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Commodity Trading Option Pricing

Commodity Trading Option Pricing. 28.3.2011. Optionpricing. Relative Pricing  Comparativeness Accessible through probabilistic approach  Which is the right probability distribution? Accessible through “arbitrage free” approach  Practicability?. Plain Vanilla Option.

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Commodity Trading Option Pricing

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  1. Commodity Trading Option Pricing 28.3.2011

  2. Optionpricing • Relative Pricing  Comparativeness • Accessible through probabilistic approach  Which is the right probability distribution? • Accessible through “arbitrage free” approach  Practicability?

  3. PlainVanilla Option • A Callisthe right to BUY theunderlyinginstrument at theexpiration date at the STRIKE price. Thevalue at expirationisthegreater of (price of theunderlyingthethat date minus strikeprice) and zero • A Putisthe right to SELL theunderlyinginstrument at theexpiration date at the STRIKE price. Thevalue at expirationisthegreater of (strikeprice minus price of theunderlyingthethat date) and zero

  4. Probabilistic Approach • Whatisthevalue of callstrike 3 on a dice, one roll?  KnowProbability Distribution!

  5. Probabilistic Approach • Sum of all payoutmultipliedbythereprobabilityover all events: 0*1/6 + 0*1/6 + 0*1/6 + 1*1/6 + 2*1/6 + 3*1/6

  6. Arbitrage Free Approach • Situation A: An Asset will be worth either 20% more or 10% less, tomorrow • Situation B: An Asset will be worth either 10% more or 40% less, tomorrow • Which Call at-the-money (Strike today’s price) is more valuable? • Idea from Didier Cossin, IMD

  7. PricingtheCalls • Assumption: one can buy or sell both underlyings and call freely and without fees or interest rate (the later make no substantial difference). Assume Price underlying 100. • Suppose the price at the current market is very low, buy 1000 calls and sell D * 1000 underlyings, such that in both cases you receive the same profit. • If you manage to do so, you can make a sure profit as long the price is too low.  Profit must be zero in an arbitrage free world!

  8. Case A • Price Underlying 100, Price Call C • Buy 1000 Calls – pay 1000*C • sellD * 1000 underlyings – receive D * 100’000 • Upper Case Profit=1000*(20-C)- D*20’000 • Lower Case Profit=1000*(-C) + D*10’000 • Equal if D = 2/3 • Equal zero if C = 6.667

  9. Case B • Price Underlying 100, Price Call C • Buy 1000 Calls – pay 1000*C • sellD * 1000 underlyings – receive D * 100’000 • Upper Case Profit=1000*(10-C)- D*10’000 • Lower Case Profit=1000*(-C) + D*40’000 • Equal if D = 1/5 • Equal zero if C = 8 !!!

  10. General Case • Price Underlying 100 canbeeither X up (100+X) or Y down (100-Y), Price Call C • Buy 1000 Calls – pay 1000*C • sellD * 1000 underlyings – receive D * 100’000 • Upper Case Profit=1000*(X-C)- D*X*1000 • Lower Case Profit=1000*(-C) + D*Y*1000 • Equal if D = X/(X+Y) • Equal zero if C = X*Y/(X+Y)  X-Y Symmetry!!!!

  11. Discussion (I) • Option pricesVolatility not expectation! (TAI????) • Independent of probabilisticview? Check X>0 and Y<0.  Case B: Thefactthatthecurrentpriceismuchcloser to theuppercasethan to thelowercaseimpliesthattheuppercaseismoreprobable!!!

  12. Discussion (II) • ProbabilisticView p:= probabilitythatpriceincreases (uppercase) / 1-p:= probabilitythatpricedecreases (lowercase) • Case A: p*120 + (1-p)*90 = 100  p = 1/3; 1-p= 2/3 • Case B: p*110 + (1-p)*60 = 100  p = 4/5; 1-p= 1/5 • 1-p = D

  13. Probability = Model forUncertainty • Randomness Uncertainty • Few thing are truly random, lots of influence are not detectable in reasonable time

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