ERM David L Olson University of NebraskaLincoln Desheng
ERM David L. Olson, University of Nebraska-Lincoln Desheng Wu, University of Reykjavik, University of Toronto Enterprise Risk Management Not just insurance, auditing, risk analysis A philosophy – A way of business
Definition • Systematic, integrated approach – Manage all risks facing organization • External – – – • Economic (market - price, demand change) Financial (insurance, currency exchange) Political/Legal Technological Demographic Internal – – Human error Fraud Systems failure Disrupted production • Means to anticipate, measure, control risk Finland May 2010 2
Finland May 2010 3
Finland May 2010 4
DIFFERENCES Traditional Risk Mgmt ERM Individual hazards Context - business strategy Identification & assessment Risk portfolio development Focus on discrete risks Focus on critical risks Risk mitigation Risk optimization Risk limits Risk strategy No owners Defined responsibilities Haphazard quantification Monitor & measure “Not my job” “Everyone’s responsibility” Finland May 2010 5
Risk & Business • Taking risk is fundamental to doing business – Insurance • Lloyd’s of London – Hedging • Risk exchange swaps • Derivatives/options • Catastrophe equity puts (cat-e-puts) – ERM seeks to rationally manage these risks • Be a Risk Shaper Finland May 2010 6
Types of Risk Stroh [2005] • External environment – Competitors; Legal; Medical; Markets • Business strategies & policies – Capital allocation; Product portfolio; Policies • Business process execution – Planning; Technology; Resources • People – Leadership; Skills; Accountability; Fraud • Analysis & reporting – Performance; Budgeting; Accounting; Disclosure • Technology & data – Architecture; Integrity; Security; Recovery Finland May 2010 7
Another view Slywotzky & Drzik, HBR [2005] • Financial – Currency fluctuation • DEFENSE: Hedging • Hazard – Chemical spill • DEFENSE: Insurance • Operational – Computer system failure • DEFENSE: Backup (dispersion, firewalls) • New technology overtaking your product – ACE inhibitors, calcium channel blockers ate into hypertension drug market of beta-blockers & diuretics • Demand shifts – Gradual – Oldsmobile; Rapid - Station wagons to Minivans Finland May 2010 8
Technology Shift • Loss of patent protection • Outdated manufacturing process – DEFENSE: Double bet • • Invest in multiple versions of technology Microsoft: OS/2 & Windows Intel: RISC & CISC Motorola didn’t – Nokia, Samsung entered Finland May 2010 9
Brand Erosion • Perrier – contamination • Firestone – Ford Explorer • GM Saturn – not enough new models – DEFENSE: Redefine scope • Emphasize service, quality – DEFENSE: Reallocate brand investment • AMEX – responded to VISA campaign, reduced transaction fees, sped up payments, more ads Finland May 2010 10
One-of-a-kind Competitor • Competitor redefines market • Wal-Mart – DEFENSE: Create new, non-overlapping business design • Target – unique product selection Finland May 2010 11
Customer Priority Shift – DEFENSE: Analyze proprietary information • Identify next customer shift – Coach leather goods – competes with Gucci – Went trendy, aggressive in-market testing » Customer interviews, in-store product tests – DEFENSE: Market experiments • Capital One – 65, 000 experiments annually – Identify ever-smaller customer segments for credit cards Finland May 2010 12
New Project Failure • Edsel – DEFENSE: Initial analysis • Best defense – DEFENSE: Smart sequencing • Do better-controllable projects first – Applied Materials – chip-making – DEFENSE: Develop excess options • Improve odds of eventual success – Toyota – hybrid: proliferation of Prius options – DEFENSE: Stepping-stone method • Create series of projects – Toyota – rolling out Prius Finland May 2010 13
