Introduction Risk Management

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Introduction Risk Managment Finance for Exchange Witek ten Hove

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This presentation belongs to the course "Finance for Exchange" at HAN University of Applied Science, Arnhem (The Netherlands).

Transcript of Introduction Risk Management

Page 1: Introduction Risk Management

Introduction Risk Managment

Finance for Exchange

Witek ten Hove

Page 2: Introduction Risk Management

Introduction Risk Management

Risk and quality Risk analysis Risk reporting Risk and behavior Risk instruments

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Risk and quality

Decrease uncertainty for stakeholders: Suppliers of capital (cash flows) Customers (product) Suppliers (sales and payments) Employees (career and reward)

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Alea Iacta Est

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Probability of loss within one month

Price- {combinations}

2 - {(1,1)} 3 - {(1,2), (2,1)} 4 - {(1,3), (2,2), (3,1)} 5 - {(1,4), (2,3), (3,2), (4,1)} 6 - {(1,5), (2,4), (3,3), (4,2), (5,1)} 7 - {(1,6), (2,5), (3,4), (4,3), (5,2),

(6,1)} 8 - {(2,6), (3,5), (4,4), (5,3), (6,2)} 9 - {(3,6), (4,5), (5,4), (6,3)} 10 - {(4,6), (5,5), (6,4)} 11 - {(5,6), (6,5)} 12 - {(6,6)}

Total: 36 combinations

Source: http://www.futureaccountant.com/theory-of-expectation-random-variable/problems-solutions/throwing-rolling-dice.php

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Probability of default within two months

Result- {combinations}

-/- 200 {(1,1)}

-/- 100 {(1,2), (2,1)}

0 {(1,3), (2,2), (3,1)}

100 {(1,4), (2,3), (3,2), (4,1)}

200 {(1,5), (2,4), (3,3), (4,2), (5,1)}

300 {(1,6), (2,5), (3,4), (4,3), (5,2), (6,1)}

400 {(2,6), (3,5), (4,4), (5,3), (6,2)}

500 {(3,6), (4,5), (5,4), (6,3)}

600 {(4,6), (5,5), (6,4)}

700 {(5,6), (6,5)}

800 {(6,6)}

Totaal: 36 combinations

Month 1   Month 2 Total

ResultProbability and Result Probability Result Probability

-200 1/36   default 36/36 -200 1/36

or            

-100 1/18   -200 1/36 -300 1/648

  -100 1/18 -200 1/324

or            

0 1/12   -200 1/36 -200 1/432

Total   3,5%

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Probability of default within two months with interest jump

Result- {combinations}

-/- 600 {(1,1)}

-/- 500 {(1,2), (2,1)}

-/- 400 {(1,3), (2,2), (3,1)}

-/- 300 {(1,4), (2,3), (3,2), (4,1)}

-/- 200 {(1,5), (2,4), (3,3), (4,2), (5,1)}

-/- 100 {(1,6), (2,5), (3,4), (4,3), (5,2), (6,1)}

0 {(2,6), (3,5), (4,4), (5,3), (6,2)}

100 {(3,6), (4,5), (5,4), (6,3)}

200 {(4,6), (5,5), (6,4)}

300 {(5,6), (6,5)}

400 {(6,6)}

Totaal: 36 combinations

Month 1   Month 2 TotalResult Probability and Result Probability Result Probability

-600 1/36   1 -600 1/36 or            

-500 1/18   1 -500 1/18 or            

-400 1/12   1 -400 1/12 or            

-300 1/9   1 -300 1/12 or            

-200 5/36   1 -200 1/12 Totaal 41,7%      

or            -100 1/6   -600 1/36 -700 1/216

  -500 1/18 -600 1/108   -400 1/12 -500 1/72   -300 1/9 -400 1/54   -200 5/36 -300 5/216   -100 1/6 -200 1/36 or            

