THE INDONESIAN JOURNAL OF BUSINESS ADMINISTRATION Vol. 2, No. 13, 2013:1651-1664 COMPARISON OF NATURAL HEDGES FROM DIVERSIFICATION AND DERIVATE INSTRUMENTS AGAINST COMMODITY PRICE RISK : A CASE STUDY OF PT ANEKA TAMBANG TBK Dikdik Dwiparandi and Isrochmani Murtaqi School of Business and Management Institut Teknologi Bandung, Indonesia dikdik.d@sbm-itb.ac.id Abstract Antam is a mining company which most revenues come from the sales of diversified commodities, namely ferronickel (36.5% of total revenues in 2011), nickel ore (24.1%), gold (36.0%), silver (2.7%), and coal (0.8%). With the trend of declining nickel price in 2012, more than half of the company s revenue is exposed to the nickel commodity price downside risk. Despite that, Antam claimed that its diversified commodities can reduce such impact, in other words it creates natural hedges, a hedging method that comes from daily activities. The topic of this final project is concerning the commodity price risk of nickel against Antam s natural hedge and other hedging tools. This research aims to find the strength of natural hedge compared with the use of derivatives to mitigate the risk of declining nickel price. Due to the limitation of data, only forward and option contract are used as derivative instruments. Risk in natural hedge is conducted by calculating the VaR of portfolio using Delta-Normal method, which then is compared to the company s retained earnings in 2011. Forward and Option contracts are applied to ferronickel and nickel ore, which make four combinations of derivatives strategy. Comparison of natural hedge and derivatives is done by comparing VaR of natural hedge with the cost of hedging of derivatives strategy in three time horizon. Based on calculation, although Antam s natural hedges is strong, the company should hedge its nickel-based commodities in short period by entering ferronickel into put option contract and nickel ore into short forward contract. Antam may also improve its diversification by adjusting its sales volume per commodity or use both derivative instruments to each commodity. Keywords: Commodity Price Risk, Value at Risk, Natural Hedge, Forward Contract, Option Contract. 1. Introduction Antam is a mining company with vertically integrated operations, which processes several diversified minerals and also operates other businesses related with the mining sector. The company has a number of commodities offered, i.e. ferronickel, high- and low-grade nickel ore, gold, silver, bauxite, and coal, and wide operational areas in Indonesia (Appendix A). In 2011, nickel price tended to decline, although Antam has mitigated it by increasing production and sales volume to cover the loss from price decrease. Moreover, gold and silver had a reverse trend. Antam, with its diversified products and revenue sources, has a natural hedge, a hedging method coming from daily activities, against the risk of nickel price decreasing. However, the trend of nickel price movement was still decreasing since the beginning of 2011 and it is predicted that the price would keep declining in 2012. Antam, with nickel commodities as its largest contributors of its revenue, still has a possibility that its revenue can still be affected negatively when this commodity prices falls. On the other hand, even if the company uses hedging tools to protect its revenue budget, several hedging positions can eliminate the opportunity to gain higher revenue if the price of hedging increases. 1651
Framework of research focuses on risk measurement, using Value-at-Risk (VaR), and risk mitigation, by comparing VaR of portfolio and cost of hedging of derivatives. This research aims to find the strength of natural hedge compared with the use of derivatives to mitigate the risk of declining nickel price. Due to the limitation of data, only forward and option contract are used as derivative instruments and applied to ferronickel and nickel ore, which make four combinations of derivatives strategy. The time horizon for calculation of VaR and derivatives are 3, 6, and 12 months. Measurement of risk in natural hedge is conducted by calculating the VaR of portfolio using Delta-Normal approach. VaR at 99% confidence level then is compared to the company s retained earnings in 2011. Comparison of natural hedge and derivatives is done by comparing VaR of natural hedge with the cost of hedging of derivatives strategy in three time horizon. 