 I think, yeah, yes, I put it there, so it's up. Good morning, everybody. Yeah, it's finance, it's more about risk. When Matteo asked me to come and present something to a conference on ecology, I said, oh, but that's not really my field. Then he talked about time horizon, and I said, oh, yeah, yeah, risk is my field, and I believe that risk has something to do with the way we want to manage the world. I'm giving a course in the University of Zurich that I'm calling the Economy of Risk in Insurance. And when the student asked me, why did I call this course like this, I said, because I believe there is value in risk management. Something the students in finance learn have no value. If you do the CAPM theory and you do that correctly, you will see that for CAPM risk management has no value. So I thought maybe working on that would show the student the value of it, and I want to show you also here the value of risk management in terms of assessing the problems we have with climate change. So now, how do I, oh, here it is. This work I'm showing you today has been done with Professor Katz at the ESSEC Business School. We had a seminar on philosophy of complexity, and they asked us to talk about risk management, so that's where the work comes from. When I think about a word, I always go to the dictionary. I like to see what the dictionary saying about the word. So about the word risk, I took two dictionary, one English dictionary, and one American one, to see what were the position of those different culture about risk. And you will see that they look very much the same, except that the American, they've added one thing, which is the degree of probability of loss. But if you read at this, the only thing you hear about risk is danger, commercial loss, person considered as a liability or a danger, amount of possible loss. So you wonder why, I mean, I'm working in reinsurance, why reinsurance would like to take risk. The reason is in the definition of Wikipedia that I like very much, risk is a concept that denotes the precise probability of specific eventualities. Technically, the notion of risk is independent from the notion of value, and as such eventualities may have both beneficial and adverse consequences. However, in general usage, the convention is to focus only on potential negative impact to some characteristic of values that may arise from a future event. So as often, I find Wikipedia very useful in those kind of thing. And yes, the notion of risk is relatively new, actually. It started with Bernoulli, who wrote a book on probability at the end of the 17th century, and the 18th century with the Enlightenment became a notion that was very much used. Here I'm quoting Etienne de Condiac, French philosopher. He defined risk as the chance of incurring a bad outcome, coupled with the hope if we escape it to achieve a good one. And in this movement about risk, the 18th century is a time when the notion that a social institution could protect people against risk started. Before that, when there was a disaster or something, the king would take the money from his cassette to pay the things. And the first time was in 1786, when the king of France, 16th, there was a big flood in France, ordered the state to pay them. So it's a change in mentality. And this contributed, of course, to the development of insurance afterwards. Life insurance, for instance, was not really acceptable by religion because it was a bet against God. And it's interesting to know that the first life insurance was actually built by a priest in Scotland. And that gave birth to the Scottish widow, the first life insurance in the world. Very often, risk and uncertainty are used indistinctly, but in economics, the tradition wants to distinguish between the two concepts. And this originates from the dissertation on risk from Frank Knight, where he makes a clear distinction between the two. He defines risk as a randomness with knowable probabilities, which is a measurable uncertainty, while uncertainty is a randomness with unknowable probabilities. Donald Ramsfeld is somebody I don't like very much. He put us in many difficulties with the war in Iraq, but he had two statements that I really liked. He said, there are two sorts of unknowns. The known unknowns and the unknown unknowns. And if you want, the risk is the known unknowns. And uncertainty is the unknown unknowns. And you'll understand why Warren Buffett, who has made a lot of money in insurance, always says you should insure what you understand because insurance is about risk and not uncertainty. That's why, for instance, war is excluded from insurance. If you now bundle risk in a portfolio, the risk of the portfolio will decrease. And that is the idea of insurance, is socialization of risk. It's very old, by the way. The first insurance contract that we found in history was written by the Babylonians, farmers there, got together to insure crops. And then the Greeks with the, with Navy, et cetera. So it's a very old concept, socialization of risk. If the different risks are independent, you will see from probability theory that it can be reduced almost to zero. That would be the perpetual mobility. Unfortunately, and that is going to be part of my lecture today, risk is rarely, I would say even never completely independent. This