0 5/36   -600 1/36 -600 5/1296   -500 1/18 -500 5/648   -400 1/12 -400 5/432   -300 1/9 -300 5/324   -200 5/36 -200 25/1296or            

100 5/36   -600 1/36 -500 5/1296   -500 1/18 -400 5/648   -400 1/12 -300 5/432   -300 1/9 -200 5/324 or            

200 5/36   -600 1/36 -400 5/1296   -500 1/18 -300 5/648   -400 1/12 -200 5/432 or            

300 5/36   -600 1/36 -300 5/1296   -500 1/18 -200 5/648 or            

400 5/36   -600 1/36 -200 5/1296Total       56,6%

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Alea Iacta Est?

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Normal distribution

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Normal distribution

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Project risk

Simple scenario Extended scenario Monte Carlo simulation

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Simple scenario analysis

Example: 5 variables / 3 scenarios

Risk analysis ScenarioPrice per unit Negative Expected Positive

Selling price 8,00 10,00 12,00

Cost of raw materials 8,00 6,00 4,00

Cost of energy 2,00 1,50 1,00

Cost of labor 3,00 2,00 1,00

Result (5,00) 0,50 6,00

Units sold 1.000 2.000 3.000

Total result (5.000) 1.000 18.000

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Extended scenario analysis

Example: 5 variables / 3 scenarios = 35 = 243 possible results

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Monte Carlo Simulation

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Known Knowns, Known Unknowns, Unknown Unknowns

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Rumsfeld = Einstein

Known Knowns, Known Unknowns, Unknown Unknowns

="Not everything that counts can be counted, and

not everything that can be counted counts." (Sign hanging in Einstein's office at Princeton)

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Black Swan events

0%

5%

10%

15%

20%

25%

30%

35%

40%

We

ek

ly g

row

th

Week

Growth Rate of a Christmas Turkey

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Risk

Risk = Likelihood x Damage

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Risk reporting

Probability classes Damage classes Risk scores Risk matrix

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Example

Probability classes

Probability classes

Score Probability (%) Description Qualification

1 10% Less than 1 x per 3 years Very unlikely

2 30% between 1 - 2 x per 3 years Unlikely

3 50% between 2 - 3 x per 3 years Possible

4 70% between 3 - 4 x per 3 years Likely

5 90% More than 4 x per 3 years Very likely

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Example

Damage classes

Damage classes

Score Damage Damage Qualification

1 Less than 100.000 EUR < 1% of equity Very low

2 between 100.000 - 400.000 EUR < 4% of equity Low

3 between 400.000 - 800.000 EUR < 8% of equity Serious

4 between 800.000 - 1.500.000 EUR < 15% of equity High

5 More than 1.500.000 EUR > 15% of equity Very high

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Example

Risk scores

Event Effect Probability Damage Risk

External

Lower purchasing power Less demand, lower selling prices, higher bad debt levels

1 5 5

Inflation Higher raw material prices, labor costs, energy prices, transportation prices, interest costs

1 4 4

Shortage raw materials Higher raw material prices 2 3 6

Shortage labor Higher labor costs 1 1 1

Logistics interruption No supplies, no distribution 1 5 5

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Example Risk matrix

High

Risk

Low R

isk

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Risk

When the probability of an event is 100%, is it still risk?

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Risico and behavior

After assessing the risks, how do you proceed?

Research Tversky / Kahneman (1979) Own experiment

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Survey students period 1 - 2010/11

Situation 1:

100% certainty 3.000 EUR profit

vs

80% certainty of 4.000 and 20% certainty of zero profit

Situation 2:

100% certainty 3.000 EUR loss

vs

80% certainty of 4.000 and 20% certainty of zero loss

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Results

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Risk instruments

Legal:

Contracts

SLAs

Etc.

Economical:

Financial instruments (derivatives, insurance)

Internal control instruments

Etc.

Management:

Quality systems

HRM instruments: competencies, experience, motivation

Etc.


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