2. Business Issue Exploration A. Conceptual Framework Conceptual framework is based on Olsson s Risk Loop, which consists of four key elements: Risk Identification, Risk Measurement, Risk Management, and Risk Monitoring (Olsson, 2002: 17). Risk identification aims to find the issue and its root causes by looking at exposures, risk factors, risk profiles, and descriptive statistics to describe potential downside risk. Risk measurement estimates of potential loss from current condition and from other hedging tools, using VaR and hedging cost as measures. Risk management compares the results from the measurement and decides what to do. Then, risk monitoring evaluates the strategic decision and describe implementation plan. B. Method of Data Collection and Analysis Risk Identification consists of risk exposures, risk factors, risk profiles and descriptive statistics. This section requires production and sales volume as well as net sales for each commodity in financial report, and historical commodity price as follows: ferronickel, nickel ore, gold, silver, and coal. These data then are utilized to compute Value-at-Risk per commodity and portfolio. Delta-Normal method is used for its simplicity and characteristics of distribution. Calculating the derivatives also needs interest rate and, for option, strike price. These result in forward price and option put price, from which the unrealized Gain / Loss and hedging cost are calculated. Next, VaR of portfolio is compared with the company s retained earnings to see the strength of its diversified portfolio. VaR is also compared with hedging costs to see whether derivatives strategy is better than the portfolio. C. Analysis of Business Situation In this study, risk identification is used to analyze business situation. It starts with overview of commodity price risk consisting of risk exposures, risk factors, risk profile and descriptive statistics. These sections aim to analyze factors affecting potential loss. 1) Risk Exposure Antam is exposed to commodity price fluctuation. Antam s main commodities are nickel (ferronickel and nickel ore), gold, silver, and coal. The volumes of production and sales of each commodity determine the exposure, which can be considered from the proportion of each commodity s sales revenue to the total revenues. The following table summarizes Antam s exposure to its commodities. Table 1. Antam s Sales Volumes and Net Sales per Commodity Commodity Units Sales Volume 1652 Sales Revenue (thousand IDR) Percentage ton Ni 19,527 3,727,767,205 36.48% Ferronickel Nickel Ore wmt 6,345,742 2,465,258,069 24.13% Gold kg 8,009 3,675,048,768 35.97% Silver kg 26,890 271,155,716 2.65% Coal ton 363,596 78,195,480 0.77% Total 10,217,425,238
Source: Annual Report 2011 2) Risk Factors Risk Factors are the fluctuating market price of each commodity within the same period. The commodities are ferronickel, nickel ore, gold, silver, and coal (Appendices A and B). Ferronickel price is bullish until November 2006, then bearish to October 2008. Then it goes up again slightly until November 2010, where it goes down from. For nickel ore, its price is correlated highly with ferronickel price. Coal has a similar movement, where the price increases to April 2004, goes steady to January 2007, and it goes bullish to May 2008. Then it goes bearish until January 2009, bullish to November 2010, and then tends to go down from then. Historical gold price data has a relatively stable movement. It just goes bullish until December 2011. The silver price data, although has some similarity with gold, is more volatile. It goes bullish until January 2008, drops and goes steady to April 2010, and sudden increase to January 2011, and goes bearish from then. 3) Risk Profiles The risk profile describes profit/loss in simple perspective, where the horizontal axis indicates the price changes of the commodity and vertical axis the benefit / loss for Antam. Risk profile shown in Figure 1 is common for all commodity price risk in Antam. When a price of one commodity increases, Antam as a seller receive profit. On the other hand, when the price decreases, Antam suffers loss. Figure 1. Risk Profile of Commodity Risk Source: Analysis, 2013 4) Descriptive Statistics Descriptive statistics is one of summary statistics that provides the main features of a given data set, which in this analysis is used to describe historical price data. In this analysis the measures that are used are: mean as average return; variance and standard deviation as volatility; skewness to find whole distribution values and kurtosis to find the peakedness or the tailedness. The results are shown in the next table. Table 2. Summary of Descriptive Statistics Moments FeNi Ni Ore Gold Silver Coal Mean 0.84% 0.38% 1.36% 1.52% 1.08% Std Dev 9.23% 11.47% 4.20% 7.51% 7.90% Variance 0.85% 1.32% 0.18% 0.56% 0.62% Skewness -0.35-0.04-0.01-0.41 0.15 Kurtosis 0.57 0.25 1.49 0.79 2.95 Based on tables above, it can be derived that all means are positive, implying that all commodities tend to bullish. The standard deviation and variance are the highest for nickel-based commodities, and lowest for gold. This means that nickel has the most volatile price movement among all Antam s commodities. Negative skewness indicates left-tail distribution, meaning that most likely it has large 1653
