Зезерова Виктория Васильевна
Learning in the Oil Futures Markets: Evidence and Macroeconomic Implications
Прикладная экономика и математические методы
In this work we model learning by agents about persistance of oil price movements which are captured well by futures prices. Hystorical price analysis shows that that during 90s oil futures were following long run equilibrium what means that spot fluctuations were considered by agents as purely temporary. Since 2003 all oil jums were considered as driven by fundamentals and were expected to be rather persistent. Learning algorithm was applied by Kalman filter, recieved estimated data are in line with futures prices. Estimated DSGE model with oil storage helped to link expectations about shocks with economy. Results suggest that under learning setup we recieve more muted effect on economy than in situation with full information.