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Published byAudra Anthony Modified over 9 years ago
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- 1 - OMP 1 Enterprise DFA™ Application of Dynamic Financial Analysis in the Oil Industry
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- 2 - OMP 2 Discussion Outline FBackground FOil Company Imperatives FProblem Diagnosis FThe Application of DFA FThe Opportunities for Actuaries
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- 3 - OMP 3 Background FStochastic Financial Modeling Not New Significant Academic Interest Standard in 1970’s Finance Texts Promoted Heavily by IBM et a FDid Not Gain Wide Acceptance in Practice Miscast as Predictive Tool Difficult and Expensive to Implement Measuring / Understanding Risk Not Valued
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- 4 - OMP 4 Background Considered Evidence that Long Term Forecasting Was Not Practical Time Results
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- 5 - OMP 5 Background FNew Focus in Investment Management Earnings Growth Was Theme Results Now Handicapped on Risk FNew Pressure From the Market Earnings Predictability Managing Analysts’ Expectations FManagements Search for Tools to Understand / Manage Earnings Volatility
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- 6 - OMP 6 Oil Company Imperatives FLarge Oil Company’s Stock Under Performing Management Believed It Undervalued Earnings “Surprises” Had Hurt Values Perceived as High Risk Company FBoard Losing Confidence in Management Huge Bets on High Risk Projects Unsure How Risks Managed “We Going to Lose the Ranch?”
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- 7 - OMP 7 Oil Company Imperatives FProject Undertaken to Evaluate Earnings and Business Risks. FObjectives Included: Understand Earnings Forecast Failures Communicate Risks to Board Change Market’s Perception of Company Risk
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- 8 - OMP 8 Problem Diagnosis - Forecast Failures FEPS Forecasts Only Compiled by Corporate No True Enterprise Model Roll Up Of Divisional Forecasts Tied to Business Planning / Challenge Process Significantly Different Risk Levels / Drivers Each Used its Own Economic Assumptions Forecasts were Deterministic Point Estimates
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- 9 - OMP 9 Problem Diagnosis - Board FInvestment Project vs. Enterprise Focused Analyses - Complex Issues FHigh Detail - Low Information FLack of Context and Comparability FNo Enterprise Level Conclusions
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- 10 - OMP 10 Problem Diagnosis - Market FMarket Perceived Company High Risk v. Competitors FReinforced by Earnings “Surprises” FLow Appreciation for Risk Hedging Programs FResulted in Lower than Market P/E
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- 11 - OMP 11 Application of DFA FProject to Address Issues Using DFA Type Analysis Enterprise Level Financial Model Developed - Tied to Corporate Plans High Impact Variables Identified Assumption Variability from Key Executives Disaggregation Analysis Competitive Analysis Board Presentations
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- 12 - OMP 12 DFA Methodology FEnterprise Model FCommon Environmental Assumptions Economic - Common for All SBU’s Non Management Controlled Issues Corporate Financial Leverage FStrategy Based Management Assumptions Business Unit Based Probability of Strategy Implementation
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- 13 - OMP 13 DFA - Methodology Exploration / Production Coal / Power Refining / Marketing Chemicals Economic Environment - Weather - Economic Growth - Supply Constraints - Spot Market Prices Management Interventions Enterprise Model Structure
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- 14 - OMP 14 DFA - Methodology FEconomic - Non Management Controlled Energy Price / Demand Drivers »Weather »Economic Growth »Supply Conditions Capital Markets Conditions FCorporate Financial Structures Financial Leverage Hedging / Market Risk Control Common Environmental Assumptions
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- 15 - OMP 15 DFA - Methodology FExploration / Production Profitability of Existing Production Success of Exploration Opportunities Project Selection / New Market Growth FRefining & Marketing Sales Growth in High Value Fuels Expansion in High Growth Markets Shut Refining in Low Growth Markets Reduce Unit Expenses Business Strategies
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- 16 - OMP 16 DFA - Methodology FChemicals Reduce Unit Costs Redesign Major Processes Commercialize New Technologies FCoal, Minerals & Power Increase Facility Utilization Mine Expansions Expand Electric Power Business Business Strategies
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- 17 - OMP 17 DFA Results Revenues Earnings per Share x Consolidated Forecast Earnings Forecast Failures
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- 18 - OMP 18 DFA Results Revenues Earnings Per Share x Consolidated Forecast 0 } Capital Requirement 100 Earnings Forecast Failures 95% Confidence Level x Expected Value Aggressive vs. Most Likely Assumptions Used in Forecasts
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- 19 - OMP 19 DFA Results Revenues Earnings per Share Expected Value x With Leverage Without Leverage x Communicate Risks to Board Financial Leverage Added High Risk and Small Earnings Gain
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- 20 - OMP 20 DFA Results Revenues Earnings per Share x x x Refining / Marketing Chemicals Exploration/ Production 0 Communicate Risks to Board x Coal Businesses Differ in Risk - Exploration Forecasts Aggressive
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- 21 - OMP 21 DFA Results Revenues net of Hedge Earnings per Share x Base Strategy x Hedge All Price Risk 0 Communicate Risks to Board Energy Market Price Greatest Risk Source
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- 22 - OMP 22 DFA Results Unit Operating Costs Earnings per Share x 0 Communicate Risks to Board Strategies to Lower Costs Had Small Impact on Risk
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- 23 - OMP 23 DFA Results Revenues Earnings % of Revenue 0 Market Perception of Risk Client Had Lower Risk than Most Competitors Client Comp. C Competitor A Competitor B
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- 24 - OMP 24 Opportunities for Actuaries FRisk Analyses are Central to Industrial Managers FDFA Type Analysis is High Value Added FActuaries Must Expand beyond Technicians to become Strategists FIf Actuaries Don’t - Others Will
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- 25 - OMP 25 Preliminary DFA Results
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