negative values. Silver has the highest negative skewness, while gold has the least. Coal on the other hand has positive skewness, indicating right-tail distribution. For kurtosis value, all commodities have lower than 3.0 (platykurtic shape), indicating a lower probability of extreme movement (Jorion, 2009:35). According to Jorion, Value-at-Risk is the worst loss over target horizon such that there is a low; prespecified probability that the actual loss will be larger (Jorion, 2007: 106). In this research, VaR predict the potential loss of each commodity in 95% and 99% confidence levels with time period of 3- month, 6-month, and 12-month. Bohdalova mentioned that there are three general techniques on calculating VaR (Bohdalova, 2007: 2). Based on comparison conducted by Fiksriyoso, this research uses Delta-Normal Method as it is one of the simplest and uses descriptive statistics results to compute (Fiksriyoso, 2012). The results are shown in the following table. Table 3. Value-at Risk for each commodities? Period FeNi Ni Ore Gold Silver Coal 3- month 7.41% 9.21% 3.37% 6.02% 6.34% 95% 6- month 10.47% 13.02% 4.77% 8.52% 8.97% 12- month 15.18% 18.87% 6.91% 12.34% 13.00% 3- month 10.47% 13.02% 4.77% 8.52% 8.97% 99% 6- month 14.81% 18.41% 6.74% 12.05% 12.68% 12- month 21.47% 26.68% 9.77% 17.46% 18.38% Based on the table, the nickel-based commodities have the highest VaR values, showing that their volatility may result in the highest loss compared to other Antam s commodities. The lowest one is gold which has half value of ferronickel s VaR. 5) Root of Problem Concluding the analysis of business situation, the root of problem is visible from several points: Antam is exposed to the change in three main commodities, namely ferronickel, gold, and nickel ore. The nickel-based commodities have a volatile price movement, which was predicted to decline. As a seller, Antam would suffer when the prices of its commodities decrease. Based on the results of descriptive statistics, nickel, ferronickel and nickel ore, has the lowest average returns while the volatility is the highest among Antam s commodities. The Value-at-Risks also conclude that nickel has the highest potential loss. 3. Business Solution D. Alternatives of Business Solution Theoretically, there are many business solutions that can be applied in Antam s situation. Due to the limitation of data availability and Indonesian condition of hedging awareness, three of the basic hedging techniques are chosen: Natural hedge, Forward contract, and Option contract. Furthermore, due to the uniqueness of Antam s commodities, two additional enhanced methods are analyzed, which are optimization of commodity portfolio and combination of forward and option proportion. E. Analysis of Business Solution 1) Natural Hedging 1654
Natural hedging can be viewed as hedging that comes from daily activities or operations, or in Dowd s words, position that reduces overall risks (Dowd, 2002: 153). Antam s natural hedging method is by diversifying the business segments. Antam s natural hedging can be calculated in the same way as calculating the portfolio of a stock. In this case, Markowitz s mean-variance method is used to find the average returns and standard deviation of the portfolio, and then to calculate the Value-at-Risk using Delta Normal method. The formulas are as follow.?????????????????? (1)?????????????????? #Ij??????? (2)?6???6?? (3) where n: the number of commodities, i = 1, 2, n, w: weight proportion, and z = 1.645 for 95% confidence level or 2.326 for 99% confidence level (Bodie, et al., 2008). The results are as presented in the following table. Table 4. Results of Antam s Portfolio of Commodities in million IDR % IDR 3- month 6- month 12- month Ave Return 0.93% 95,517 46,608 65,913 95,517 Std Deviation 0.36% 36,454 17,788 25,156 36,454 VaR 95% 0.59% 59,962 29,259 41,378 59,962 VaR 99% 0.83% 84,805 41,381 58,522 84,805 As shown in the table above, with a portfolio the standard deviation decreases to 0.36%, and its Value-at-Risks for 1-year period is reduced to 0.59% (Rp.60 billion) at a 95% confidence level and 0.83% (Rp.85 