dependence, of course, limits the diversification benefit and risk cannot be brought to zero, as we know. There is, though, only one free lunch is diversification. So it's the only place where when you invest money or when you do work that you can hope to reduce your risk is by diversification. There is no other possibilities. And that's why when you go to invest, you have to be very, very careful about where you invest and how you diversify. A stochastic world. I made a small exercise putting on this graph the events that happened in the 21st century, the events I remembered. And you will see it's quite interesting. It's all started with the 9th, 11th, big shock. Then we had the internet bubble in 2002, 2003. Then we had the big Atosha terrorist attack in Bandrit followed by a bombing in London. And we also had Katrina Vilma that flooded New Orleans and actually was a big loss for insurance. By the way, I usually give this example to my student. The Katrina Vilma costed the reinsurance business 50 billion dollar. The whole premium of reinsurance at that time was about 150 billion all over the world for all the risk in the world. And one risk cost about a third of it. There was one bankruptcy out of 125 reinsurer. We were going to move to subprime crisis and Lehman Brothers financial crisis. The subprime market was about 700 billion US dollar. The real estate market in the US was 12,000 billion. So 700 billion, 12,000 billion. The whole world is on its knees in terms of finance. A third of the premium was a non-event for reinsurance. You wonder why? And I think one of the reasons, I will show you that a bit later, is the models that the bank use for the risk management are completely flawed. By the way, at the same time at the Lehman Brothers crisis there was a Georgia crisis with Russia which is after the Chechen war one of the first step taken by Putin that will bring us to what we are now. Then, I don't know if you remember, but in 2010, this volcano eruption that stopped all flights in Europe. I had a friend who was supposed to come to visit me. He was in Egypt. It took him a week to get back to Switzerland because of the volcano eruption. And this is one of the dangers that we identified in reinsurance to be quite big at one point, that a volcano eruption could stop all travel, airplane travel in the whole world. The Pinatubo eruption in the beginning of the 19th century would have done that. Arab Spring, Christ's Church Earthquake, Japanese Tsunami, Thai Flood, same year, 2011. Sandis in the U.S., sovereign debt crisis. Ukraine, First War, ISIS. Charlie Hebdo, Vir Shafandas, the big immigration crisis in Europe. Ebola, Bataklan, Brexit, Trump election. Fires in Canada that evacuated half of the city unrest in Iran, a big one at the end of 2017. The election of Bolsonaro, which is another sign of populists growing in the world. Fires in Australia in 2020. I don't know if you remember, but I had many friends in Australia that were very, very shocked by the size of those fires. COVID, and last but not least, Ukraine. So I think you would agree with me that we are really entering in the face of stochastic work, where lots of stochastic events put us off balance. It was always like this in the past. The history is full of those events. But what happens now is any of these events has consequences somewhere else, very quickly. The pest plague took about 10 years to come from Kyrgyzstan to Europe. COVID took few weeks. So when we are facing such a stochastic work, what happens, and this is a bit, the diagnosis that we posed at the time, that's already 10 years ago or 20 years ago, that big risks are growing. They're growing for insurance, but I think they're growing for society in general. What are the reasons for that? Demographic changes, concentration of population. We had yesterday an interesting talk on population, but wasn't concentrated on what I am interested in, which is really the concentration of population in cities and movement of population, the spread of disease. Climate change, so the risk of natural catastrophes are increasing, and we can see that in the numbers of claims that we ensure get on natural catastrophes. Social and political changes. I think one part is good, that the better living standards make people get more insured and they, of course, claim more when disaster happened. New technologies, internet of things, cyber attacks, we have seen during the COVID phase a surge of cyber attacks, particularly interesting enough on hospitals. I don't think the people were so interested in hospital, but they're cynical. That's the place where they could attack, so they did. New financial products. We have also seen during the financial crisis how those products, which are supposed to be capital protected, can all of a sudden go down the drain because they were protected by lemon browsers. Here is interesting graph, I think, about population. You see that around between 2000 and 2010, the population of the world in cities became higher than in land, and of course that has consequences on the size of the problems. When it hits somewhere. The next graph is interesting, and you will see that with the one that comes afterwards. When I showed this graph to a friend, they said, but why, you are showing me the same graph, no, no. This graph shows