Why it is important and why statistics is needed.

Transcription

1 Trial lecture on a chosen topic: Financial risk management: Why it is important and why statistics is needed. NTNU, Trondheim, Kjersti Aas Norsk Regnesentral What is risk? The term risk describes the probability of an undesirable event happening as a result of a present decision or of some future event. In life, we face multitudes of these risks. There are risks that we would readily take, while there are also those that we would try to avoid.. 2 1

2 Risk Management The worlds of business and finance are not much different from our lives when it comes to risk-taking. In any business venture, owners or shareholders are bound to face risks. Risk management refers to the entire process of identifying, analyzing, evaluating, and treating risks. Risk management has been described as one of the most important innovations of the 20 th century (Steinherr, 1998). 3 More and more important Risk came for the first time out on top as the major concern in Accenture s executive issues study in The global market for risk technology is estimated to be worth $5.9bn in

3 Financial risk Financial Risk relates to the volatility of unexpected outcome or movements in financial variables. An understanding of financial risk has become essential to survival in all business activity. Alan Greenspan (2003): Uncertainty is not just an important feature of the monetary policy landscape; it is the defining characteristic of that landscape. 5 Financial risk types One usually distinguish between the following three types of financial risk Market risk: The risk linked to fluctuations in interest rates, market prices and foreign exchange rates. Credit risk: The risk of losses resulting from failure by financial counterparties to meet their obligations. Operational risk: Losses caused by internal factors such as inadequate or ineffective internal processes and systems, or by external factors such as natural disasters and criminal acts. 6 3

4 Why manage financial risk? Historical lessons The banking crisis of the late 1980s and early 1990s. 8 4

5 Financial instruments The financial business has become more complex due to new financial instruments, e.g. Options Credit derivatives Guaranteed return investments This makes it more difficult than ever for banks, insurance companies, authorities and private investors to fully understand and evaluate their risk exposures. 9 New regulations Pressure from international changing regulatory environment. Three important new regulatory environments Basel II from January 1 st 2007 Solvency II planned from 2010 IFRS from April 1 st

6 Basel II Capital management requirements designed to ensure that a bank holds capital reserves appropriate to the risk the bank exposes itself to through its lending and investment practices. 11 Basel II Pillar 1: Separate capital charges for Credit risk Market risk Operational risk Pillar 2: The banks should assess the overall capital adequacy in relation to their risk profile and a strategy for maintaining their capital levels. Pillar 3: Banks should offer the public greater insight into their risk measures and other information relevant to risk management. 12 6

7 Solvency II Regulatory requirements for insurance firms The aim is to ensure the financial soundness of insurance undertakings, and in particular to ensure that they can survive difficult periods. Specifies the amount of capital the insurance company should hold against unforeseen events such as higher than expected claim levels unfavourable investment results 13 IFRS International Financial Reporting Standards in accountancy. Require statistically and mathematically sound valuation of derivatives and options. 14 7

8 Other reasons Regulators want a high level of capital in financial institutions to protect deposit holders and financial stability. Assessment of risk is the key element in the processes used by the rating agencies. It is widely believed that proper financial risk management can increase the value of a corporation and hence shareholder value Statistical methods and financial risk management 8

9 Why using statistical methods? Risk relates strongly to uncertainty and to the notion of randomness. Hence, quantitative methodology has become an increasingly important component of financial risk management. However, whereas much of traditional statistics concerns the average, the normal, and the expected, risk management has more to do with the extreme, the abnormal and the unexpected. 17 Risk measures Measuring a risk usually means summarising its distribution with a number known as a risk measure. Here, I will concentrate on three different measures: Standard deviation/volatility Value-at-Risk Expected Shortfall 18 9

10 Standard deviation The standard deviation of a probability distribution or random variable, is a measure of the spread of its values. The standard deviation is the far most used measure for financial risk. 19 Standard deviation (II) If the probability distribution is not symmetric, the standard deviation is not an appropriate risk measure. Both distributions below have mean equal to 832 and standard deviation equal to A B 20 10