billion) at a 99% confidence level. If this value is compared with Antam s retained earnings in 2011 (Rp.9.7 trillion), it is small enough that it only affects less than 1% of the retained earnings. As such, Antam s portfolio of commodity sales can be considered as strong enough to withhold nickel s commodity risk. Next, in doing a sensitivity analysis for Antam s natural hedge, the relationship of the price changes between nickel and other commodities is needed. As the regression analysis between nickel price and other commodities is not significant (Appendix C), it is assumed that the correlation coefficient shows the relationship between commodities, such as: Nickel Ore Ferronickel Gold Ferronickel Silver Ferronickel Coal Ferronickel??????@???????@???????@???????@? Using the relationships above, the total profit/loss of the portfolio dependent on nickel price changes is shown in table 5. From the table it can be seen that 1% change of ferronickel price affect the total return as much as 0.428% for 3-month, 0.507% for 6-month, and 0.505% for 12-month period. This is because the production volume of Antam s commodities for each period has different percentages. But from the changes of total return more than 40% from nickel price change, it is obvious that Antam s return is affected by nickel. Table 5. The Effect of Ferronickel Price Change on Portfolio Return Nickel Portfolio Return Price 3-6- 12- Change month month month 100% 42.76% 50.66% 50.52%???? 1655
10% 4.28% 5.07% 5.05% 0% 0.00% 0.00% 0.00% -10% -4.28% -5.07% -5.05%???? -100% - - - 42.76% 50.66% 50.52% 2) Derivative Instruments There are four basic derivative instruments: forward, future, option, and swap. Based on Anindita s result of qualitative comparison, this research only uses forward and option (Anindita, 2012). a) Forward According to Hull, forward contract is an agreement to do transaction of a specific asset with specific amount of cash at an agreed date in the future. In analyzing nickel s forward price, as the historical data for forward price is not available, this research uses the following formula to generate forward price (Hull, 2012: 118):???????????? (4) Antam is a seller of nickel, so it assumes short position in forward contract. Hedging cost is assumed to be zero. From the forward price, Unrealized Gain/Loss is generated by subtracting the forward price with the spot price at the time of delivery. b) Option Option contract is similar to forward, but rather than obligation, it gives its holder the right to do transaction. In calculating the option price, Black-Scholes-Merton method is used (Hull, 2012: 313).??????????????6????? (5)??????6??????????????? (6) where????????? (8) The Strike Price ( K) used follows the regulation from London Metal Exchange for nickel option contract as assumption (CMEGroup, 2011): $25 for strikes from US$25 to US$9,975 $50 for strikes from US$10,000 to US$19,950 $100 for all strikes over $US20,000 Antam is the seller, so it is in the position of a put option contract. In calculating the Cost of Hedge, the spot price now ( S 0 ) is subtracted with Put Price ( p). For Unrealized Gain / Loss in historical simulation, the strike price ( K) is subtracted with the spot price at the time of delivery ( ). The comparison of forward and option is done with historical data and present one. In the historical simulation the gain / loss and the cost of hedging is compared. The results are shown in Appendices D and E. The figures above show that forward contracts have almost similar loss with profit for 3 month period, while the rest of the periods have more loss compared to profit. On the other hand, option contracts eliminate this loss. However, as forward is assumed costless, the cost of hedging of an option contract only is shown, and as seen in the figure, the longer the contract is the more volatile the movement.the means and the standard deviations from the historical simulations for forward and option contracts are shown in the next table. Table 6. Comparison of Forward and Option Contracts from Historical Simulation Return Hedging Cost Period Forward Option Forward Option Mean -1.72% 5.78% 0% 1.08% 3- St month Deviation 18.61% 9.22% 0% 0.21% 6- Mean -4.15% 7.32% 0% 1.03% 1656????6??? /???????? /?????? S y (7)