you the concentration of population in cities, and you see there in 2013, that's the prediction that they did in 2019 at the UNO, you see all those dots of big cities and the red ones that are cities of more than 10 million, there were only three in 1970. Now, this other graph that my friend said is the same one, this is not the same. This is a graph that shows you the natural catastrophes that happened until 2007 in the world. But you see those natural catastrophes are exactly in the regions where you have those big cities. So, that is where this problem of peak, yes? This we, those are the claims that insurance had. And of course, you can see that you also have claims in Africa, you also have claims in, so it's not only in developed countries. You know this, but I like it because it goes far, far back. This is the temperature change, the average temperature change per year, and you see this hockey stick graph that many people give, so I think I don't have to convince you about climate change here. Another interesting thing that we saw already yesterday, this is the life expectancy from 1945 where pension funds started to be developed to 2010. So you see that in the US, the life expectancy grew by about 13 years. The total fertility went down by 19%. Japan is the most dramatic case. 31 years of life expectancy grows and 70% fertility downward. France is somewhere in between, but you see 26 years of increase in life expectancy is huge. So pension fund funds have to provide funding with much fewer productive people. So how do you do this? By looking at higher return. How do you get higher return? By taking more risk. And when you take more risk, you increase the volatility. And if you now look at the volatility of financial markets in the last 50 years, okay, I'm not going to enter in all the details because it depends on the frequency at which you look at it, but if you look at it at high frequency, the volatility has increased a lot. So which also means the risk has increased, the financial risk has increased. So managing risk. Distress and risk attitude over the years, I think in the few centuries ago, people lived, had lives that were very uncertain. They fragility gave people a strong sense of vulnerability and that also reduced their willingness to take risks. Although this idea of risk did not really exist. And you had very slow growth in the middle age. The advent of industrialization combined with the philosophical critique of religion were strong causes for the change in perception. As a consequence, people started to take more risk. The idea of lending money became very popular. And we had a phenomenal economic growth. I'll show you an example of that. And the first in science was very hard. The 19th century is the time when science was the hero. In France, Pasteur had national funerals when he died. I doubt if any of the scientists of today will get that anymore. Yeah, that's phenomenal growth. I took Sweden because Sweden didn't have the war and it's quite impressive. If you go back to 1720, how fast the GDP grows. At the same time, of course, it had enormous environment impact, as we know. This growth was done at the price of consuming the commodities our Earth is offering us. By the late 20th century, individual existence in developed countries appeared to be boringly secure. Epidemic disease were out. Peaceful and war between great powers seemed impossible because of nuclear war. And skepticism about science started to grow. Weapons of mass destruction, environmental problems made people question the validity of all those scientific discovery. Was it useful? Is it just not surprising that the perception of risk has once more dramatically changed over the course of the economic development? Managing risk should help us lead more predictable lives. And it's quite interesting when you go through the newspaper, society as a whole demands a word where the vulnerability of mankind is diminished. In the old days, when the natural catastrophe happened, preacher asked people to repent and were pointing to God's anger with human behavior. Today, we rather look for the responsibility of people. Letting the disaster happen without having prepared enough for it. Governments are made liable. I think it's quite also interesting to look at reaction about the war. Oh, it's terrible, it's criminal. Yes, it is. Yes, it's, but war is criminal in itself. And it produces those kinds of events. When you allow people to kill, don't be surprised. They will do other things too. And simultaneously, I think people are not ready to pay. You know, it was quite interesting when soldiers died in outside wars, there was an uproar in countries. I mean, when you send soldiers to war, there will be soldiers killed. So the change of mentality is quite important here. At the same time, people refuse to pay the price of risk. We were discussing yesterday about, you know, those plastic bottom. We pay for the production, but we don't pay for the recycling. If we would pay for the recycling of that, it would cost four or five times that. So we're not ready to pay the price of risk. The same thing, you build a nuclear power plant, it's very expensive, but we don't pay for the risk we bring. Same thing with the carbon power plant. Rating agencies were distributing this triple