- Published: September 26, 2022
- Updated: September 26, 2022
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MBA (Energy Trading)
Saumya Sharma
Assistant ProfessorCollege of Management & Economic StudiesUniversity of Petroleum & Energy StudiesDehradun – 248 006Guided by: Submitted by:
Siddharth saxena
SAP ID: 500014665Roll No.: R590211028
MBA (Energy Trading)
2011-2013
upes_logo1
College of Management and Economic Studies
University of Petroleum and Energy Studies,
Dehradun, Uttarakhand, India
MARCH, 2013
Certificate of Originality
This is to hereby state with the intention of this report is very original in every sense of the terms and conditions and it carries a sense of honour and belief and that no shortcuts have been taken and I remained both meticulous and caring during the prevalence of this research work. I have put in my point best to keep this work as informative and precise as possible. It may be also stated here that during the preparation of this report some help has been taken from a scope of professionally shared information & knowledge, a comprehensive description of which has been mention in the references chapter of this report. Dated: Signature:
Siddharth saxena
R-590211028MBA – Energy Trading (2011-13)University of Petroleum & Energy StudiesDehradun
Acknowledgement
I acknowledge with thanks the help, guidance and the support that I have received during research work. I express deep sense of gratitude to Assistant Prof. Saumya Sharma, for her enormous help and valuable guidance and suggestion during the research work. I must also thank Mr. Shailendra Pokhriyal, Head of Department, Energy Trading, COMES, UPES for his cooperation and suggestion which enabled me carry out this research work in a better manner. Siddharth saxena
MBA (Energy Trading),
University of Petroleum & Energy Studies,
Dehradun,
Uttarakhand
Table of Contents
STATEMENT OF THE PROPOSAL
PROBLEM STATEMENT
” ENERGY PORTFOLIO MANAGEMENT” – is the research work that aims of creating a dynamic portfolio management process with analyzing all the risks that are related with the energy portfolio and how they impact the valuation of the same. It is aimed to provide best immunity to the portfolio from the known risks.
BACKGROUND
The term ” portfolio management” has a long history in the finance and investment. Under that name and others, the same risk management concepts andtechniques have long been applied to procurement of commodities, including energy utility procurement of fuels and purchased power In recent years, the term has begun to be used in the energy industry to describe actual or suggested approaches to default service resource management and trading in business that have restructured energy industry. However, application of portfolio management concepts need not be confined to energy deficient markets. Energy portfolio management helps utilities like cost-efficiently procure energy by tracking changes in market behavior and consumption, changes in suppliers in deregulated markets, market price volatility, and supply risk. Study also addresses a high-value; cost-effective solution that can reduce risk and provide solid return on investment. Energy portfolio management is a comprehensive study for management of sales and procurement portfolios in the energy industry or energy-intensive companies. OBJECTIVESThe following are the key objectives of the topic: Price volatility which is tolerable for trader, taking into accountthe means at their disposal for managing that risk? How portfolio depends on the level and instability of prices? Timeframe for which the proposed strategy apply? What stability level of prices is expected to result during that time? How sensitive is the expected levelWhat flexibility is available and what point of timeframe
SCOPE OF RESEARCH
This dissertation would include various risks which can occur while managing a energy profile. The time duration for collection and analysis of data would be factor that should be most relevant and help provide much needed immunity to the portfolio. This work would be done for energy sector and specially designed model for current valuation of assert i. e. portfolio.
RESEARCH METHODOLOGY
RESEARCH DESIGNThe research is descriptive as well as imperial as it will be conducted on the basis earlier research that has been conducted in this area of risk. Insights form market professionals would be obtain to know the ” Ground Realities” of the risks involved and existing valuation models. SOURCE OF DATAThis research will be based on Secondary data collected from1. Journals2. Industry Professionals3. Past Data models
STATISTICAL/MATHEMATICAL TOOLS
Lattice modelBinomial option pricing modelLocal volatilityMonte Carlo method for option pricingValuation of optionFourier analysisTaylor analysisBernoulli processMarkov chainStochastic processGeometric Brownian motionStochastic volatility
PRICING THEORY
Dynamics-Free PricingPricing Under Bernoulli DynamicsBlack-Scholes DynamicsAmerican Options and ‘ Exotics’Models with Uncertain VolatilityDiscontinuous ProcessesInterest-Rate Dynamics
INTRODUCTION
In energy portfolios across the hedge funds it is generally observed to have much concentration on the crude oil or other petroleum products. To mitigate this exposes and divide across the energy spectrum we have taken crude oil , natural gas, coal and propane as commodities , this will help us understand the overall measures and implications across the energy sector. Energy portfolio is affected by number of attributes which goes around the whole spectrum that is petroleum products and other energy products . this explains the exposes and relative instability in the system . this intern affects the portfolio returns and its growth.
