 Oh, okay, morning everybody. It's like always a renewed pleasure to be at the Property and Freedom Society, and I thank Professor Hoppe and Giltchen for their invitation. The title of my lecture today, my speech, will be, What if Anything Can Businessmen Learn from Betting Gods? It is an interesting thought association because the entrepreneur and the better seem to enjoy two completely opposite public images. The businessman is seen as a rational, highly educated, hardworking person who takes complex decisions and would undertake a risk investment only if a good reward is expected. The better, to the contrary, reminds us of an impulsive and spendthrift individual whose knowledge of the world barely extends beyond horses and docks, and who would risk his last shirt just to avoid the burden of work. Now, whatever the degree of average accuracy of these two stylized characters, from the point of view of an economist, they share a lot in common. First, both of them put at stake their own property in what is a legitimate private transaction. And second, in deciding on their investments, they both act in an imperfectly known environment, the uncertainty of which they try to limit. It is this last point that I would like to develop further on the ground of Ludwig von Mises's theory of probability. This will allow me to establish how common indeed the underlying aspects of conductive business and of making bets really are. And my hope is that this comparison will prove helpful in outlining the social usefulness of betting odds. Mises's probability theory is a theory of the different types of knowledge. Its starting point is the acting individual whose choices are constrained by scarcity, in the sense that he cannot obtain all of his ends due to the constraint availability of means. Only a limited number of ends can be achieved. Should scarcity not exist, which would imply that one would not have to give up anything and that all possible ends could be achieved instantaneously and at no cost, human action as we know it would be simply impossible. Nothing would be valued as a means given that there would be no ends yet unachieved. Nothing would be worth remembering, experimenting, learning, or even accumulating. Because the logical consequence of abundance is the negation of human nature, the necessity and reality of scarcity must therefore be admitted. Mises's most acclaimed contribution to social sciences is to have shown that the structure of human action, in other words, the economizing of means to achieve ends, has logically unavoidable implications and these logically unavoidable implications are the economic laws, such as the law of marginal utility or the law of decreasing returns. Now we learned about these laws from pure reticulation and introspective reflection on the very structure of human action. The knowledge which is gathered that way is certain in the sense that its validity is not contingent on evidence gathered from experience. The laws of economics apply whenever and wherever there is human action. Now presumably, whether there is human action or not is a matter indeed of empirical evidence. However, this piece of evidence has no bearing on the content of the economic laws. It only determines whether they apply or not and this type of knowledge which is certain, independent from experience and yet meaningfully related to reality is called praxeological knowledge. Economists improve this knowledge and communicate it by means of apodictic, that is certain statements that absolutely leave out any notion of probability. Now for the acting individual, praxeological knowledge, though useful, is by far the less important element of what it takes to accomplish a successful action. To achieve his goals, the acting individual must learn the underlying causal relationships between means and ends. He must actively search for new causal relations and constantly verify that past regularities that he observed still hold true. In short, human action needs a great deal of up-to-date practical knowledge of how the world works in practice. And the acquisition of this knowledge is grounded in the actor's own experiences as well as in the study of the natural sciences, which by the way themselves consist in classifying experiences and observations of real events. Now the specificity of this experimental knowledge is that there is nothing apodictic about it. It is essentially uncertain as there can be no logical guarantee that its validity will hold true tomorrow again. In short, this type of experimental knowledge is made out of and communicated through probable statements. Probability is the most characteristic aspect of our knowledge of reality. Let me quote Mrs. here. Apodictic certainty is only within the orbit of the deductive system of a prioristic theory. The most that can be attained with regards to reality is probability and the thought. Probability designates the deficiency or uncertainty of our knowledge for which Mrs. identifies two fundamentally distinct causes. First, our knowledge of natural phenomena is bound to be deficient because the ultimate causes that govern and move nature are so far hidden to us. Second, our knowledge of our own and other people's behavior is also bound to be incomplete because of the very reality of human choices. Mrs.'s innovative contribution to the theory of probability is