A rating to structured product like mortgage-backed securities on subprime loans at a very doubtful credit worthiness if you would do the model right. CEO of big banks proposed to make 25% return on equity. I remember that was in 2007, I was presenting our capital management structure to bank analyst in London. And one of these analysts asked me, Mr. Dakaranya, it's very interesting, you only talk about capital, but you don't talk about return. I said, sir, you don't understand me. When I talk about capital, I need to protect myself against the risk. I'm also talking about return. And you should throw stones at Mr. Ackerman when he says he wants to do 25% return on equity. If he would do that for 10 years, he would multiply his capital by 300. Is that sustainable for the German economy? Does it make sense? I understand that a company, a startup company that comes with a new product make 25% return on equity. When you get to Deutsche Bank office, do you feel the startup atmosphere? I mean, it's a bank, okay? Today, Deutsche Bank is struggling very hard because putting such a target on their profit is criminal, that's my opinion on that. Because it is, you have to take enormous risks and not with your money to reach those returns. All of these examples points to the necessity of being better aware of the realistic price of what you're doing. The demand for more safety can only go with, I think, more sophisticated risk management that thrives for making the system more resilient. Risk and complexity. There are two phenomena that contribute to make risks more complex and difficult to handle today. The first one is a shortening of the time scale. I mentioned this question of the Pest Plagd, but we see that in many, many aspects. I gave you a few months ago a talk on high-frequency trading. When I started working in finance, the high-frequency trading was few times a day. Now, high-frequency trading is few thousand times a day. And the increased interdependences. And so that has consequences on long-term. So that's what was interesting. At one point, you have your time scales at shortened and at the same time, because of this interdependence becoming very big, the consequence of what you're doing have very long-term effects. We have multiple networks that have developed. And these networks are working at the faster space. What took months before would take hours today, sometimes even minutes. With the advent of those technologies that we also heard about a few minutes ago, the human brain might be overwhelmed. Our brain does not function at those speeds. Computers do. We need, when we think, or at least I do, I need time. I need time to understand. I need time to decide. Will we be able ourselves to adapt to this new timescale? The example of cyber risk is interesting. This map here was done by experts about dependence of different things. As we progress in the 21st century, the complexity of society appears to become more apparent. Cyber risk is inextricably linked to the rise of hyperconnectivity and through the physical world around us. An example, when Russia attacked Ukraine, they launched an attack against a communication network that stopped people communicating in France. And they did that because this network was used by the Ukrainian army. By the way, it made a big claim for insurance and big discussion, is this war, act of war excluded from the insurance or not? I was at a seminar at Lloyd's where distinguished lawyers discussed for hours on that. But because that's the other thing, war is about destruction and the exclusion of war is about destruction. Here, nothing was destructive, just communication. Predictions that we do with our model become much more dependent on the assumptions that we have used for this dependence. I'll show you an example when I'm finishing my talk. There are interesting things also. I said our brain could be overrun, but at the same time, in our lifetime, we leave many outcomes of risks. This might give us the opportunity to study them better to see, we can often see their immediate consequences now. So for instance, the COVID pandemics we've had it and so we've seen the consequences of it. Although we knew about it before, when you live through it, you might learn more. And the appearance of new interaction could help us change our views on phenomenon. It was interesting, you talked yesterday about the way you do the taxonomy of the vegetation. So you see new interactions that we hadn't seen before or we hadn't understood because maybe they were there but we didn't see them. And here, that's my strong belief that scientific approach consists in distinguishing the main contribution to the phenomenon and in modeling them. So I am personally quite skeptical on those extremely complex model with lots of parameters that at the end do not for me explain much. I remember when I was studying physics, this professor who was telling us, imagine that you have the computer that model everything. It's very good in modeling everything. You would not understand. That was 50 years ago, we are almost there. I'm preaching for that science should help us simplify, reducing the problem, putting it on grounds that we can be treated and experimentally proven. If you do this, I think this scientific approach will be crucial to handle