Transcript ASTIN`s Next Greatest Contributions

ASTIN’s Next Greatest Contributions
Stephen P. D’Arcy, Ph. D., FCAS
Professor of Finance
University of Illinois
ASTIN 2007
Orlando, Florida
Objective
• Provide a presentation to facilitate valuable
research on risk
– Identify potential technical tools that could be
productively applied to risk analysis
– List critical practical problems in need of
additional research
– Encourage researchers to apply their skills in these
areas
Short Version
• Tools
– Data mining and predictive modeling
– Neuroscience
• Neuroeconomics
• Neurofinance, behavioral finance
• Key practical problems
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Enterprise Risk Management
Unified theory of risk
Risk metric
Extreme event probabilities
Data Mining and Predictive
Modeling
• Finding patterns in data that were not
previously recognized
• Current applications
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Risk classification
Ratemaking
Credit scoring
Fraud detection
• Next step, apply to loss reserving
Loss Reserving
• Need to move beyond the Chain Ladder Method
• Bring predictive modeling approach to reserving
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Technology now allows transactional data analysis
Analyze individual claim histories
Determine correlations across line, lines of business
No longer have to work with aggregate data
• Better approach to loss reserve models
– Systematic, statistically driven methodology
– Consistent probabilistic models of ultimate losses,
case reserves and paid loss processes akin to interest
rate and equity return models of finance
U t , Ct , Pt
Loss Reserving (2)
• Economic value of loss reserves
• Reserve ranges
– Standard actuarial approach
– Communicated effectively to our publics
Neuroscience of Risk
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How are decisions relating to risk made?
Chemistry of decision making
Effect of framing
Impact of recent events
Cascade behavior
What factors improve decisions?
Applications of Neuroscience to
Insurance
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Optimal policy design
Sales process
Pricing
Default options
Claim negotiations
Relationship between risk taking behavior and
credit scoring (Brockett, et al)
The Problem With “Risk Management”
• Risk Management
– Developed in 1960s
– Focus was on pure risk (insurable, hazard)
• Financial Risk Management
– Developed independently in 1980s
– Value-at-Risk – measure of certain percentile loss
• Asset Liability Management
– Impact of interest rate changes on surplus
– Duration and convexity – at least two sided metrics
• Enterprise Risk Management
– Incorporates all risks facing an organization
– Name suggests focus still on managing downside risk
Need for New Emphasis
(and Perhaps a New Name)
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ERM is not just managing downside risk
More on the lines of risk-return tradeoff
Incorporate portfolio theory
Combine risk reduction (insuring, traditional
risk management) with investing for expected
gain
• Need consistent approach for addressing both
aspects of financial decision making
Unified Theory of Risk
• Unified Theory in Physics – as yet unattained
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Gravitation
Electromagnetism
Strong force (holds atomic nuclei together)
Weak force (responsible for slow nuclear processes)
• Unified Theory of Risk
– Speculative risk
– Pure risk
• Expand on Friedman-Savage utility function
– Concave below current wealth level
– Convex above
Current State of Corporate Finance
• For investment decisions
– Net present value – invest if positive
– Risk adjusted cost of capital
• For reducing risk
– Insuring
– Hedging
– Options to abandon or convert
• If considered by themselves, risk reducing
steps would often have a negative NPV
Problems with Risk Measures Used
for Adjusted Cost of Capital
• Variance or standard deviation of returns
– Treats upside deviation the same as downside
– Squares the difference between observation and
expected value
• Semi-variance and semi-standard deviation
– Still squares the difference between observation and
expected value
• Portfolio theory
– Linear correlation issues
Need an Effective Risk Metric
• Metric will be multi-dimensional
– Return (mean, conditional expected)
– Variability
• Overall
• Downside
– Probability of particular negative outcome
• Amount willing to lose
• Risk of ruin (insolvency)
• Risk of meltdown (adverse external impact)
– Consider qualitative effects (especially for
operational risk)
Need for Different Risk Metrics –
Corporation
• For a corporation as a whole and rating agencies
– Maximum loss would be the stockholders’ equity
– Size of any loss larger than that is irrelevant
– Portfolio effect is important
• For capital allocation within an organization
– Need to consider spillover effects
– Loss in one division could consume capital from rest
of organization
• Mango’s Capital Hotel example
• Rent depends on likelihood of needing capital and amount
Need for Different Risk Metrics –
Regulators
• Need to consider all possible losses
• What impact would a loss have on external
parties
– Counterparties – Long Term Capital Management
– Policyholders
– Financial market structure
• Loss of confidence
• Elimination of segment of market
– Savings and Loan industry
– Subprime lenders
– Hedge funds
Extreme Event Probabilities
• Catastrophic losses impact many areas
simultaneously
– Monetary loss itself
– Impact on financial markets
• Interest rates
• Equity values
• Foreign exchange rates
– Can alter market structure
• Complex systems
• Correlation
– Not a constant
– Varies over time
– Varies based on position on probability distribution
Copulas
• Recognize that correlation varies
across a distribution
• Separates joint distribution into
– Marginal distribution of the individual
variables
– Interdependency of the probabilities
– Venter (2002)
• Many standard copulas
• Reality may be more complex than
the mathematics
Black-Scholes Option Pricing Model
Pc  PsN ( d1)  Xert N ( d 2)
d 1  [ln( P s / X )  ( r  
d 2  d 1   t 1/ 2
Pc
Ps
X
r
t
σ
N
= Price of a call option
= Current price of the asset
= Exercise price
= Risk free interest rate
= Time to expiration of the option
= Standard deviation of returns
= Normal distribution function
2
/ 2 ) t ] / t 1/ 2
Black-Scholes Problems
• Based on lognormal distribution of prices
• Fine for at-the-money options
• Inappropriate for far in- or out-of-themoney options
Extreme Event Probabilities (2)
• Regime switching approach
– Hardy – Equity returns
• Nassim Nicholas Taleb’s work
– Fooled by Randomness: The Hidden Role of Chance in the
Markets and Life
– The Black Swan: The Impact of the Highly Improbable
Some Other Critical Issues
• What is the value of liquidity?
• Much of finance is based on arbitrage free
arguments
– What impact do incomplete markets create?
– How do we place a value on non-hedgeable risks
• Capital markets for insurance risks
Need for Actuaries and Financial
Economists to Work Together on
Next Breakthroughs
Both Actuaries and Financial Economists:
Are mathematically inclined
Address monetary issues
Incorporate risk into calculations
Use specialized languages
Each can learn from each other
What Do You Think Will be
ASTIN’s Next Greatest
Contributions?