11 Value-at-Risk (I) Financial legend has it that in the early 1990s, Dennis Weatherstone, chairman of the investment bank JP Morgan, demanded to see the bank's aggregated risk exposure at 4.15 each day. The type of report that Weatherstone received is now a common feature of financial institutions worldwide, and it entails calculating the firm's Value-at-Risk. Source: erisk.com 21 Value-at-Risk (II) The p% Value-at-Risk (VaR) corresponding to a financial variable is the value such that p% of the distribution of the variable is below this value. Probability density %-VaR Loss 22 11

12 VaR (II) VaR is not a coherent risk measure. VaR does not take the length of the tail into account. Both distributions below have VaR equal to A C 23 Expected Shortfall (I) The p% Expected Shortfall (ES) corresponding to a financial variable is the expected value of the variable given that the p% VaR is exceeded. Probability density % ES Loss 24 12

13 Expected Shortfall (II) ES is easy to understand. ES is always more conservative than VaR. ES is in most relevant cases a coherent risk measure. In my opinion, ES is still the best risk measure of all.' Risk management expert from Deutsche Bundesbank: 25 Applications 13

14 Applications Credit risk Banking credit portfolio Collateralised Debt Obligations (CDOs) Market risk Pension fund Commodity price risk Model for power prices Total risk Model for result before tax 27 Credit risk 14

15 Credit risk (I) 29 Credit risk (II) Credit risk is the far largest risk type for banks. Credit risk arises when counterparties are not able to fulfill their contractual obligations. The credit risk for a bank portfolio is typically dependent on the following quantities: The probability of default for each client The size of the loss given that a client defaults The correlation between the different clients in the portfolio

16 Basel II-model Basel II has specified a statistical model for the capital requirement for each client based on the quantities at the previous slide. One may also simulate the whole credit loss distribution for the bank based using the Basel II-model. 31 Credit Risk (III) 95% VaR 99% VaR 99.9% VaR 32 16

17 CDO The credit risk in a portfolio of debt obligations can be restructured and sold as so-called Collateralised Debt Obligations (CDOs). The risk of a CDO investment is directly related to the underlying portfolio of credit risk. If there are changes in any of the underlying quantities, the market value of a CDO may significantly change. 33 Credit derivatives Narvik and other towns in Norway had their municipal governments invested in CDO-type securities. The four communities may have lost as much as $64 million

18 Market risk Stock market risk (I) 36 18

19 Stock market risk (II) 37 Pension fund (I) Market risk is a consequence of the open positions of a corporation in the foreign exchange rate, interest rate and capital markets. For life insurance companies, market risk is the far largest risk type. A typical pension fund portfolio is invested in equities, government and other bonds, and real estate. The risk of the portfolio is dependent on the distributions of the different assets the correlations between the assets 38 19

20 Pension fund (II) Buffer interest rate guarantee loss Portfolio value Keywords: Non-normal distributions and copulae 39 Pension Fund (III) Huge loss of Irish pension fund in

21 Commodity price risk Commodity price risk For non-financial firms, commodity price risk often is one the largest risks. E.g. the players in the deregulated power markets need to make decisions in the presence of large uncertainties about future electricity prices. Realistic price models are needed for tasks such as production planning, portfolio optimization, derivatives pricing and risk management

22 Electricity prices Historical Nord Pool weekly spot prices Aggregated inflow to the Nordic water reservoirs Electricity prices ---- Historical price ---- Seasonal trend -----Seasonal trend+inflow Electricity prices have a clear seasonal trend. Inflow is an important factor. But there are price movements that cannot be explained by these factors alone! 44 22

23 Multi-factor Price Model Model the spot price S t as a product of four factors: On the log scale, the model is 45 Total risk: A model for the uncertainty in the financial result of a hydropower company 23

24 Total risk for a hydropower company Power price Operating revenues Weather Investments Production - operating expenses + financial income - financial expenses Interest rates loan portfolio = Result before tax 47 Result before tax CI CI Prognosis January 2006 January 2007 January 2008 January

25 Summary Summary An understanding of financial risk has become essential to survive in all business activity. Risk management has to do with the unexpected, the abnormal and the extreme. Statistical methodology is one of, if not the most important component of financial risk management