ERM David L. Olson, University of NebraskaLincoln Desheng Wu, University of Reykjavik, University of

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ERMDavid L. Olson, University of
Nebraska-LincolnDesheng Wu, University of
Reykjavik, University of Toronto

• Enterprise Risk Management
• Not just insurance, auditing, risk analysis
• A philosophy A way of business

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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

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DIFFERENCES
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Risk Business

• Taking risk is fundamental to doing business
• Insurance
• Lloyds 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

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Types of RiskStroh 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

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Another viewSlywotzky 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

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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• Outdated manufacturing process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 didnt Nokia, Samsung entered

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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

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One-of-a-kind Competitor

• Competitor redefines market
• Wal-Mart
• DEFENSE Create new, non-overlapping business
  design
• Target unique product selection

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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

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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

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COSOCommittee of Sponsoring OrganizationsTreadwa
y Committee 1990sSmiechewicz 2001

• Assign responsibility
• Board of directors
• Establish organizations 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

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COSO Integrated Framework 2004Levinsohn 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

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Risk Management Tools

• Simulation (Beneda 2005)
• Monte Carlo Crystal Ball
• Multiple criteria analysis
• Tradeoffs between risk return
• Balanced Scorecard
• Organizational performance measurement

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ERM SoftwareRhoden 2006

• Penny 2002
• Algorithmics Incorporated ERM software, global
  financial institutions
• Janes Defence Industry 2005
• Strategic Thought Active Risk Manager defence
  industry
• Rhoden 2006
• Q5AIMS
• From Q5 Systems Ltd
• Safety audit corrective action tracking
• Mobile devices, Web-link
• Preceptor
• Learning management system
• Regulatory compliance, technical training
• PicketdynaQ
• Workplace audit assessment management
• Regulatory references built in

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SIMULATION

• Crystal Ball
• Spreadsheet add-in
• Value at Risk (VaR)
• Distribution of expected value at specified
  probability level
• gt3.42 _at_ 0.95

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Spreadsheet
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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

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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

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EXCEL RN generation

• Options
• Analysis Tools
• Random Number Generation
• Output Range
• Number of Variables
• Number of Random Numbers
• Distribution
• Parameters
• Random Seed

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Sharpe Ratio

• Consider variance of stock as measure of risk
• Tradeoff between mean and variance
• Efficient investment opportunities

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Simulation studies involving the Sharpe ratio

• Opdyke Journal of Asset Management 2008 85,
  308-336
• Simulated to reflect autocorrelation of
  distributions
• Yu et al. Journal of Asset Management 2007
  82, 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 202, 56-59
• Dollar-cost averaging for 401k contributions
• Simulated different strategies for contributions,
  allocation ratios, growth targets as decision
  variables
• Boscaljon Sun Journal of Financial Service
  Professionals 2006 605, 60-65
• Value-at-risk return-at-risk more conservative
  than variance
• Simulated all 3

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Simulation studies involving Black-Scholes model

• Alam Journal of Economics Finance 1992
  163, 1-20
• Figlewski et al. Financial Analysts Journal
  1993 494, 46-56
• Barraquand Martineau Journal of Financial
  Quantitative Analysis 1995 303, 383-405
• Frey Finance Stochastics 2000 42, 161-187
• Gopal et al. Decision Sciences 2005 363,
  397-425
• Fink Fink Journal of Applied Finance 2006
  162, 92-105

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Black-Scholes Option Pricing

• Model to value options
• Price of call Probxltd1S Probxltd2Ee-rT
• where S price of stock
• E exercise price
• r risk-free interest rate
• T time to maturity (years)

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Estimation of specification error biases
Black-Scholes Cox-Ross models

• Alam, Journal of Economics Finance, Fall 1992,
  163, 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

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Evaluating Performance of Protective Put Strategy

• Figlewski et al., Financial Analysts Journal,
  Jul/Aug 1993, 494, 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

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Numerical Valuation

• Barraquand Martineau, Journal of Financial
  Quantitative Analysis, Sep 1995, 303, 383-405
• Cox-Ross does well for one asset, but
  computational demands increase exponentially
• Closed form solution unfound
• Monte-Carlo only tractable method

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Advanced Option Pricing

• Fink Fink, Journal of Applied Finance,
  Fall/Winter 2006, 162, 92-105
• Foreign currency options have volatility smiles
  (u-shaped)
• 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)

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More efficient super-hedging

• Frey, Finance Stochastics, 2000, 42, 161-187
• Add descriptive, predictive power by allowing
  variation of volatility estimate
• Hedge what you intend to hedge
• Minimize transactions costs
• Probabilistic argument

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Online Auction Risk

• Gopal et al., Decision Sciences, Aug 2005, 363,
  397-425
• Buyers risk losers lament (bid too low
  lose bid too high pay too much)
• Sellers risk accept too low
• Simulation used to estimate volatility
• Searches through combinations of strike price
  option price

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Financial Simulations

• a very rich field for simulation
• high degrees of uncertainty in cash flows
• SPREADSHEETS for the most-part

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Monte Carlo Simulation
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China vendor price distribution
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Taiwan vendor price distribution
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Simulation Output
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MCDM j alternatives, I criteriaweights, scores
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MCDM Weights
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Scores
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Values
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Balanced Scorecard
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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

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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 RD 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