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FRE 501 2013 Lab 8 (Oct 28 th )

FRE 501 2013 Lab 8 (Oct 28 th ). Reflections on 6 weeks of Trading Applying Theory to Real-life. Mission Statement. Understand how commodity futures markets work, Formulate and refine trading and hedging strategies, Learn and practice risk management,

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FRE 501 2013 Lab 8 (Oct 28 th )

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  1. FRE 501 2013Lab 8 (Oct 28th) Reflections on 6 weeks of Trading Applying Theory to Real-life

  2. Mission Statement Understand how commodity futures markets work, Formulate and refine trading and hedging strategies, Learn and practice risk management, In preparation for future professional roles

  3. Trading Game Rankings

  4. Relationship between Ranks

  5. Ranks: Avg Gain per unit risk vs Sharpe

  6. Quadrant of skill vs risk appetite

  7. Who would you invest with? Would rather invest money with those who can allocate capital efficiently – demonstrated proficiency at generating good returns per unit of risk taken It is easier to teach / encourage a superior investor with excellent judgment to increase/decrease the size of their positions to get a desired return Than it is to teach a risk-loving person to become a superior investor

  8. Applying Theory to Real-Life

  9. Broadly, You have covered Concepts • Prices over space • Prices over time • Prices over form Models – 2 basic categories • Simple models (two factor) • Complex models (multi-factor )

  10. Simple Models You use your two factor models (other factors are exogenous) to illustrate/solve simple what-if and dynamic problems: • 3-panel trade/storage diagramx(only 2 countries or 2 periods) • Convenience yield diagram • Single-commodity blending

  11. Complex Models We have to use the complex models for multi-factor problems (excel models maximizing NAW) • multi-country • multi-period • multi-commodity blending Most real-world problems that deserve attention are pretty much complex. Outcomes of complex situations are often non-linear and jerky – complex models are important for understanding these dynamics. A quick comment about Econometrics: Scientists use data analysis techniques to calibrate parameters for their models Economists started using the same techniques to find parameters to model their data – the common ‘kitchen sink’ approach. Naïve assumptions based on historical data can lead to very bad policy

  12. Real World Applications: Spatial Remember 5 country spatial model for tomatoes Do you think Spain’s ban on Argentinian Soy Methyl Ester (Apr 2012) had any effect on the market price of SME or soybeans? Hardly – global traders simply shuffled trade around. Argentinian SME went to Italy and Germany instead. Brazil and US SME went to Spain.

  13. Real World Applications: Spatial 1. Does the application of an export tax on Crude Palm Oil in Indonesia make the domestic price higher or lower? 2. Does it make the export price higher than the world market price? • Lowers it by the amount of the tax • Indonesian exporters are price takers, domestic producers bear the full burden of the tax

  14. Real World Applications: Temporal Introducing the element of time and hence inter-temporal costs such as storage and costs of capital – help you to understand why and how spatial equilibriums can be violated (e.g. commodity finance importing in China) And why futures curves can swing between contango and backwardation

  15. Real World Applications: Temporal The real cost of storage is extremely high for many food commodities, especially in tropical climates, where fruit rots quickly – products must often be processed within 24 hours Tropical: Sugarcane; Palm OilTemperate: Milk Significant market power is in the hands of the processors, the primary producers always get squeezed

  16. Real World Applications: Blending Examples covered in lecture are primarily blending of one commodity to optimize prices according to contract standards The basic concept is one of mixing ABC in different proportions to get specified qualities of DEF Why is blending important? This concept can be broadly applied to many other areas of business and policy

  17. Real World Applications: Blending • Cereals are routinely blended by companies • Special-K, Honey-Oat, Captain Crunch • Animal/Livestock Feed • Consumer Vegetable Oil (Supermarket retail) • Biodiesel All multi-factor blending optimization problems Blending is basically your concept of demand substitution in action.

  18. Real World Applications: Blending Vegetable Oil Cloud Points: (start solidifying into fat) • Rapeseed Oil : -3.9 °C (most expensive) • Soybean Oil : -3.9 °C • Refined Palm Oil : 8-10 °C (cheapest) Blenders/Bottlers optimize their blends depending on market prices and market requirements. North Asia (N. china, Korea, Japan) gets close to 100% soybean or rapeseed oil. South Asia gets close to 100% palm oil. Places in the middle get a blend. All are labeled and sold as 100% vegetable oil, which is true.

  19. Seasonal Biodiesel Demand in Europe: 2010 Real World Applications: Blending

  20. Real World Applications: Blending Honey: Manuka- NZ and AUS produce 1700 tonnesManuka honey/year, but 10,000 tonnes are sold each year (a lot in China). Part blending part fraud Chinese Honey: When US, Canada, EU banned Chinese honey because of antibiotic use (Chloramphenicol), exports from Australia tripled the next year (much more than they actually produce) Where do you think it came from? Pollination of pear trees by hand in China: All insects dead from pesticide

  21. Real World Applications: Blending Coffee Roasts are also blends - Alejandro will discuss next week Tea Blends – Bee will discuss later

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