this complex world. For the inherent risks or the risks that we already had and the new ones born from our connections, studying the dependence between risks is essential for understanding their impact on consequences. Just before coming here, I was contracted by a big insurance company to look at their insurance risk model. And my criticism to them was exactly this. The way they modeled their dependence was not good because very often in risk, dependence increases when the situation gets bad. We've seen that. You see certain dependence that were not so obvious before. And that's the difficult part. I talked about diversification before. And there is a saying in trading rooms, diversification disappears when you need it the most during the crisis. So modeling the dependence is becoming something very important. We have less and less time to take decisions and their impact are more and more longer. And we are facing this contradiction today. So notion like linear correlation, copulas were introduced to treat statistically the problem of dependence between random variables and we should use more of that. The realization that risk are more interdependent in extreme situation led us to develop the notion of systemic risk, which is the risk for the whole system and what we also call systematic risk, which are risks that are a component of many, many systems. During the last financial crisis, reality reminded us that the new quantitative tools might be used with the full, because I remember going to a conference in Washington where Alan Greenspan at the time said, oh, financial crisis will disappear because we have very good risk management tools. How wrong he was. Because I think many of those tools, I told you, one of them is this CAPM theory that says that risk management has no value. These assumptions that are used to do those model and one of the assumption of CAPM is that the market works without friction. Ridiculous, what makes economy interesting is exactly what makes also sex interesting. Those are the frictions. Without frictions, the economy would not work and without frictions, there would be no reinsurer because insurance would be enough. The problem, there is no market for insurance liability and the reinsurer to this market for the liability. Many of the models that are used in banks rely on Gaussian assumptions. They grossly underestimate the probability of extreme events. However, there were already other models based on extreme value theory that would attribute reasonable probabilities to what actually happened and that's what I want to show you at the end. This is something coming out of our economic scenario generator model that we developed in 2005. And here is the prediction of the distribution for the third quarter, 2008. The yellow is the forecast. The blue is the distribution forecast. The purple is what really happened. And if you look at the probability of what really happened in the distribution that we predicted, it was minus 9%. So both models were not very right, but that's not bad. The bad thing, so you have the Gaussian model and the one that we developed with extreme value theory. The next one is much more interesting. That's the fourth quarter of 2008 after the crash of the Lehman Brothers crash. So here, of course, the forecast was completely wrong, but what is interesting is that the Gaussian model would give you the probability of this event to be one over 1400 years, so impossible, basically. And our model gave one over 100 years. Is this the right probability? I don't know. What I can tell you is I have about, historians have reconstructed the S&P 500 from the beginning of the New York Stock Exchange. And if I look at the data from then, this is the second largest shock. So one over 100 year, maybe, maybe not, but certainly much better as a probability than 1000 years. If you're a risk manager, if you have a one over 100 year probability, you will care about it. If you have a 1400 year probability, you will not care about it. Okay, that brings me to my conclusion. Living in a rich world subject to large stochastic shock demand a level of sophistication in handling the risks that we have not known in the past. At the same time, we must, and that's something that sometimes I feel people forget. We must accept that risk. It is an inherent component of innovation and progress. We cannot completely refuse a risk. You see what happens now in China. We don't want this pandemic to happen, but it will happen, whatever you do. And to stop it happening, you killed the society. So we need to accept the risk, but we need tools to apprehend and manage the future outcomes and hedge the worst scenario. And that's where I think insurance, well done, and the financial system that works are very important because they help us go through those crisis with as little harm as possible. Climate change, as we know, political instabilities that we have seen, the Trump election, the Bolsonaro elections, and many others. The over reliance and complex IT systems, the other day I almost lost my iPhone and I got crazy. I really got crazy because I have my train ticket on it. I have my visa card on it. I have my passport on it. 20 years ago, I did not notice those kinds of instruments. So to help us prepare a better future for the new generations, I am so lucky to have now grandchildren, but I'm afraid for them. Risk management should be given the aim of improving the efficiency of our work by optimizing risk and return together. We cannot live without return, but we must live with risk. So we need to bundle them together and understand when we take decision that there are risks and return and do a compromise. 