The analogy of light source and shadow is a good one ! The higher the risk, the higher uncertainty?

thank you Mr. Ternyik for the answer.

Not exactly. I didn't quite think so :) Rather, my metaphor was that when the light shines at a sharp angle and constantly changes its location (i.e. business conditions are changeable and difficult for an entrepreneur), there will be high uncertainty about the shaping of the end results for business projects.

Uncertainty is the opposite of certainty, i.e. full stability of the conditions in which we operate. If the operating conditions change, which is not included in the calculation of the risk of an operation aimed at a specific goal, the result of this operation may be at increased risk or may not be achieved at all, e.g. when a rocket taking off into space falls into uncontrolled vibrations (caused by some error technical), stronger and stronger (increase in uncertainty) during take-off and acceleration in a steep upward flight, may deviate from the course (previously calculated taking into account the distribution of variables, i.e. flight risk) or even suffer a crash.

The dynamic and kaleidoscopic nature of some business and economic variables may not allow for risk and uncertainty prescription.

Oh for crying out loud, these are definitions. If it can be measured, it is risk. If it cannot, it is uncertainty. Of course, the ability to measure things will change through time.

Thank you, Professor, for participating in the discussion. I apologize in advance for linguistic mistakes, because I know little english , definitely better at maths and economics. We probably studied the same school of classical corporate finance and the same lectures on risk management according to the theory of Anglo-Saxon economists. :) I learned risk management by Frank Knight theory during classes at the University of Economics in Poznań (Poland in Europe, the same city where the mathematicians who broke the enigma codes came from). It has never bothered me to look for answers to the questions that the financial analysts of the markets themselves, interviewed so many times on Bloomberg TV or CNBC or another news agency. Many analysts say this: "I observe high uncertainty, or" the uncertainty in the markets is increasing recently. "However, they added often the risk we can quantify, and the uncertainty is an immeasurable risk. I asked analysts questions as still a student of economics: high uncertainty of running a business or increasing uncertainty in the markets, what was the basis for your conclusion? On the basis of what measure do you think so? Usually, after such questions, the analyst got embarrassed and went like this: "it seems to me that since the business conditions have changed in relation to those that were forecasted several months ago, we have uncertainty for the business, or I was answered like this: „uncertainty is increasing, because a lot is changing in the environment and our initial plans for macro and public finance indicators are deeply revised - this means increased uncertainty”.

In my opinion, these analysts were simply asking and being questioned by me could not support themselves with anything more than a gut feeling and a general emotional impression based on professional experience. As cliometrics from Poznań, we say that uncertainty is measurable. For this we use residual variance, which measures the variability due to unexplained causes or experience errors using GARCH models , it is an analysis of time series loaded with heteroscedasticity (almost exclusively ex post) and it is not a matter of personal impression and emotional reception of changes. Let me remind you that several prominent ecomists have already started measuring the uncertainty, and here is what has been established in this regard:

The first method of uncertainty research is called the panel method, assuming that uncertainty leads to a lack of consensus among economists. It usually refers to the diversity of opinions among experts dealing with the future of the economy. It is assumed here that the greater the differentiation of opinions, the greater the uncertainty.

The second method of measuring uncertainty is indirectly related to the risk analysis and is based on the examination of forecast errors. Its logic is very simple: the greater the variation in forecast errors, the greater the uncertainty. Each forecast is treated separately as a forecast of one expert. The rule further applies that the greater the variation (this time of errors in forecasts and not the forecasts themselves), the greater the uncertainty. However, the concept of forecast errors is more complex here. This is because not only a point assessment is required (what will be inflation in the future, for example), but also a forecast of its volatility. The latter can be obtained using, for example, the Robert Engle method. The volatility forecast is used to adjust the scoring. The dispersion of forecast errors so corrected answers the question "what do not know about what I do not know?" (quoted after B. Wyżnikiewicz, W. Charemza, New challenge - measuring economic uncertainty, 2019). This method is based on the analysis of statistical data for the period previously forecasted. The uncertainty assessment requires the determination of forecast errors.

The third method is the simplest and directly refers to the concept of F. Knight. Its creator and promoter is Nicholas Bloom from Stanford University with his team. They created the EPU (Economic Policy Uncertainty Index). Its essence is to compare over time the number of articles published in large-scale opinion-forming journals in which the words "uncertainty" and similar in the context of the economy appear. If the number of such articles increases, the value of the index increases, and vice versa. The Bloom team provides the global EPU index values ​​online as well as 23 country indices. Recommended literature for researching the problem:

Robert Engle, GARCH 101: The Use of ARCH/GARCH Models in Aplied Econometrics, Journal of Economic Perspectives, nr 4/2001

Peter Ferderer, Does uncertainty affect investment spending? Journal of Post Keynesian Economics 1993, nr 16, pp 19-35

Jacek Wallusch, Niepewność w handlu morskim Gdańska z Europą Zachodnią w latach 1575-1783, in Gospodarka ludów Morza Bałtyckiego. Nowożytnośc i współczesność, t. II, Toruń 2009, pp. 24-44.

D. A. Zalewski, An Emiprical Analysis of Uncertainty and Investment During the Graet Depression, The Journal of Economic History, 1994, nr 2.

Summarizing the problem of uncertainty. If in fact the uncertainty is immeasurable, then all economists should remove from their language phrases such as low, high, increasing or decreasing economic uncertainty :) In other words, the language of my mathematics MSC. Z. Kaczmarek from the Railway Technical School in Ostrów, "if something can increase or decrease in time t1, it means that from some of its size in the base period t0 it is to decrease or increase by a specific numerical value".

Thank you, Mr. Oluwole, for an interesting observation. Even very dynamic phenomena can be studied, provided that we have accurate and systematic observations of events. Ideally, there should be hundreds of such confirmed observations. Then we can apply econometric models from the GARCH / ARCH group. You can try to control risk and uncertainty cannot be controlled. Personally, I believe that risk is predictable and uncertainty is not predictable. Ex post can measure both different risks and the degree of uncertainty of phenomena.