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Palisade User Conference October 25-26, 2007 Making It Happen: Assessing Volatility &

Palisade User Conference October 25-26, 2007 Making It Happen: Assessing Volatility & Employing Simulation to Mitigate Risk By Roy Nersesian Monmouth University Columbia University. Three Areas of Employing Simulation To Mitigate Risk: Chartering Decision Optimization Swap Optimization

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Palisade User Conference October 25-26, 2007 Making It Happen: Assessing Volatility &

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  1. Palisade User Conference October 25-26, 2007 Making It Happen: Assessing Volatility & Employing Simulation to Mitigate Risk By Roy Nersesian Monmouth University Columbia University

  2. Three Areas of Employing Simulation • To Mitigate Risk: • Chartering Decision Optimization • Swap Optimization • Substituting Insurance for Swaps

  3. Typical Long-Term Rate Forecast Type I The market is presently at $10 per ton and will improve marginally over the next 5-10 years for the following reasons: 1. 2. 3.

  4. Typical Long-Term Rate Forecast Type II The market is presently at $10 per ton and will decline marginally over the next 5-10 years for the following reasons: 1. 2. 3.

  5. Typical Long-Term Rate Forecast Type III The market is presently at $10 per ton and will remain unchanged over the next 5-10 years for the following reasons: 1. 2. 3.

  6. So Which Is Selected? 10% Fact X% What Client Wants to Hear Y% What Is in the Self-Interest of the Forecaster X% + Y% = 90%

  7. Another Approach Assume Economic Growth for Major Oil Consumers Translate to Oil Import Demand Identify Sources Translate to Tanker Demand Project Tanker Supply Compare and Obtain Estimate of Surplus Surplus Determines Rate Forecast

  8. Interesting Problem: Future Tanker Supply Depends on Newbuilding Orders and Scrapping Activity Both Dependent on the Market High Market – Order Ships and Defer Scrapping Low Market – Scrap Ships and Defer Ordering Must Know Result of Forecast in order to Determine Future Vessel Supply Supply Is Then Matched to Demand To Obtain the Rate Forecast!

  9. Volatility Greatly Diminished in Forecast!

  10. General Nature of Macroeconomic Forecasts Less Volatility Outlook Poor for Next Few Years Be Patient – Market Will Improve The Infamous Check () Forecast

  11. At least this forecast is has a rationale not dependent on what the client wants to hear! But What’s Missing?

  12. The Irrationality of Life -The Wild Cards of Reality!

  13. Why Not Just Go With the Flow? Three Markets: Weak, Strong, and In-Between

  14. Market Conditions 0 – 70% Chance Weak Market 1 – 20% Chance Transition Market 2 – 10% Chance Strong Market

  15. For a Fleet of Four Vessels Select Type of Charters Run @RISK Simulation

  16. Mean 1,817 Risk 2.13%

  17. Mean 2,276 Risk 1.73%

  18. Mean 2,031 Risk 0.15%

  19. Mean 2,335 Risk 19.6%

  20. Oil Company Reaction One Big Yawn • Have Given up on Discrete Forecasts • Admit to Failure Because of Wild Cards • Believe in a Diversified Portfolio of Charters • Very Focused on Today’s Deals (Overriding Consideration in Diversification Nevertheless This is a Methodology of Analysis For Billions of Dollars of Shipping Expense

  21. Oil Company Reaction to Today’s Market • Today’s Market Is Strong, But How Long? • As Long as China Keeps Growing at 10%/Year • But For How Long? Who Knows! • So Why Bother? Simple Solution: Stay Diversified and Let Market Deals DetermineDiversification, Not a Computer Simulation!

  22. Swap Optimization

  23. “We Advise Our Clients to Cover 20-30% of Their Exposure With Swaps” Where Does That Come From? Heuristic Advice (Sounds Good) Is There Another Way?

  24. Before Anything Can Occur, Have to be Able To Simulate Future Prices Can Always Explain Past Price Patterns But The Future Has All the Appearance of Randomness

  25. What are the Minimum Inputs Required To Forecast the Future Price?

  26. Price over $70: Propensity to Sell Price over $80: 90% Chance of a –1 (Down Market) Price below $40: Propensity to Buy Price below $30: 90% Chance of a +1 (Up Market)

  27. Range For Each of 5 Years Average 5-Year Range Use RISKOptimizer To Determine These Factors Objective: Desired Range of $30 Less Average Range Close to 0 In Order for This Equation To Generate an Objective Value Close to Zero AeBx - C

  28. What We Would Like: Large Probability of Small Incremental Change Small Probability of Large Incremental Change

  29. Not Too Concave! Implies a Linear Relationship Between Probability of Price Change and Degree of Change (Can Incorporate a Maximum Change)

  30. Nevertheless Can Create Any Chart Pattern Imaginable! Head and Shoulders?

  31. Nice Breakout

  32. The Dog Just Keep Hitting the F9 Key to Create a Slew Of Price Patterns

  33. Problem: A Copper Mining Company Risk: Low Price of Copper

  34. Revenue in U.S. $ and Debt in British £s Risk: Adverse Change in Exchange Rates

  35. Inputs Outputs Modeling Future Copper Price (Based on Past Prices)

  36. A Nice Concave Shape! The Probability of a Small Incremental Change Higher Than Probability of A Large Incremental Change

  37. Inputs Outputs Modeling Future GBP/$ Conversion Rate (Based on Past Conversion Rates)

  38. Not As Concave as Desired Probability of Any Incremental Change About The Same (Linear Relationship)

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