UNITS
Dollars per Barrel for crude oil. Dollars per Thousand Cubic Feet for natural gas. US Dollars per Metric Ton for coal. Dollars per Gallon for propane.
TIME FRAME
The time frame taken is a span of five years taking average of each month prices.
Europe Brent Spot Price FOB
(Dollars per Barrel)
YEARJANFEBMARAPRMAYJUNJULAUGSEPOCTNOVDEC200892. 1894. 99103. 64109. 07122. 8132. 32132. 72113. 2497. 2371. 5852. 4539. 95200943. 4443. 3246. 5450. 1857. 368. 6164. 4472. 5167. 6572. 7776. 6674. 46201076. 1773. 7578. 8384. 8275. 9574. 7675. 5877. 0477. 8482. 6785. 2891. 45201196. 52103. 72114. 64123. 26114. 99113. 83116. 97110. 22112. 83109. 55110. 77107. 872012110. 69119. 33125. 45119. 75110. 3495. 16102. 62113. 36112. 86111. 71109. 06109. 49
Price of U. S. Natural Gas LNG Imports (Dollars per Thousand Cubic Feet)
YearJanFebMarAprMayJunJulAugSepOctNovDec20088. 429. 379. 419. 8511. 3312. 3412. 9910. 259. 069. 168. 098. 8620097. 636. 826. 344. 23. 883. 894. 213. 943. 353. 954. 254. 6320100. 785. 744. 874. 254. 244. 24. 84. 934. 64. 785. 095. 4120115. 564. 995. 355. 424. 636. 665. 56. 994. 487. 414. 25. 5720124. 254. 32. 952. 964. 373. 15. 154. 023. 173. 187. 215. 22
COAL, SOUTH AFRICAN EXPORT PRICE
US Dollars per Metric Ton
YearJanFebMarAprMayJunJulAugSepOctNovDec2008
115111108. 75120. 7142. 38167. 75156. 9147. 75109. 789. 3877. 25200976. 469. 0658. 5662. 8858. 0360. 261. 164. 2561. 1364. 3566. 4473. 8201086. 9483. 3682. 9688. 790. 9492. 8190. 6187. 985. 8290. 99103. 2115. 242011122. 62117. 74121124. 03120. 46119. 01116. 27118. 27115. 62110. 88105. 47104. 192012106. 26105. 3103. 43101. 3393. 7785. 3187. 3389. 1185. 8282. 885. 7488. 84
Mont Belvieu, TX Propane Spot Price FOB (Dollars per Gallon)
YearJanFebMarAprMayJunJulAugSepOctNovDec20080. 5061. 4251. 4751. 591. 71. 8131. 8621. 6511. 531. 0450. 7380. 6120090. 7270. 6590. 6530. 6380. 7010. 8460. 7520. 9060. 9461. 0081. 0761. 1920101. 3121. 2841. 1361. 1371. 0821. 0371. 011. 0721. 1321. 2341. 2541. 29620111. 3481. 3791. 3971. 4541. 5211. 521. 5281. 5281. 561. 4721. 4581. 39520121. 2941. 221. 2611. 1960. 9540. 7880. 8740. 9010. 910. 9620. 890. 797
COEFFICIENT OF VARIATION (CV)
This measure is the ratio of the distribution’s standard deviation to its mean. It is one way to measure risk relative to return, or in such cases, variation in price relative to mean price, measured over a define period. Tolerance bands can be established around coefficient of variation (William Steinhurst, 2006)To calculate cofficient of variation we will require percentage change per month. corrosponding tabel is given in annexture A. CALCULATIONEurope Brent Spot Price FOB (Dollars per Barrel)
Coefficient of variation
STANDARD DEVIATION IN SPOT
24. 43969
STANDARD DEVIATION IN % CHANGE
0. 093408
MEAN(AVERAGE)
92. 153
MEAN(AVERAGE)
0. 01
COFFICIENT OF VARIATION
0. 265208
COFFFICIENT OF VARIATION
12. 39Price of U. S. Natural Gas LNG Imports (Dollars per Thousand Cubic Feet)
Coefficient of variation
STANDARD DEVIATION IN SPOT
2. 483838
STANDARD DEVIATION IN % CHANGE
0. 877858
MEAN(AVERAGE)
5. 775833
MEAN(AVERAGE)
0. 11
COFFICIENT OF VARIATION
0. 43004
COFFFICIENT OF VARIATION
7. 878703Coal, South African export price, US Dollars per Metric Ton
Coefficient of variation
STANDARD DEVIATION IN SPOT
24. 62738
STANDARD DEVIATION IN % CHANGE
0. 08187
MEAN(AVERAGE)
97. 16661
MEAN(AVERAGE)
-0. 0011
COFFICIENT OF VARIATION
0. 253455
COFFFICIENT OF VARIATION
-77. 1Mont Belvieu, TX Propane Spot Price FOB (Dollars per Gallon)
Coefficient of variation
STANDARD DEVIATION IN SPOT
0. 329396
STANDARD DEVIATION IN % CHANGE
0. 257909
MEAN(AVERAGE)
1. 160667
MEAN(AVERAGE)
0. 86
COFFICIENT OF VARIATION
0. 283799
