1. Risk analysis & modeling using Excel & VBA
Dr Jan Kaczmarzyk, FAB 2017

2. Organisational matters
Consultations are planned: every Monday A (08:00 – 09:30, Room 603D) and every Wednesday B (19:00-20:30, Room 603D).
The total 100% to get a pass consists of the exam (65%) and the group project (35%). You get a pass with 50% (50% - 3.0, 60% and so on).
The exam is planned on penultimate classes (June). The project will be done completely during mid-term classes (be aware of an announcement).
The files presented during classes are available at
The program of the classes – the mysterious syllabus.

3. Organisational matters
Market risk analysis of actively managed investment portfolios using historical simulation.
Financial data acquiring and merging using Excel.
Volatility, threat and sensitivity measurement – the example of investment funds.
The quality of portfolio management – measurement techniques.
Market risk forecasting using Monte Carlo methods (basics)
The randomness of returns and market risk forecasting,
The market risk forecasting of investment funds,
The market risk forecasting of pension funds.
Corporate risk measurement and analysis using Monte Carlo methods (basics)
Elementary Excel & VBA programming techniques for risk analysing using Monte Carlo methods.
Financial models for corporate risk analysis.
Corporate risk analysis – the case of an investment project.

4. Organisational matters
CNTI Login details for Windows Excel 2013 in ENG.
Username: Student3
Password: Student!

5. 1. The theory of risk (just what you need)
Uncertainty is in fact awareness, a kind of feeling that suggests something different than you expect may happen. So, you buy a stock and you only know it may go up or down. Uncertainty is not quantified in any way.
Risk is very close to uncertainty but instead of uncertainty – risk is quantified. What should you know when buying a stock to accept risk rather than uncertainty? E.g. that there is 10% probability that the weekly change of the stock won’t exceed the -2.4%.
Sometimes it is indicated that information about risk is a result of risk quantification or risk categorisation. The result of categorisation is e.g. a statement that there is a low chance that the weekly change of the stock won’t exceed the -2.4%.

6. 1. The theory of risk (just what you need)
There are two general concepts of risk. The negative and neutral. The negative concept describes risk as a chance of loss. That’s the way the most people think about risk. E.g. You can’t crash your car and make it better. (So in terms of insurance we often use negative concept of risk) – Negative risk = only a threat. But, when it comes to buying a stock, the negative concept is inadequate. The neutral concept which describes risk as a possible profit or loss (chance or threat) seems to be much better. E.g. The stock may go down or up. The result of buying a stock may be worse or better than expected in the consequence. – Neutral risk = a chance or a threat.

7. 1. The theory of risk (just what you need)
Financial risk is every kind of risk which has financial consequences (both profits or losses, as the neutral concept suggests).
Financial risk covers: operational risk, market risk, credit risk, liquidity risk, legal risk and business risk (typically).
Market risk is a risk that is a result of prices changes on financial markets. Typically market risk consists of:
Stock price risk,
Exchange rate risk,
Commodity price risk,
Interest rate risk,
Real estate price risk, etc.

8. 1. The theory of risk (just what you need)
Sometimes we describe stock price risk (or any other financial instrument price risk) as total risk. Total risk consists then both of systemic and specific risk. E.g. you buy a stock (PEKAO) and you are able to notice that its price changes That’s obvious. Volatility is the symptom of total risk. You can check using simple statistical tools how much the changes of the price are explained by the changes of main index (WIG). This is how you find out the systemic part. The „rest” is the specific part.
Risk management process consists of:
risk identification,
risk quantification
and risk control.
risk analysis

9. 2. Risk Quantification
Risk quantification methods for market risk include: Historical simulation – we base on historical (empirical) prices. Historical prices are the source of the historical (empirical) probability distribution of price changes (return rates). Historical simulation is very effective, but it is very limited at the same time. E.g. weekly data gives the information about risk in scale of a week, monthly data – in scale of a month. The longer the forecasting period is the less points of available data you have. Variance-covariance method – we base on assumption that financial instruments price changes can be described using normal probability distribution instead of historical (empirical) probability distribution. This methods allow forecasting of risk for any desired period. The most important problem is the assumption that returns from financial instrument are normally distributed.

10. 2. Risk Quantification
Risk quantification methods for market risk include: Monte Carlo simulation – this method operates on randomly generated returns. The probability distribution for describing returns can be normal or any other which fits better. It also allows forecasting of risk in any desired period. The other advantage of the Monte Carlo method is its simplicity