month 12- month St Deviation 29.49% 12.60% 0% 0.32% Mean -10.74% 9.71% 0% 0.81% St Deviation 50.73% 16.63% 0% 0.36% The results show that an option s average return is higher and its standard deviation for return is smaller than those of a forward. Also, the longer the time period, the bigger and more volatile forward s loss is, and the bigger yet more volatile option s return is. However, as forward doesn t have cost of hedging, an option s average cost of hedging and its standard deviation is higher. Therefore, it can be concluded that an option is more beneficial even though there is a cost of hedging. Next, the effect of nickel price changes on the portfolio with forward / option contracts on nickelbased commodities is analyzed. The results are shown in Appendices F and G; the profit from the price decrease differs as much as 1% for 3-month, 2% for 6-month period, and 3% for 12-month with the highest return coming from ferronickel forward nickel ore forward strategy and lowest return from ferronickel option nickel ore option. Also, different strategies give different loss when the price goes up; compared to the loss from ferronickel forward nickel ore forward strategy, the loss from ferronickel forward nickel ore option decreases 2 times for 3-month period and 1.4 times for 6- and 12-month ones, while one from ferronickel option ferronickel forward 2.7 times for 3-month and 5.5 times for 6- and 12-month ones, and the near constant loss from ferronickel option nickel ore option becomes profit with 1% price increase results in 0.035% profit increase. 3) Comparison Based-on the VaR and Cost of Hedging Antam s diversified portfolio of commodities is already good enough with its Value-at-Risk as a cushion strategy. The Value-at-Risk even with the confidence level of 99% can be held with Antam s retained earnings. However, this possibility of loss should be compared with the cost of hedging when Antam uses a forward or an option contract. 4) Optimizing the Natural Hedge Portfolio Table 7. Comparison of VaR and CoH (thousand IDR) 3 months 6 months 12 months Portfolio VaR 95% 29,258,638 41,377,962 59,962,364 Portfolio VaR 99% 41,381,050 58,521,642 84,805,915 FeNi Ni Ore CoH Fo Fo - - - Fo Op 6,653,104 13,927.690 33.380.455 Op Fo 5,595,090 26,198,711 59,389,088 Op Op 12,248,194 40,126,400 92,769,543 As can be seen in the table, for the 3-month period, the Value-at-Risks at 95% and 99% are actually higher than the cost of hedging for any strategy. For 6-month period, they are still higher, although the cost of ferronickel option nickel ore option strategy is close to VaR 95%. For 12-month period, ferronickel option nickel ore option strategy is higher than VaR 99%, and ferronickel option nickel ore forward strategy has almost similar value with Value-at-Risk. 1657
As Antam s business segments can be considered as a portfolio, another method of analysis is the Markowitz portfolio mean-variance optimization. With this method, depending on the purpose, the commodities contribute more to accomplish such purpose are emphasized. Two optimization objectives are used: to minimize the risk and to maximize the Sharpe ratio. Minimizing the risk holds true with the purpose of risk management, and is done by minimizing the portfolio s standard deviation. Maximizing the Sharpe ratio can maximize the portfolio return while keeping the risk as low as possible. The results are shown below. Table 8. Optimization of Antam s Portfolio of Commodities Present Condition Min Std Deviation Max Sharpe Ratio Ferronickel 36.48% 13.10% 10.61% Nickel Ore 24.13% 0.00% 0.00% Gold 35.97% 71.48% 75.33% Silver 2.65% 0.00% 0.00% Coal 0.77% 15.42% 14.06% Total 100.00% 100.00% 100.00% Return 0.93% 1.25% 1.26% St Deviation 0.36% 0.13% 0.13% Sharpe Ratio 2.62 9.29 9.36 VaR 95% 0.59% 0.22% 0.22% VaR 99% 0.83% 0.31% 0.31% As shown above, the VaRs for both strategies are pushed down from 0.59% to 0.22% (Rp.22 billion) for 95% confidence level and 0.83% to 0.31% (Rp.32 billion) for 99% confidence level. Both strategies emphasize the weight portion of gold, and then of coal and ferronickel, while nickel ore and silver are zero. This can be interpreted as in order to minimize the risk, Antam should prioritize the sales volume of its commodities in the following order: gold, coal, and ferronickel, while pushing down the volume of nickel ore and silver. Table 9. The Effect of Nickel Price Change on Optimized Portfolio Return Nickel Price Change Portfolio Return Min Std Deviation 1658 Max Sharpe Ratio 100% 20.83% 18.48%??? 10% 2.08% 1.85% 0% 0.00% 0.00% -10% -2.08% -1.85%??? -100% -20.83% -18.48% From sensitivity analysis above in the table, 1% changes of ferronickel price results in the changes of portfolio return of 0.21% for minimizing standard deviation strategy and 0.18% for maximizing Sharpe ratio strategy. This is much lower than the original portfolio where it means that the portfolio return is affected by the change of nickel price around 20%.