COFFFICIENT OF VARIATION
0. 301347
INFERENCE
The coefficient of variation value of spot price of natural gas is 0. 4 which is more than the other energy forms across the same time spectrum which is around 0. 25, thus we can deduce that the risk related to return is substantially high then other energy forms(for given time period)
BETA
Beta is a measure of the systematic risk of a single instrument or an entire Portfolio and describes the sensitivity of an instrument or portfolio to broad market movements. A portfolio with a large beta will tend to benefit or suffer from broad market moves more strongly than the market overall, while one with a small beta will swing less violently than the broad market. (William Steinhurst, 2006)Here to get colse corrospondence of the market fluctuation the benchmark index taken is ” Commodity Fuel (energy) Index” which is defined asCommodity Fuel (energy) Index, 2005 = 100, includes Crude oil (petroleum), Natural Gas, and Coal Price Indices(imf)The calculation of beta is done by the regression which is given by the division of the covariance of the two arrey in the system by the variance of the benchmark index here it is taken as Commodity Fuel (energy) Index. All the four products percentage change in prices is taken against corresponding change in fuel price index.
CALCULATION
Europe Brent Spot Price FOB (Dollars per Barrel)
COVARIANCE
0. 007275
VARIANCE
0. 006409
BETA
1. 135094Price of U. S. Natural Gas LNG Imports (Dollars per Thousand Cubic Feet)
COVARIANCE
-0. 00475
VARIANCE
0. 006409
BETA
-0. 74036Coal, South African export price, US Dollars per Metric Ton
COVARIANCE
0. 003902
VARIANCE
0. 006409
BETA
0. 608893Mont Belvieu, TX Propane Spot Price FOB (Dollars per Gallon)
COVARIANCE
0. 006342
VARIANCE
0. 006409
BETA
0. 989531
INFERENCE
Beta corresponds to the systematic risk and correlation of each instrument with respect to the index. Here the value of Europe Brent Spot Price FOB that is 1. 2 which relates to the index. Contrarily the U. S. Natural Gas LNG Imports gives negative value deducing that on every move in the index there will be opposite move of slightly less intensity on the natural gas prices.
RELEABILITY TEST
To test the reliability of the beta value special R – SQUARE test is done which corresponds to the accuracy and efficient calculation mechanism.
R – SQUARE
R – SQUARE(Europe Brent Spot Price FOB)
96. 41%
R – SQUARE(U. S. Natural Gas LNG Imports)
0. 46%
R – SQUARE(Coal, South African export price)
36. 71%
R – SQUARE(Mont Belvieu, TX Propane Spot Price)
61. 77%This clearly shows Europe Brent Spot Price FOB mostly corresponds to the index in subject and the U. S. Natural Gas LNG does not correspond to the index at all.
EXTREME VALUE MEASURES
This measures the portfolio riskiness. In general, this type of measure is the difference in cost between a portfolio’s expected cost and some estimate of its worst-case cost. This measure portfolio riskiness by the difference between its expected cost and average of the worst 10% of its cost’s probability distribution. (NorthWestern Energy 2005 Electric Default Supply Resource Procurement Plan, 2005)In this study of portfolio management the extreme value measure corrosponds to mean valure , standerd deviation , skewness , kitrous, r square and engle 1. To calculate all the four commodities are evaluated for corrosponding given parameters. Here the for R square and Engel 1 calculation commodities are evaluated with corresponding Commodity Fuel (energy) Index. For the calculation of R square the correlation coefficient for given data is deduced. Further the product of this coefficient with the sample size gives the value of Engle 1.