25% return on equity means that you're going to take very, very high risk. Sometimes it makes sense. Develop a new vaccine, come up with new things, but for a bank, it is criminal. I think, and I want to finish with an optimistic touch, the future is wide open to good scientists and managers to provide society with both security it demands without losing the creativity and the entrepreneurship we need. Thank you very much. Okay, thank you very much, Mikhail. So I think there are many questions, but I have one. So do you think the private sector can provide a risk insurance to cope with the challenges that are ahead like climate change? Or do you think that the finance in the private sector will not be able to do that and we need institutions? We need... You know I'm Swiss, so I'll give you a Swiss answer. We need both. I think we need the private sector. Because capital allocation with restricted resources is a very difficult task and we need many people to work on it. But I don't think the private sector will do it without strong regulation. One of the reason why financial crisis all of a sudden started to become very high is because the Glass-Steagall Act was put away by Clinton and the Glass-Steagall Act was a law passed by Roosevelt after the big depression. So yes, we need regulation. Financial sector, private sector cannot do it without that. We need intelligent regulation is not always easy and that's where science is very important. The last work I did now was to prove that the way we measure risk today is intrinsically pro-cyclical. So mathematically pro-cyclical and that's very bad because it means that during quite times we'll don't think about the risk and when situation is very bad we ask for much more capital than what we actually need and then we make the crisis even worse. We have seen that in 2008, 2009. So both. So I have a question regarding the relation between known unknowns and unknown unknowns, right? I mean, this is clear, it's also intriguing but even the known unknowns are always based on a model of reality on what you think you know and there is a risk that what you know is wrong, right? You have seen for instance the banks. The banks were thought that they can measure the known unknowns but actually it was based on a model that were completely rotten, right? So in some sense, I would like if you can comment you know on the risk of getting in wrong and known unknowns, all models are wrong, some are useful, right? I think those that are not useful tend to be dangerous, right? Because based on wrong models you take wrong decisions. Not only the banks can get the model wrong but also the economic system is based on a model of economic behavior which maybe we will find out in a few years that is as rotten as the very simplistic Gaussian assumptions in 2008. So maybe we also the illusion of controlling the risk based on a model that maybe is a bit less simplistic than the one based on Gaussian independence assumption maybe is more elaborated but don't you think that is still a risky illusion that you can really handle the risks as opposite to understand the source of the risk and maybe mitigate the risk, prevent the risk, maybe accepting the idea that we are working on the wrong model of society of economy? Yes, but what is the alternative? So yes, you're right, model can be wrong. By the way, I would like to say that the bank was using, we're using wrong model willingly, knowingly. I know that. I, a good friend of mine was the chief risk officer for credit risk at one of the big Swiss banks. He showed me the email he sent to the CEO on those triple A MBS. Saying that he actually modeled it and he wasn't triple A and he warned the CEO and he said you use, you must use rating agency thing. So I don't think he's a model that brought us the financial crisis is greed. Okay, this being said model can be wrong. Yes, definitely. And that's why scientific approach is important because science is about fighting the error. If you remember Popper. So that is why I think we need to be, to try at least to be as rational as possible. And also in the model we developed, we also included what we called model risk. Or some of the assumption you put in the model, you can actually quantify the error. Yes, uncertainty and risk. The boundary is difficult. And I think the role of science is to push the boundary between risk and uncertainty, to push this frontier. And that's what it has been doing. Not enough, I agree, but I don't see any other alternative. And here I'm talking like Margaret Satcher. Yeah, thank you very much. Thank you, here we go. Two comments and a sort of question. The first one is just the irony of your closing statement that you exhort us to optimize risk and return and then tell us how foolish you are with your phone, which is sort of interesting that someone who has the understanding you have can't translate it into your own behavior. So you put your