5) Combination of Forward and Option Another alternative is by combining the forward and option contracts in one commodity. Here how much of ferronickel is used in a forward contract and in an option contract are calculated, and then they are combined with the same condition for nickel ore. This method aims to gain the benefit of both contracts while reducing the risk or loss of only focusing on one contract. For simplification, the term Fo-Op means the comparison of weight for forward and option contracts, where 25-75 means 25% of the total volume of the commodity is put in forward contract while 75% is in option contract. The costs of hedging of these combinations are shown in Appendix H. For the period of 3-month and 6-month, the costs of hedging of any combination of proportion have lower value than the Value-at-Risk. For 12-month period, only the combination of ferronickel 0-100 and nickel ore 0-100 has higher value than VaR at 99%, and eight combinations have higher value than VaR at 95%. Because the presence of forward contract eliminates the cost of hedging from option, forward-option combination strategy can be chosen for such purpose. The more forward s proportion is, the more the cost of hedging is covered. Appendix I shows the forward-option combinations for nickel ore with the least forward proportion that eliminates hedging costs of the combinations for ferronickel, in three time periods. 4. Conclusion and Implementation Plan Antam s natural hedging is strong enough to withstand the risk of a drop in the price of nickel. With Value-at-Risk as cushion, the company s retained earnings are much larger than its portfolio VaR at a 99% confidence level. However, based on the calculation, the hedging costs for any derivative strategies in 3- and 6-month periods are lower than VaR at 95% confidence level. it is concluded that Antam should hedge with derivative in short period. With two nickel-based commodities which are ferronickel and nickel ore, Antam has four alternatives on derivatives. Considering the upside risk of forward and the cost of hedging of option, based on calculation, the best strategy is to put the ferronickel in an option put contract and the nickel ore in a short forward contract. It is also recommended that Antam adjusts its production and sales volumes to enhance its portfolio of commodities. Based on the portfolio optimization, Antam should focus on gold, coal, and ferronickel to minimize risk of nickel price decreasing. Moreover, on the derivative strategy, as it is possible to use both forward and option in one commodity, an example to use this benefit is that for a 3-month period with ferronickel in a 25% forward and a 75% option contract; and putting nickel ore in a 75% forward and a 25% option contract, thereby giving half the risk if nickel price increases and 0.5% difference of profit if the price of nickel decreases. In practice, forward contract doesn t need third party such as CMEgroup and LME, so Antam can negotiate and deal directly with the buyers. On the other hand, an option contract needs third party. However, considering that the buyers are many and international, third party would be helpful. The recommended one is CMEGroup and LME