CALCULATION
Europe Brent Spot Price FOB (Dollars per Barrel)
mean
92. 153
standard deviation
24. 43969
skewness
-0. 42049
kitrous
-0. 7916
r square
0. 976206
sample size
59
engle 1
57. 59614Price of U. S. Natural Gas LNG Imports (Dollar/ Thousand Cubic Feet)
mean
5. 775833
standard deviation
2. 483838
skewness
1. 048503
kitrous
0. 799302
r square
0. 081253
sample size
59
engle 1
4. 79391Coal, South African export price, US Dollars per Metric Ton
mean
97. 16661
standard deviation
24. 62738
skewness
0. 540404
kitrous
0. 33489
r square
0. 62669
sample size
59
engle 1
36. 9747Mont Belvieu, TX Propane Spot Price FOB (Dollars per Gallon)
mean
1. 160667
standard deviation
0. 329396
skewness
0. 01812
kitrous
-0. 82808
r square
0. 586967
sample size
59
engle 1
34. 63103
INFERENCE
Combined table
Brent
ng
coal
propane
mean
92. 1535. 7797. 1661. 16
standard deviation
24. 432. 4824. 60. 32
skewness
0. 421. 040. 540. 018
kitrous
-0. 790. 790. 33-0. 828
r square
0. 970. 0810. 620. 586
sample size
59595959
engle 1
57. 594. 7936. 9734. 63INTERPRETATION(taking all commodities of equal proportions)The average of all four mean is 49. 06, this corresponds to the minimum value of the portfolio that can be possible with all four commodities doing worse corresponding to the fuel index. The average of skewness is around 0. 5 which means that the mostly the return achieved by the portfolio is underperforming by fifty percent. Kitrous is significantly low and positive for natural gas and coal but just opposite for crude and propane. Thus indicating that the index is related to the portfolio. Engle 1 value of natural gas is significantly low indicating low hetroskedasicity. Same is significantly high for all other commodities.
VALUE AT RISK (VAR)
A traditional approach for quantifying risk of investment portfolios. VaR measures the downside risk of a portfolio. It is always calculated in the context of a risk level and a planning horizon. VaR of a proposed resource portfolio over a one year planning horizon at the 99% risk level. That VaR would tell us the amount of extra cost that would have a 1% chance of occurring over the next year. (William Steinhurst, 2006)In this study all the commodities are evaluated for VaR analysis
CALCULATION
Europe Brent Spot Price FOB (Dollars per Barrel)
PARAMETER SPOT
PARAMETER(% CHANGE)
PORTFOLIO VALUE
100PORTFOLIO VALUE100
AVERAGE RETURN SPOT
21. 07103AVERAGE RETURN % CHANGE0. 069167
STANDARD DEVIATION IN SPOT
24. 43969STANDARD DEVIATION IN SPOT0. 093408
CONFIDENCE LEVEL
0. 95CONFIDENCE LEVEL0. 95
CALCULATION
CALCULATION
MINIMUM RETURN WITH 95 % PROB
-19. 1287MINIMUM RETURN WITH 95 % PROB-0. 08448
VALUE OF PORTFOLIO
-1812. 87VALUE OF PORTFOLIO91. 5524
VALUE AT RISK
1912. 87VALUE AT RISK8. 447596Price of U. S. Natural Gas LNG Imports (Dollar/ Thousand Cubic Feet)
PARAMETER (SPOT)
PARAMETER(% CHANGE)
PORTFOLIO VALUE
100PORTFOLIO VALUE100
AVERAGE RETURN SPOT
1. 948306AVERAGE RETURN % CHANGE0. 328863
STANDARD DEVIATION IN SPOT
2. 483838STANDARD DEVIATION IN SPOT0. 877858
CONFIDENCE LEVEL
0. 95CONFIDENCE LEVEL0. 95
CALCULATION
CALCULATION