COSO Committee of Sponsoring Organizations Treadway Committee – 1990 s Smiechewicz [2001] • Assign responsibility – Board of directors • Establish organization’s risk appetite • establish audit & risk management policies – Executives assume ownership • Policies express position on integrity, ethics • Responsibilities for insurance, auditing, loan review, credit, legal compliance, quality, security • Common language – Risk definitions specific to organization • Value-adding framework Finland May 2010 14
COSO Integrated Framework 2004 Levinsohn [2004]; Bowling & Rieger [2005] • Internal environment – describe domain • Objective setting – objectives consistent with mission, risk appetite • Event identification – risks/opportunities • Risk assessment - analysis • Risk response – based on risk tolerance & appetite • Control activities • Information & communication – to responsible people • Monitoring Finland May 2010 15
Risk Management Tools • Simulation (Beneda [2005]) – Monte Carlo – Crystal Ball • Multiple criteria analysis – Tradeoffs between risk & return • Balanced Scorecard – Organizational performance measurement Finland May 2010 16
ERM Software Rhoden [2006] Penny [2002] • Algorithmics Incorporated – ERM software, global financial institutions Jane’s Defence Industry [2005] • Strategic Thought – Active Risk Manager – defence industry Rhoden [2006] • Q 5 AIMS – From Q 5 Systems Ltd – Safety audit & corrective action tracking – Mobile devices, Web-link • Preceptor – Learning management system – Regulatory compliance, technical training • Picketdyna. Q – Workplace audit & assessment management – Regulatory references built in Finland May 2010 17
SIMULATION • Crystal Ball – Spreadsheet add-in – Value at Risk (Va. R) • Distribution of expected value at specified probability level • >3. 42 @ 0. 95 Finland May 2010 18
Spreadsheet Finland May 2010 19
Stochastic Elements these PRO FORMA models include a number of inherently STOCHASTIC elements – costs are really guesses • can base variance on subjective estimates • for repetitive operations, collect data – revenues are even more uncertain – discount rates in NPV uncertain Finland May 2010 20
Net Present Value where n = number of time periods in analysis ini = revenues in period i outi = cash outflow in period i r = discount rate i = END of time period Finland May 2010 21
EXCEL RN generation • Options – Analysis Tools – Random Number Generation » Output Range » Number of Variables » Number of Random Numbers » Distribution » Parameters » Random Seed Finland May 2010 22
Sharpe Ratio • Consider variance of stock as measure of risk – Tradeoff between mean and variance – Efficient investment opportunities 7 6 5 4 mean 3 var 2 1 0 0 1 2 3 Finland May 2010 4 5 6 23
Simulation studies involving the Sharpe ratio • Opdyke – Journal of Asset Management [2008] 8: 5, 308 -336 – Simulated to reflect autocorrelation of distributions • Yu et al. – Journal of Asset Management [2007] 8: 2, 133 -145 – Value-at-risk = max expected loss over a given time period at a given confidence level – Simulation showed simply using Sharpe ratio insufficient – need to reflect covariance • Chen & Estes – Journal of Financial Planning [2007] 20: 2, 56 -59 – Dollar-cost averaging for 401 k contributions – Simulated different strategies for contributions, allocation ratios, growth targets as decision variables • Boscaljon & Sun – Journal of Financial Service Professionals [2006] 60: 5, 60 -65 – Value-at-risk & return-at-risk more conservative than variance – Simulated all 3 Finland May 2010 24
Simulation studies involving Black-Scholes model • Alam – Journal of Economics & Finance [1992] 16: 3, 1 -20 • Figlewski et al. – Financial Analysts Journal [1993] 49: 4, 46 -56 • Barraquand & Martineau – Journal of Financial & Quantitative Analysis [1995] 30: 3, 383 -405 • Frey – Finance & Stochastics [2000] 4: 2, 161 -187 • Gopal et al. – Decision Sciences [2005] 36: 3, 397 -425 • Fink & Fink – Journal of Applied Finance [2006] 16: 2, 92 -105 Finland May 2010 25