for ferronickel commodity (The Option & Futures Guide, n.d.). For nickel ore commodity, since most prefer payment in cash or letter of credit, to negotiate directly with the buyers in forward contract should be easier. Depending on the negotiation, the offered forward price and option strike price and put price may be higher or lower than calculated prices, so adjustment should be made. In general, higher forward price and strike price are more profitable for Antam, while higher put price means higher hedging cost. Finally, the company should continue monitoring this risk to mitigate the potential upside movement of nickel price. Production and sales volumes should also be maintain to keep Antam s diversified commodity portfolio strong. References Anindita, A. 2012. Selecting Hedging in Reducing Market Risk of Natural Gas Price Volatility in Energy Industry: Free Floating Price Simulation in a Case Study of Gas Project for PLN at PT. Energi Mega Persada. Bandung Institute of Technology. 1659
Annual Report 2011. (n.d.). Retrieved Jan 17, 2013, from PT. Aneka Tambang, Tbk.: http://www.antam.com/ Bodie, Z., Kane, A., & Marcus, A. 2008. Investments (7th ed). New York: McGraw-Hill. Bohdalova, M. 2007. A Comparison of Value-at-Risk Methods for Measurement of the Financial Risk. Science and Technology Assistance Agency. CME Group. 2011. Futures & Options Trading for Risk Management. Retrieved Feb 5, 2013, from http://cmegroup.com/ Dowd, K. 2005. Measuring Market Risk (2nd ed.). Chicester, GBR: John Wiley & Sons. Fiksriyoso, N. 2012. Application of Value at Risk for Managing Portfolio Currencies of Transaction Exposure: A Case Study of Trade Payables in PT. United Tractors, Tbk. Bandung Institute of Technology. Hull, J. C. 2012. Options, Futures, And Other Derivatives (8th ed.). London, GBR: Pearson Education Limited. Index Mundi. (n.d.). Commodity Prices. Retrieved Feb 24, 2013 from http://www.indexmundi.com/ Jorion, P. 2007. Value at Risk: The New Benchmark For Managing Financial Risk. SGP: McGraw-Hill. Jorion, P. 2009. Financial Risk Manager Handbook (5th ed.). New Jersey, USA: John Wiley & Sons. Olsson, C. 2002. Risk Management in emerging markets. London, GBR: Pearson Education Limited. Quarterly Report 2000-2011. (n.d.). Retrieved Feb 23, 2013, from PT. Aneka Tambang, Tbk.: http://www.antam.com/ The Options & Futures Guide. (n.d). Nickel Options Explained, Retrieved Feb 4, 2013 from: http://www.theoptionsguide.com/ 1660
Appendix A. Annual Net Sales per Commodity in IDR Net Sales 2006 2007 2008 2009 2010 2011 Ferronick el 2,724,767,1 65 5,793,314,4 57 3,517,701,6 31 2,146,923,3 84 3,679,373,1 25 3,727,767,2 05 Nickel ore 2,009,015,3 4,894,101,0 2,955,753,7 1,696,184,3 2,363,658,7 2,465,258,0 40 98 29 80 68 69 Gold 601,305,309 1,034,230,9 2,740,298,5 4,321,459,4 2,353,744,1 3,675,048,7 33 30 07 56 68 Silver 73,030,479 107,708,897 156,824,223 429,422,695 238,103,897 271,155,716 Bauxite 190,819,493 129,931,694 159,367,427 78,676,103 34,448,181 46,381,406 Coal - - - 2,187,900 23,779,692 78,195,480 Other precious 1,597,385 3,224,066 7,757,434 4,961,663 9,493,499 1,657,078 metal Iron sand 10,975,478 17,049,633 9,075,079 1,594,577 - - Refinery services 17,890,789 28,641,720 45,203,085 29,960,146 41,698,898 80,969,682 Source: Annual Report, 2011. Appendix B. Historical commodity price (ferronickel, nickel ore, gold, silver, and coal) Source: indexmundi.com, 2013. Source: Quarterly Report, 1999-2011. 1661