MINIMUM RETURN WITH 95 % PROB
-2. 13724MINIMUM RETURN WITH 95 % PROB-1. 11508
VALUE OF PORTFOLIO
-113. 724VALUE OF PORTFOLIO-11. 5084
VALUE AT RISK
213. 7245VALUE AT RISK111. 5084Coal, South African export price, US Dollars per Metric Ton
PARAMETER (SPOT)
PARAMETER(% CHANGE)
PORTFOLIO VALUE
100PORTFOLIO VALUE100
AVERAGE RETURN SPOT
19. 88988AVERAGE RETURN % CHANGE0. 06009
STANDARD DEVIATION IN SPOT
24. 62738STANDARD DEVIATION IN %CHANGE0. 08187
CONFIDENCE LEVEL
0. 95CONFIDENCE LEVEL0. 95
CALCULATION
CALCULATION
MINIMUM RETURN WITH 95 % PROB
-20. 6186MINIMUM RETURN WITH 95 % PROB-0. 0746
VALUE OF PORTFOLIO
-1961. 86VALUE OF PORTFOLIO92. 5426
VALUE AT RISK
2061. 856VALUE AT RISK7. 45736Mont Belvieu, TX Propane Spot Price FOB (Dollars per Gallon)
PARAMETER (SPOT)
PARAMETER(% CHANGE)
PORTFOLIO VALUE
100PORTFOLIO VALUE100
AVERAGE RETURN SPOT
0. 277567AVERAGE RETURN % CHANGE0. 104765
STANDARD DEVIATION IN SPOT
0. 329396STANDARD DEVIATION IN SPOT0. 257909
CONFIDENCE LEVEL
0. 95CONFIDENCE LEVEL0. 95
CALCULATION
CALCULATION
MINIMUM RETURN WITH 95 % PROB
-0. 26424MINIMUM RETURN WITH 95 % PROB-0. 31946
VALUE OF PORTFOLIO
73. 57591VALUE OF PORTFOLIO68. 05417
VALUE AT RISK
26. 42409VALUE AT RISK31. 94583
INFERENCE
The value at risk calculated for all four commodities in separate analysis at the spot price as well as on the percentage change of the spot prices. The confidence level taken is 95% as the time spectrum is of five years. The VaR value for the percentage change taken is more relevant if correlated with the fuel index thus in percentage change calculation natural gas is the most venerable commodity and others are also quite venerable if invested independently. VaR analysis shows the riskiness in investing in any one of these commodities independently and forming a portfolio will be a wise option.
REVENUE AT RISK (RAR)
Because of the cost uncertainty of that resource, they have Revenue at Risk (RaR). RaR is equal to the maximum amount of extra resource cost that the manufacturer can afford to pay without severe damage to its finances. (William Steinhurst, 2006)For our study RaR is a function of the direct impact of the market fluctuations. To measure this if the change in the percentage impact is either greater than ten percent or less than ten percent is noted and analysis is done on the only those values. Thus giving the actual risk related to the revenue and its implication.
CALCULATION
Europe Brent Spot Price FOB (Dollars per Barrel)
MONTH
Spot Price
% CHANGE
MAY, 08
122. 812. 59%
AUG, 08
113. 2414. 68%
SEP, 08
97. 23-14. 14%
OCT, 08
71. 58-26. 38%
NOV, 08
52. 45-26. 73%
DEC, 08
39. 95-23. 83%
MAY, 09
57. 343. 43%
JUN, 09
68. 6119. 74%
AUG, 09
72. 5112. 52%
MAY, 10
75. 9510. 46%
MAR, 11
114. 6410. 53%
JUN, 12
95. 1613. 76%
AUG, 12
113. 3610. 47%Calculation
PARAMETER SPOT
PORTFOLIO VALUE
100
AVERAGE RETURN SPOT
23. 25337
STANDARD DEVIATION IN SPOT
26. 92094
CONFIDENCE LEVEL
0. 95
CALCULATION
MINIMUM RETURN WITH 95 % PROB
-21. 0276
VALUE OF PORTFOLIO
-2002. 76
REVENUE AT RISK
2102. 764Price of U. S. Natural Gas LNG Imports (Dollar/ Thousand Cubic Feet)
MONTH
