Trading Volatility in Commodities. Péter Dobránszky. 25 th March 2009, New York

Transcription

1 Trading Volatility in Commodities Péter Dobránszky 25 th March 2009, New York

2 Introduction Assessing which commodity trading models thrive in volatility Getting new focus because of the underperformance showed by other markets Commodity derivatives market is not so advanced as equity or FX derivatives markets Smaller market, lower volume No best practice for quotation conventions Products and quotation conventions closest to equities and FX Approach the modelling problem through yield curve models Data providers with intra- and extrapolated market data that are not necessarily in line with each other 2

3 Asset classes EURUSDV3M Curncy VIX Close CL3 Comdty Mar Mar Mar Mar Mar Mar-09 3

4 Schwartz-Smith calibrated to AHD on 03-Jun-08 Market vol. Calibrated vol. Market fw d. Calibrated fw d. 3,200 29% 3,150 27% 3,100 25% 3,050 Volatility 23% 3,000 Forward 21% 2,950 19% 2,900 17% 2,850 15% 2, TTM 4

5 Copper (CAD) futures and IVs LPI3 LPI15 LPI27 LPI63 LMCADS03 LMCADS15 LMCADS63 LMCADS Mar Jun Sep Dec Mar Jun Sep Dec Mar

6 Primary aluminium (AHD) futures and IVs LAI3 LAI15 LAI27 LAI63 LMAHDS03 LMAHDS15 LMAHDS63 LMAHDS % % % % % Mar Jun Sep Dec Mar Jun Sep Dec Mar

7 Quoting the smile by delta vol BF RR put delta -25% ATM +25% call delta 7

8 FX relative risk reversals EURUSD 25R3M / V3M EURUSD 25R1Y / V1Y EURUSD 25R4Y / V4Y 15% % % % 10-Mar Mar Mar Mar Mar Mar

9 FX relative butterflies EURUSD 25B3M / V3M EURUSD 25B1Y / V1Y EURUSD 25B4Y / V4Y 7% 1.8 6% % 1.2 4% 1.0 3% 0.8 2% % Mar Mar Mar Mar Mar Mar

10 WTI oil relative risk reversals CL3 25RR / V CL12 25RR / V CL60 25RR / V 1 5% -5% -1-15% 07-Jul Aug Sep Oct Nov Dec Jan Feb-09 10

11 WTI oil relative butterflies CL3 25B / V CL12 25B / V CL60 25B / V 5% 4% 3% 2% 1% 07-Jul Aug Sep Oct Nov Dec Jan Feb-09 11

12 LCO oil 3M and 63M IV smiles in the last half year

13 19/09/08: strong short smile, skew to right, light long smile, skew to left

14 20/10/08: high short vol, stronger short smile, no short skew, unchanged long skew

15 19/11/08: no short smile, clear skew to left, no long smile, curve is rather flat

16 19/12/08: further vol increase on short, no change on long

17 20/01/09: both short term and long-term volatilities are lower, skews are stronger

18 20/02/09: short smile back, long smile back, very strong long smile on right

19 20/03/09: no changes

20 Gold IV term structure dynamics XAUUSDV3M Curncy XAUUSDV1Y Curncy XAUUSDV4Y Curncy Mar Jun Sep Dec Mar Jun Sep Dec Mar-09 20

21 Silver IV term structure dynamics XAGUSDV3M Curncy XAGUSDV6M Curncy XAGUSDV1Y Curncy Mar Jun Sep Dec Mar Jun Sep Dec Mar-09 21

22 Commodity modelling requirements Mean-reversion in asset prices short-term, long-term Stochastic convenience yield Decreasing volatility term structure Multi-factor stochastic volatility short-term, long-term Volatility smile also on long-term Unspanned stochastic volatility (cannot model the skew) Equilibrium volatility level is stochastic also Jumps Discontinuous asset path Closer futures jump larger than longer futures Stochastic mean-reverting jump frequency Stochastic implied volatility skew Reduce the need for stochastic volatility 22

23 Agenda workshop 1. Modelling Financial Asset Price Dynamics 2. Affine Jump-Diffusion Processes and the Fourier Inversion 3. Modelling the Dynamics of Commodity Curves 4. Pricing Volatility and Jump Derivatives 5. Hedging and Risk Management 6. Questions 23

24 Questions Contact details: Péter Dobránszky Further details: 24