Appendix C. Results of Regression Analysis of Nickel and Other Commodities Commodities Adjusted R Square Significance F Intercept P-value X Variable Nickel Ore 0.308752 2.7E-11 0.814262 2.7E-11 Gold -0.00209 0.387728 0.047014 0.387728 Silver 0.044134 0.012105 0.280638 0.012105 Coal 0.009319 0.148095 0.39179 0.148095 Appendix D. Historical simulation of forward and option contracts gain/loss Appendix E. Historical simulation of forward and option contracts cost of hedging FeNi Price Changes Appendix F. The Effect of Ferronickel Price Change on Profit/Loss of Portfolio with Forward-Option Portfolio Return with Derivative (%) 3 months 6 months 12 months FeNi Fo Op Fo Op Fo Op Ni Ore Fo Op Fo Op Fo Op Fo Op Fo Op Fo Op 100% - - - - - - -33.4 17.3 12.4 3.7 41.0 30.1-7.6 3.3 39.8 29.2-7.4 3.2?????????? 10% -2.8-1.8-1.2-0.2-2.9-2.5-0.8-0.4-1.7-1.8-0.4-0.5 0% 0.6-0.1 0.2-0.6 1.3 0.5 0.1-0.7 2.5 1.2 0.6-0.7-10% 4.0 3.3 3.6 2.9 5.6 4.8 4.4 3.6 6.8 5.5 4.8 3.5?????????? -100% 34.7 34.0 34.2 33.5 43.6 42.8 42.4 41.6 44.9 43.6 42.9 41.6 Appendix G. The Payoff Profile from the Portfolio with Forward and Option 1662
Appendix H. The Cost of Hedge from Forward-Option Combination in IDR 3 month CoH (thousand IDR) FeNi Fo-Op portion 6 month CoH (thousand IDR) FeNi Fo-Op portion 12 month CoH (thousand IDR) FeNi Fo-Op portion Ni Ore Fo-Op portion 0-100 25-75 50-50 75-25 100-0 0-100 12,248,194 10,584,918 8,921,642 7,258,366 5,595,090 25-75 10,849,422 9,186,146 7,522,870 5,859,594 4,196,318 50-50 9,450,649 7,787,373 6,124,097 4,460,821 2,797,545 75-25 8,051,877 6,388,601 4,725,325 3,062,049 1,398,773 100-0 6,653,104 4,989,828 3,326,552 1,663,276 - Ni Ore Fo-Op portion 0-100 25-75 50-50 75-25 100-0 0-100 40,126,400 36,644,478 33,162,556 29,680,633 26,198,711 25-75 33,576,723 30,094,800 26,612,878 23,130,955 19,649,033 50-50 27,027,045 23,545,123 20,063,200 16,581,278 13,099,355 75-25 20,477,367 16,995,445 13,513,523 10,031,600 6,549,678 100-0 13,927,690 10,445,767 6,963,845 3,481,922 - Ni Ore Fo-Op portion 0-100 25-75 50-50 75-25 100-0 0-100 92,769,543 84,424,429 76,079,316 67,734,202 59,389,088 25-75 77,922,271 69,577,157 61,232,044 52,886,930 44,541,816 50-50 63,074,999 54,729,885 46,384,772 38,039,658 29,694,544 75-25 48,227,727 39,882,613 31,537,500 23,192,386 14,847,272 100-0 33,380,455 25,035,341 16,690,228 8,345,114 - Source: Analysis, 2013 Appendix I. The Effect of Nickel Price Change on Revenue of Portfolio with Forward-Option Combination 1663
Portfolio Return with Derivative (%) 3 months 6 months 12 months FeNi 0-25- 50-75- 100-0- 25-50- 75-0- 25- Price FeNi 100 75 50 25 0 100 75 50 25 100 75 Change Ni 75-75- 50-50- 25-100- 50-25- 0-75- 25- Ore 25 25 50 50 75 0 50 75 100 25 75 100% -8.4 - - - - - - - -7.6 13.7 14.9 20.1 21.3 10.5 16.1 21.7-4.8-7.6???????????? 10% -0.9-1.3-1.5-1.9-2.1-0.8-1.1-1.6-2.0-0.4-0.8 0% 0. 0.1 0.05 0.2 0.1 0.1 0.0 0.1 0.2 0.2 0.1-10% 3.4 3.5 3.4 3.6 3.5 4.4 4.4 4.4 4.5 4.5 4.3???????????? -100% 34.0 34.2 34.1 34.2 34.2 42.4 42.3 42.4 42.5 42.6 42.4 1664