SPOT PRICE
% CHANGE
FEB, 08
9. 3711. 28%
MAY, 08
11. 3315. 03%
AUG, 08
10. 2521. 09%
SEP, 08
9. 06-11. 61%
NOV, 08
8. 0911. 68%
JAN, 09
7. 6313. 88%
FEB, 09
6. 82-10. 62%
APR, 09
4. 233. 75%
SEP, 09
3. 35-14. 97%
OCT, 09
3. 9517. 91%
JAN, 10
0. 78-80. 25%
FEB, 10
5. 74635. 90%
MAR, 10
4. 87-15. 16%
APR, 10
4. 25-12. 73%
JUL, 10
4. 814. 29%
FEB, 11
4. 99-10. 25%
MAY, 11
4. 6314. 58%
JUN, 11
6. 6643. 84%
JUL, 11
5. 5-17. 42%
AUG, 11
6. 9927. 09%
SEP, 11
4. 48-35. 91%
OCT, 11
7. 4165. 40%
NOV, 11
4. 2-43. 32%
DEC, 11
5. 5732. 62%
JAN, 12
4. 25-23. 70%
MAR, 12
2. 9531. 40%
MAY, 12
4. 3747. 64%
JUN, 12
3. 1-29. 06%
JUL, 12
5. 1566. 13%
AUG, 12
4. 02-21. 94%
SEP, 12
3. 17-21. 14%
AUG, 12
4. 0226. 81%
SEP, 12
3. 17-21. 14%
NOV, 12
7. 21126. 73%
DEC, 12
5. 22-27. 60%
PARAMETER SPOT
PORTFOLIO VALUE
100
AVERAGE RETURN SPOT
1. 772
STANDARD DEVIATION IN SPOT
2. 269332
CONFIDENCE LEVEL
0. 95
CALCULATION
MINIMUM RETURN WITH 95 % PROB
-1. 96072
VALUE OF PORTFOLIO
-96. 0719
REVENUE AT RISK
196. 0719Coal, South African export price, US Dollars per Metric Ton
MONTH
SPOT
% CHANGE
MAY, 08
120. 710. 99%
JUN, 08
142. 3817. 96%
JUL, 08
167. 7517. 82%
OCT, 08
109. 7-25. 75%
NOV, 08
89. 38-18. 52%
DEC, 08
77. 25-13. 57%
MAR, 09
58. 56-15. 20%
DEC, 09
73. 811. 08%
JAN, 10
86. 9417. 80%
NOV, 10
103. 213. 42%
DEC, 10
115. 2411. 67%Calculation
PARAMETER SPOT
PORTFOLIO VALUE
100
AVERAGE RETURN SPOT
24. 61107
STANDARD DEVIATION IN SPOT
31. 89444
CONFIDENCE LEVEL
0. 95
CALCULATION
MINIMUM RETURN WITH 95 % PROB
-27. 8506
VALUE OF PORTFOLIO
-2685. 06
REVENUE AT RISK
2785. 062Mont Belvieu, TX Propane Spot Price FOB (Dollars per Gallon)
MONTH
SPOT
% CHANGE
FEB, 08
1. 425181. 62%
AUG, 08
1. 651-11. 33%
OCT, 08
1. 045-31. 70%
NOV, 08
0. 738-29. 38%
DEC, 08
0. 61-17. 34%
JAN, 09
0. 72719. 18%
JUN, 09
0. 846-20. 68%
JUL, 09
0. 752-11. 11%
AUG, 09
0. 90620. 48%
DEC, 09
1. 1910. 59%
JAN, 10
1. 31210. 25%
MAR, 10
1. 13611. 53%
MAY, 12
0. 95420. 23%
JUN, 12
0. 788-17. 40%
JUL, 12
0. 87410. 91%
DEC, 12
0. 79710. 45%Calculation
PARAMETER SPOT
PORTFOLIO VALUE
100
AVERAGE RETURN SPOT
0. 231547
STANDARD DEVIATION IN SPOT
0. 288443
CONFIDENCE LEVEL
0. 95
CALCULATION
MINIMUM RETURN WITH 95 % PROB
-0. 2429
VALUE OF PORTFOLIO
75. 71005
REVENUE AT RISK
24. 28995
INFERENCE
All the commodities are taken only for real fluctuations among all propane comes out to have minimum revenue at risk than come natural gasThis corresponds that propane and natural gas both requires less purification when compared to other two and both are ready to use thus have much less exposes to market fluctuations. To add to this the market capitalizations for these two is also less to have such an impact.
LIQUIDATION VALUE AT RISK
The total potential loss that could occur if an asset has to be liquidated. For instance, a fund might try to determine what would happen if it were forced to retire an unproductive assert. (William Steinhurst, 2006)For liquadation the confidance level taken has to be ten percent or less than ten percent this is done to make sure the least confidence on the assert and the liquidation value at risk.