Black-Scholes Option Pricing • Model to value options Price of call = Prob{x<d 1}*S – Prob{x<d 2}*E*e-r. T where S = price of stock E = exercise price r = risk-free interest rate T = time to maturity (years) Finland May 2010 26
Estimation of specification error biases – Black-Scholes & Cox-Ross models Alam, Journal of Economics & Finance, Fall 1992, 16: 3, 1 -20 • Black-Scholes – assumes constant variance of returns – Tends to underprice options at-the-money, overprices at extremes (“u-shaped”) • Cox-Ross – Variance changes with stock price – Analytically intractable Finland May 2010 27
Evaluating Performance of Protective Put Strategy Figlewski et al. , Financial Analysts Journal, Jul/Aug 1993, 49: 4, 46 -56 • Having put in place protects portfolio from loss below strike price • Simulated 3 put strategies: – Fixed strike price – Strike price a fixed % below asset price – Upward ratcheting policy • Ignores buying, selling, settlement costs (taxes) • Cost of put strategy is path dependent, thus only cost effective if expect high volatility in market Finland May 2010 28
Numerical Valuation Barraquand & Martineau, Journal of Financial & Quantitative Analysis, Sep 1995, 30: 3, 383 -405 • Cox-Ross does well for one asset, but computational demands increase exponentially • Closed form solution unfound • Monte-Carlo only tractable method Finland May 2010 29
Advanced Option Pricing Fink & Fink, Journal of Applied Finance, Fall/Winter 2006, 16: 2, 92 -105 • Foreign currency options have volatility smiles (“ushaped”) • Equity options have volatility skews (higher volatility for lower strike prices) • Bates model uses mean reversion for volatility estimates • Simulated Black-Scholes, Merton & Heston, Bates – Bates won easily – Black Scholes inflexible (Merton & Heston better here) Finland May 2010 30
More efficient super-hedging Frey, Finance & Stochastics, 2000, 4: 2, 161 -187 • Add descriptive, predictive power by allowing variation of volatility estimate • Hedge what you intend to hedge – Minimize transactions costs • Probabilistic argument Finland May 2010 31
Online Auction Risk Gopal et al. , Decision Sciences, Aug 2005, 36: 3, 397 -425 • Buyer’s risk – loser’s lament (bid too low & lose; bid too high & pay too much) • Seller’s risk – accept too low • Simulation used to estimate volatility • Searches through combinations of strike price & option price Finland May 2010 32
Financial Simulations • a very rich field for simulation – high degrees of uncertainty in cash flows • SPREADSHEETS for the most-part Finland May 2010 33
Iceland heating pipes Mean Lognormal (30. 76, 38. 61) – offset 30 MONTH Seasonal Differential from Mean Apr 3. 604167 May 10. 45833 Jun 72. 3125 Jul 46. 5 Aug -24. 6458 Sep 1. 875 Oct 29. 0625 Nov 22. 0833 Dec -27. 8958 Jan -15. 375 Feb -26. 5208 Finland May 2010 34
Supply Chain Simulation Produce to Forecast Finland May 2010 35
Supply Chain Simulation Produce to ROP/Q Q 30 Q 40 Q 50 AVG STOCKOUTS Q 60 To forecast – 0 to 643, mean 50 ROP 30 468 495 440 393 ROP 40 421 366 398 352 ROP 50 377 324 287 313 ROP 60 334 283 249 223 AVG HOLD To forecast – 81 to 559, mean 253 ROP 30 39 38 45 51 ROP 40 43 51 49 56 ROP 50 47 55 63 61 ROP 60 52 61 68 76 AVG SALES To forecast – 452 to 1281, mean 1032 ROP 30 612 585 640 687 ROP 40 658 714 682 728 ROP 50 703 756 793 767 ROP 60 746 797 831 857 May 2010 Finland 36
