1. Prof Robin Matthews March 16 2017 ADAPTED May 12 2017 London
DBA Presentation
Prof Robin Matthews March ADAPTED May London
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2. BRIEF SUMMARY
The economist Frank Knight distinguished risk and uncertainty by saying that it was possible to attach probabilities (perhaps only subjective probabilities) to risk, whereas uncertainty referred to situations that was so unexpected that calculation of any kind (including probability calculations) was impossible. He associated uncertainty with the completely unexpected events that occur in our lives and beset us. John Maynard Keynes took the same view. Events like the fall in the Berlin wall, the Arab Spring, the financial crisis of are examples of uncertainty. And there are many micro examples that affect our lives constantly; death in the family, personal loss through theft or accident, sudden illness and so. And the macro events stemming from uncertainty affect whole societies and the effect individuals. So uncertainty is part of life.
The examples I’ve given you are examples of what you might call bad luck, or misfortune, but there are many examples of uncertainty that bring forth opportunities; windfall gain, sudden turn for the better, fortuitous events that benefited such as some of the macro events given above confer wins as well as losses. What might be thought of as bad luck may turn out to be all for the good. What the future holds is always unknown before the event.
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3. It is easy to rationalise the unexpected after the event and attribute causality to what happened and say ” We should have expected this or that.” But it’s just ex post rationalisation. The famous politician was once asked what worried him most; “ Events, dear boy”, he said.
Slide 5 distinguishes expected value and expected utility; the impact of change depends on both its probability and the expected utility (positive or negative associated with the change.
E(V), expected value values events measured by the expected money value of alternative outcomes V(a) and V(b) weighted by their respective probabilities. Expected value does the same sort of calculation but U(a) and U(b) refer to some index of utility or happiness. What both formulations emphasise is that there are two forces affecting the impact of outcomes 1. The impact on money values, or utility and 2. The probability of their occurrence. Events such as major disasters (tsunamis, global extinctions) may have a low probability but they have an enormous negative impact.
Having distinguished risk and uncertainty, I began by relating risk to the enneagram mandala, slide 6 and in a linear way in slide 7. Risk enters as we move between thought and action as shown in the red line in slide 6.
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4. It is often assumed that probability is normally distributed (risk)
It is often assumed that probability is normally distributed (risk). This is so in most financial analysis. But not all events have normal probability distributions. Extreme events like earthquakes or wars or financial meltdowns often have what are called fat tailed distributions or Black Swan distributions (slide 21) ; they are events that happen time and time again al though they have a very low probability as compared to milder events.
The remainder of the lecture focused on financial risk stemming from the high connectivity of the financial system with the non-financial sector, ordinary businesses that continually borrow, payback and refinance their activities; slides 12 and 13. Slide 14 illustrates the impact of a shock to a bank, that reduces its assets and forces it to call in loans or refused to refinance existing loans when they come up for renewal.
Slide 15 is a picture of the inverted pyramid created by too active securitisation.
Slides 16 to 18 illustrate the interconnectivity of the international financial system showing how shock to part of the system can spread throughout the whole, creating mayhem as in 2008.
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5. Risk and uncertainty Risk and the enneagram
Expected value and expected utility
E(v) = Pa V(a) + PbV(b)
E(U) = Pa U(a) + PbU(b)
Risk and Uncertainty
Risk associated with probability (subjective or frequentist)
Uncertainty with the unexpected
Sources of risk
Financial political technological ecological etc.
Black swans
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6. RISK GRAMMAR GRAMMAR GRAMMAR OUTER DYNAMICS 9 Evaluation, 8 reflection
1 vision,
intention
ADAPTATION
implementation 7
2 values
REALISATION
SEARCH
PAYOFFS 6
3 INNER DYNAMICS/
CAPABILITIES
choice commitment 5
4 alternative scenarios
GRAMMAR
RISK
GRAMMAR
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7. Search Choice CONCEPTUAL Implementation EVENTS Adaptation
strategic decision process
Search
Intentions, aspirations, vision of the future
imagining/analysing alternatives,
deciding according to
values norms and desired payoffs
Conceptual stage
Imagination/analysis
Algorithms
Mind sets
CONCEPTUAL
Choice
Commitment to chosen alternatives.
RISK AND UNCERTAINTY; from potential to actual
Dynamics ensure that intentions are never fully realised
Implementation
Implementation of chosen alternatives.
Monitoring events and comparing actual with desired outcomes.
EVENTS
Actual payoffs occur.
Algorithms for implementation; systems structures cultures architectures path dependence
Monitoring and control, algorithms comparing actual events to intentions.
Adaptation stage
Change evolution as elements of the meta model change
Adaptation
Adaptation to changes in outer dynamics, inner dynamics and grammar, or miscalculations,
unexpected events and disappointing payoffs.
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8. payoffs Outer dynamics grammar
Payoffs to
stakeholder groups
Tangible and
intangible
Assets
(including
Reputation)
payoffs
Competitors and
co-operators
Outer dynamics
Inner dynamics
Global macro conditions
grammar
Rules, laws, regulations, structures, architectures, routines; Mindsets, culture, norms, values, habits, moods; Intelligence rational and emotional; Formal and informal, Inner and outer; Hard and soft systems.
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9. payoffs Inner dynamics Outer
GRAMMAR
SYSTEM
STATE
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10. GLOBAL POSITIVE FEEDBACKS
FINANCIAL
REVOLUTION
Flexible exchange rates
Deregulation
New asset pricing models
TECHNOLOGICAL
Investment funds
Shorter product cycles
Pressure to reduce costs
Outsourcing
GLOBAL
DEMAND
FDI
Consumption
Investment
Asset prices
Sovereign wealth funds
Securitization
GLOBAL POSITIVE FEEDBACKS
1980 – 2006
(circa)
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11. Yin (dark) Yang(light) Eventually balance sheets recover
Current account deficits
financial deficits fallacy of composition
Bubble bursts
Asset prices ↓
Balance sheet
Recession
Deleveraging
Govt’s, Firms,
Households
Deficient demand
U ↑ G ↓
Contagion
Fiscal policy works
Risk aversion
Liquidity trap
Inflated asset prices
Hubris
New asset bubble
Contagion
Speculation, leveraging, securitization
Monetary policy works
Excess demand U↓ G↑
Govt’s, Firms,
Households
Increase demand
Eventually balance sheets recover
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15. The financial tower of Babel: 21ST century
CDO’s
CDC’s
CDW’S
SWF’S
SPV’’s
SPE’s
CONDUITS
IPO’s
PRIVATE EQUITY FUNDS
HEDGE FUNDS
DERIVATIVES/OPTIONS
SHADOW BANKING SYSTEM
REGULATED BANKING SYSTEM
CORPORATE BONDS
GOVERNMENT BONDS
LIQUID ASSETS
CASH
unregulated
regulated
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16. Haldane (2009)
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17. Haldane (2009)
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18. Haldane (2009)
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20. From
Bettis RA, Hitt MA The New Competitive Landscape.
Strategic Management Journal 16 : 7-19.
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21. Evolution and change distinction TYPES OF SYSTEM CHANGE
TTYPES OF ypest
Random
no pattern
Normal distribution
Bell shaped or approximately so
Fat tailed distributions
change on all scales possible; Black Swans
Deterministic
predictable iff imformation perfect
Chaotic
Deterministic but CDIC
Catastrophic
Singularity and great extinctions
Self ordered criticality
Attraction to tipping points; major (phase) transitions.
TYPES OF SYSTEM CHANGE
distinction
change
Evolution
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