CALCULATION
Europe Brent Spot Price FOB (Dollars per Barrel)
LIQUDATION AT RISK
PORTFOLIO VALUE
100
AVERAGE RETURN SPOT
21. 07103
STANDARD DEVIATION IN SPOT
24. 43969
CONFIDENCE LEVEL
0. 10
CALCULATION
MINIMUM RETURN WITH 100 % PROB
52. 39176
VALUE OF PORTFOLIO
5339. 18
VALUE AT RISK
-5239. 18Price of U. S. Natural Gas LNG Imports (Dollar/ Thousand Cubic Feet)
LIQUDATION AT RISK
PORTFOLIO VALUE
100
AVERAGE RETURN SPOT
1. 948306
STANDARD DEVIATION IN SPOT
2. 483838
CONFIDENCE LEVEL
0. 10
CALCULATION
MINIMUM RETURN WITH 100 % PROB
5. 131472
VALUE OF PORTFOLIO
613. 15
VALUE AT RISK
-513. 15Coal, South African export price, US Dollars per Metric Ton
LIQUDATION AT RISK
PORTFOLIO VALUE
100
AVERAGE RETURN SPOT
21. 01588
STANDARD DEVIATION IN SPOT
27. 45148
CONFIDENCE LEVEL
0. 10
CALCULATION
MINIMUM RETURN WITH 100 % PROB
56. 19638
VALUE OF PORTFOLIO
5719. 64
VALUE AT RISK
-5619. 64Mont Belvieu, TX Propane Spot Price FOB (Dollars per Gallon)
LIQUDATION VALUE AT RISK AT RISK
PORTFOLIO VALUE
100
AVERAGE RETURN SPOT
0. 277567
STANDARD DEVIATION IN SPOT
0. 329396
CONFIDENCE LEVEL
0. 10
CALCULATION
MINIMUM RETURN WITH 100 % PROB
0. 699704
VALUE OF PORTFOLIO
169. 97
VALUE AT RISK
-69. 97
INFERENCE
All the commodities are taken only for real liquidations, among all propane comes out to have minimum liquidation value at risk than come natural gas. This corresponds that propane and natural gas both requires less purification when compared to other two and both are ready to use thus have much less exposes to market liquidation. To add to this the market capitalizations for these two is also less to have such an impact.
COSTS AT RISK
Cost-at-Risk (CaR) is a supplementary measure used in the management of the interest-rate risk on the domestic central-government debt. CaR quantifies the risk on the debt and gives important input to the weighing of interest-rate risk against costs. A distinction is made between absolute and relative CaR. Absolute CaR for a given year indicates the maximum costs with a probability of 95 per cent. Relative CaR is the difference between absolute CaR and the average interest costs. Relative CaR thus indicates the maximum increase in the costs for a given year, with a probability of 95 per cent. (Cost-at-Risk for the Domestic Debt, 2000)In our study the cost at risk is taken with respect to the Average majority prime rate charged by banks (US banks) . All the fluctuations and impacts are calculated annually in order to get maximum exposer to the intrest rates. The cost of precuring and trading a commdity is impacted by the intrest rates largly.
