prices, RS and RSI.

Graph 3
Graph 3
Graph 4 – overbought and oversold
Graph 4 – overbought and oversold

Daily prices

The table presented below shows a summary of last fifteen values of RSI using the daily prices of copper futures.

DateClosePrice ChangeVolatilityChangeGainLossAverage GainAverage LossRSRSI
14-Aug-152.364-0.00040.22452-0.00100.0010.00960.01290.744242.667
16-Aug-152.344-0.85%0.22243-0.0200.020.00890.01340.665139.943
17-Aug-152.333-0.47%0.22216-0.01100.0110.00830.01330.625738.488
18-Aug-152.297-1.56%0.23013-0.03600.0360.00770.01490.517634.108
19-Aug-152.283-0.61%0.23078-0.01400.0140.00720.01480.482732.557
20-Aug-152.3231.74%0.242370.040.0400.00950.01380.690340.837
21-Aug-152.307-0.69%0.24305-0.01600.0160.00880.01390.633638.786
23-Aug-152.285-0.96%0.24552-0.02200.0220.00820.01450.56536.101
24-Aug-152.269-0.70%0.24645-0.01600.0160.00760.01460.520834.244
25-Aug-152.3232.35%0.26690.0540.05400.01090.01360.805144.601
26-Aug-152.251-3.15%0.23936-0.07200.0720.01010.01770.571736.374
27-Aug-152.3343.62%0.271210.0830.08300.01530.01650.931648.229
28-Aug-152.3460.51%0.269480.0120.01200.01510.01530.987649.688
30-Aug-152.336-0.43%0.26974-0.0100.010.0140.01490.940348.462
31-Aug-152.3380.09%26.98%0.0020.00200.01320.01390.950648.735
01-Sep-152.303-1.51%27.49%-0.03500.0350.01220.01540.795944.319
Graph 5
Graph 5
Graph 6
Graph 6
Graph 7
Graph 7

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). 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). 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). 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.

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