passport, your credit cards and everything on one device. So that's rather alarming to me, but that's just an observation that somehow the intellect doesn't translate into behavior. The second point, comment, is simplicity for complexity. And this is something that we debate endlessly, of course. And I would make a distinction between simplicity for publishing, which is 50% at least of papers. There's simplicity for tractability. You are very optimistic. And maybe I'm not, very okay, but simplicity for tractability, which is sort of okay. And then there's simplicity for understanding. And this is an interesting debate I have with physicists. So tractability is not understanding. It's understanding the mathematics, not the world. Okay, so that's another comment. And the third, now here's the question, which is, is insurance becoming reinsurance? Is that sort of the evolution in terms of methods that the world is now moving into this kind of extreme value phenomenology which you have expertise in? Is there a sort of a migration from the methods of insurance to reinsurance? For the last question, here I can answer definitely yes. If you look at the evolution, more and more in insurance, there rely on methodologies that were developed by reinsurance. And this thing I was talking about, the validation, it was an insurance company asking me a reinsurer to validate their model. Yes, yes, because peak risks are growing for insurance as I showed you. The question of simplicity is a very important one. I agree with you. And I think your comments I share. By the way, I have my passport in paper and the credit card in plastic. Thanks for the presentation. I'm encouraged by the fact that the insurance industry is one of the leading industries taking climate change seriously because it touches them so closely and I think they're gonna help move the rest of the market in that direction. But I'm also worried about, as you presented that as their, as risk goes up, they're looking for returns that are higher and unrealistic. And I mean, you showed, as you called it sustainable growth, but you couched it immediately. And I mean, I think we're in a very much growth limited world. And so this kind of, this collision that's coming between end of growth in some ways, as we're used to at least and the need for more. So I don't know where you see that going. Agreed. I mean, I could have, and I thought about that before, show you some of the model we have developed about pension theoretical models. And in those models, what you see is sometimes to reduce the risk the long term, you have to take more risk shorter. This interplay between the two, the two horizon are very important. I find sometimes paradoxical that we ask the pension fund to invest in government votes. I mean, all these savings that we've put now and we want to do pension fund with that is put in inefficient investment. I'm physicist from training. So I know what I'm eating now is what we produce now, not what we produced 30 years ago. So you have to look at this in a dynamic way. If we want to feed the people in 30 years, we need to become to put the society in a path where it is more efficient. If we don't do this, whatever saving you do now will not help. On the contrary, what will happen is what you have those huge volatility. We should invest in new ideas, new ways of solving the problem rather than in safe investment. It's a difficult problem. I have no full solution, but sometimes I'm very surprised the way people think about it. That was my mission, such we need to take risk. If we want progress, we have to take big risk so to stop the climate change, very big. And we have to change a lot in the way we live. We don't want that. That's why we are in the situation we are now. So one comment is, I mean, it would be nice to have some quantitative measure of where we are going. I mean, say you said there is an interplay between long-term risk and short-term risk. So are we, I mean, can this be measured quantitatively at the global scales? Are we building up risk in the future? Or are we, say, decreasing risk in the future? Or, say, there is a sense that, say, finance is disconnected with the real economy. Can this be measured? And can one understand what the trends are? So, I mean, can these questions be made quantitative? I think this conference is very useful for us. Those conferences where we confront different methodology in different sectors will help us build things like, for instance, I would like that the models that look at ecological decision get inspired by some of the model we use for this long-term investment. Because we have developed models for this interplay that could be used. I've not done it, but I think they could be used in this field to estimate quantitatively what happens if you increase the risk now, reduce the risk later, or the reverse. Because it's not in all situations that you have to take risk now to reduce the risk in the future. There are some situations, not all of them. So, depending on, it's a derivative that is sometimes positive, sometimes negative. And you have to find the boundary conditions where this is true. So, I think we could use such approach in such model also for ecological decisions. Okay, so I think we have a coffee break. Maybe we reconvene at a quarter past 11.