Monte Carlo Simulation Quoted price Exchange distribution Produc Organizati t failure onal failure China 0. 82 No(1. 3, . 2) 0. 10 0. 15 0. 05 2. 13 Taiwan 1. 36 No(1. 03, . 02) 0. 01 0. 10 1. 81 Vietnam 0. 85 No(1. 1, . 1) 0. 15 0. 25 0. 05 2. 51 Germany 3. 20 No(1. 05, . 02) 0. 01 0. 02 0. 01 3. 43 Alabama 2. 05 1 0. 03 0. 20 0. 03 2. 78 Finland May 2010 Political failure Expected price 37
China vendor price distribution Finland May 2010 38
Taiwan vendor price distribution Finland May 2010 39
Simulation Output Mean cost Min cost Prob{failure} Prob{low} China 2. 06 0. 54 0. 253 0. 406 Taiwan 1. 84 1. 30 0. 123 0. 103 Vietnam 2. 60 0. 58 0. 410 0. 479 Germany 3. 43 3. 14 0. 040 0. 003 Alabama 2. 05 0. 254 0. 009 Finland May 2010 40
MCDM j alternatives, I criteria weights, scores Finland May 2010 41
MCDM Weights Criteria Base 100 Base 10 Best (100) Worst (10) Average Quality 100 60 0. 2299 0. 2308 0. 23 Experience 90 55 0. 2069 0. 2115 0. 21 Cost 85 50 0. 1954 0. 1923 0. 19 Flexibility 60 40 0. 1379 0. 1538 0. 14 Technical 50 30 0. 1149 0. 1154 0. 11 Exchange 30 15 0. 0690 0. 0577 0. 06 Capital 20 10 0. 0460 0. 0385 0. 06 435 260 Finland May 2010 42
Scores Quality Experience China Problems 2 years Taiwan High Vietnam Cost Flexibility Technical Exchange Capital 0. 82 High Average High Weak 17 years 1. 36 High Moderate High Concerns 1 year 0. 85 Low Moderate Weak Germany High 5 years 3. 20 Low High Moderate High Alabama good 7 years 2. 05 Low High None Average China 0. 20 0. 30 1. 00 0. 60 0. 00 0. 20 Taiwan 1. 00 0. 50 1. 00 Vietnam 0. 40 0. 10 0. 95 0. 20 0. 50 0. 20 Germany 1. 00 0. 70 0. 00 0. 20 1. 00 0. 50 1. 00 Alabama 0. 70 0. 90 0. 30 0. 20 1. 00 0. 50 Finland May 2010 43
Values Criteria Weights CHINA TAIWAN VIETNAM GERMANY ALABAMA Quality 0. 23 0. 20 1. 00 0. 40 1. 00 0. 70 Experience 0. 21 0. 30 1. 00 0. 10 0. 70 0. 90 Cost 0. 19 1. 00 0. 50 0. 95 0. 00 0. 30 Flexibility 0. 14 1. 00 0. 20 Technical 0. 11 0. 60 1. 00 0. 20 1. 00 Exchange 0. 06 0. 00 0. 50 1. 00 Capital 0. 06 0. 20 1. 00 0. 50 Score 0. 52 0. 88 0. 39 0. 61 0. 64 Rank 4 1 5 3 2 Finland May 2010 44
Balanced Scorecard Perspectives Goals Measures Financial Survive Succeed Prosper Cash flow Sales, growth, income Increase in Market share, ROI Customer New products Responsive supply Preferred suppliers Customer partnerships % sales new products On-time delivery Share of key accounts’ purchases # Cooperative engineering efforts Internal business Technology capability Manufacturing experience Design productivity New product innovation Benchmark vs. competition Cycle time, unit cost, yield Engineering efficiency Planned vs. actual schedule Innovation & learning Technology leadership Manufacturing learning Product focus Time to market Time to develop next generation Process time to maturity % products yielding 80% sales New product innovation vs. competition Finland May 2010 45
Conclusions • Outsourcing provides competitive access – Broader opportunities • Demonstrate 3 tools – Monte Carlo simulation • Evaluate probabilistic elements – MCDM • Consider multiple criteria • Select vendor by decision maker preference – Balanced Scorecard • Measure effectiveness of selected vendor Finland May 2010 46
ERM Research • • Mostly descriptive, frameworks SURVEY – Lynch-Bell [2002] surveyed 52 companies • Examined practices of governance, strategy, processes, technology, functions, culture – Milladge [2005]; Gates [2006] surveyed 271 members of the Conference Board • Skelton & Thamhain [2003]; Thamhain [2004] – 3 year field study R&D product development – Suggest look-ahead simulation, rapid prototyping to anticipate problems • Beasley et al. [2005] – Gathered data on 123 organizations, found ERM implementation positively related to: • • • Chief risk officer presence Board independence Top management support Big Four auditor presence Entity size Banking, Education, Insurance Finland May 2010 47
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