CALCULATION
Europe Brent Spot Price FOB (Dollars per Barrel)
calculation
spot price
MAX 08
132. 72
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
126. 084
MEAN 08
96. 8475
RELATIVE COST AT RISK
29. 2365
MAX 09
76. 66
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
72. 827
MEAN 09
61. 49
RELATIVE COST AT RISK
11. 337
MAX 10
91. 45
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
86. 8775
MEAN 10
79. 511667
RELATIVE COST AT RISK
7. 3658333
MAX 11
123. 26
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
117. 097
MEAN 11
111. 26417
RELATIVE COST AT RISK
5. 8328333
MAX 12
125. 45
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
119. 1775
MEAN 12
111. 65167
RELATIVE COST AT RISK
7. 5258333Price of U. S. Natural Gas LNG Imports (Dollar/ Thousand Cubic Feet)
spot price
MAX 08
12. 99
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
12. 3405
MEAN 08
9. 9275
RELATIVE COST AT RISK
2. 413
MAX 09
7. 63
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
7. 2485
MEAN 09
4. 7575
RELATIVE COST AT RISK
2. 491
MAX 10
5. 74
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
5. 453
MEAN 10
4. 474167
RELATIVE COST AT RISK
0. 978833
MAX 11
7. 41
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
7. 0395
MEAN 11
5. 563333
RELATIVE COST AT RISK
1. 476167
MAX 12
7. 21
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
6. 8495
MEAN 12
4. 156667
RELATIVE COST AT RISK
2. 692833Coal, South African export price, US Dollars per Metric Ton
spot price
MAX 08
167. 75
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
159. 3625
MEAN 08
112. 2133
RELATIVE COST AT RISK
47. 14917
MAX 09
76. 4
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
72. 58
MEAN 09
64. 68333
RELATIVE COST AT RISK
7. 896667
MAX 10
115. 24
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
109. 478
MEAN 10
91. 6225
RELATIVE COST AT RISK
17. 8555
MAX 11
124. 03
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
117. 8285
MEAN 11
116. 2967
RELATIVE COST AT RISK
1. 531833
MAX 12
106. 26
PROBABILITY
0. 95
ABSOLUTE COST AT RISK
100. 947
MEAN 12
92. 92
RELATIVE COST AT RISK
8. 027Mont Belvieu, TX Propane Spot Price FOB (Dollars per Gallon)
spot price
max 08
1. 862
probability
0. 95
ABSOLUTE COST AT RISK
1. 7689
MEAN 08
1. 32875
RELATIVE COST AT RISK
0. 44015
max 09
1. 19
probability
0. 95
ABSOLUTE COST AT RISK
1. 1305
MEAN 08
0. 841833
RELATIVE COST AT RISK
0. 288667
max 10
1. 312
probability
0. 95
ABSOLUTE COST AT RISK
1. 2464
MEAN 08
1. 1655
RELATIVE COST AT RISK
0. 0809
max 11
1. 56
probability
0. 95
ABSOLUTE COST AT RISK
1. 482
MEAN 08
1. 463333
RELATIVE COST AT RISK
0. 018667
max 12
1. 294
probability
0. 95
ABSOLUTE COST AT RISK
1. 2293
MEAN 08
1. 003917
RELATIVE COST AT RISK
0. 225383
INFERENCE
For all the years individually natural gas and propane lave very less cost at risk when compared to other two commodities. This again proves that the more commodity is exposed in terms of market capitalization more is the chance of running into risk , realization in tough and immunity is weak. All those commodities namely here Brent and coal have higher cost at risk with respect to interest rate index.
Volatility
Measure of variation of the value of portfolio within a given time spectrum. This also shows the impact of random market fluctuation on the valuation. Due to impact on one assert the corresponding change in other asset and relative change in valuation. Volatility impact is calculated with respect to CBOE Volatility Index which is benchmark in volatility index. This will give relative exposure corresponds to each date. To calculate the implied volatility standard deviation of the stress impact of given index as well as the spot prices are to be deduced. The correlation of the two values is deduced in order to get standard deviation.
CALCULATION
Europe Brent Spot Price FOB (Dollars per Barrel)
standard deviation
6. 801573
implied volatility
2. 607983Price of U. S. Natural Gas LNG Imports (Dollar/ Thousand Cubic Feet)
standard deviation
1. 048153
implied volatility
1. 023794Coal, South African export price, US Dollars per Metric Ton
standard deviation
10. 80215
implied volatility
3. 286663Mont Belvieu, TX Propane Spot Price FOB (Dollars per Gallon)
standard deviation
0. 114602
implied volatility
0. 338529
INFERENCE
Coal and Brent have higher volatility with respect to the volatility index in consideration. The volatility in the market is impacting the commodities having more exposure to the market and are more venerable in nature.
Valuation
Based on black soles theory we can find the valuation of the portfolio . there are two main attributes of this theory these are preference free and risk neutral nature of portfolio . from this theory for our study we are adopting only risk neutral nature of portfolio. In this theory of valuation is based on the fact that assert price is lognormally proportional to the market as well as time spectrum
Taking binomial calculation for the current value of portfolio while taking the risk neutral nature of black soles model. For the calculation time frame taken is 5 years, value of portfolio ( assert) is taken 100 units, average riskless interest rate taken in the study is 3 %, market implication affecting the given portfolio is 10 % i. e. implied volatility
Thus if we will form binomial portfolio tree with 10% volatility, we will get
100
90. 48 110. 5281. 87 100 122. 1474. 08 90. 48 110. 52 134. 9967. 03 81. 87 100 122. 14 149. 18 60. 65 74. 08 90. 48 110. 52 134. 99 164. 87