to emphasize that these two distinct causes for uncertainty bring about very different knowledge imperfections. In his own terminology, he calls them respectively class and case probabilities. Class probability corresponds to collecting and communicating a type of knowledge that could be called statistical knowledge. A single phenomenon is described exclusively in terms of the characteristics of the whole class of similar phenomena to which it belongs. The knowledge deficiency here consists in a total ignorance of any of the particularities of the phenomenon. The only specificity known is that it belongs to a class for which all the relevant characteristics are known. For instance, we know nothing about a given premature baby developing hearing problems later in life. More importantly, there really is no tool available to get this knowledge for any single premature baby. However, we know that out of 100 such babies treated according to a specific medical protocol, 25 will develop hearing problems. Similarly, we know nothing about a specific airplane flight ending in a crash and we absolutely cannot know it. However, we know that one out of 30 million flights ends more or less dramatically. Progress in statistical knowledge is related to identifying through observation new classes to which a specific phenomenon belongs. A comparison of the different characteristics that result from a change in the class attribution is actually as far as natural sciences can go in the identification of the specific factors that determine the phenomenon under study. For instance, if current evidence shows that a given disease has a higher rate of occurrence among smokers than among non-smokers, then another way of expressing this is to say that smoking is a determining factor of the disease. And the partial contribution of this factor would even be numerically expressed based on the comparison of the two rates of occurrence within the two different classes. Richard Formises, Ludwig's brother, who has contributed most to develop the theory of class probability or as he calls it, relative frequency probability, gave his book The Unequivocal Pytal Probability, Statistics and Truth. According to him, truth is being attained through the accumulation and the description of statistics in line with the four basic operations of numerical probability analysis. Let me quote him, starting from a logically clear concept of probability, which for him meant only relative frequency probability, based on experience, using arguments which are usually called statistical, we can discover truth in wide domains of human interest and the thought. Richard's bias was to consider that this was the only scientifically available method for improving our imperfect knowledge of the world. And it is here that the second type of knowledge deficiency identified by his brother, Ludwig, becomes crucial. Some phenomena do not belong to any identified class. They are singular cases that form a one element class by themselves. As a consequence, statistics and numerical probability analysis are of no avail here to improve our knowledge of such phenomena. However, this does not mean that our knowledge of such case phenomena is even more deficient, quite to the contrary. The reason why these phenomena do not belong to any multiple element class is that we do know some of the specific factors that determine them. Let me quote Mises, case probability means we know, with regard to a particular event, some of the factors which determine its outcome. But there are other determining factors about which we know nothing. Most importantly, comes the last sentence of this quote, case probability has nothing in common with class probability, but the incompleteness of our knowledge and the quote. In a sense, we know more, though not everything, about such non-classifiable phenomena. And that is exactly what singles them out. First in the category, first in this category of single phenomena is human action itself, the logical structure of which is already known to us. And our deeper grasp of human action, as opposed to the natural phenomena, compels us to consider human choices as unique events. We'll learn more about them by Verstehen, which Mises identifies as a specific method of the social sciences. In historical analysis, when applied to past actions, Verstehen consists in understanding the specific factors that brought about the concrete individual choices. And when dealing with the uncertainty of the future, that same method implies speculating about how individuals will act. Thus, Mises' case probability corresponds to accumulating and communicating a type of knowledge that could be called speculative knowledge. Thanks to this definition of probability as deficient knowledge of two types, and to his categorical distinction between the fundamentally different types of probability, Mises actually solves intellectual disputes that have persisted until nowadays. In the food prints of his brother Richard, proponents of the objective theory insist that probability is a physical property of objects, very much like their mass, specific heat, or electric resistance. Following John Maynard Keynes, advocates of the subjective theory rethought that probability is just our subjective degree of belief of what phenomena are. Rudolf Karnap made an attempt to reconcile these two views and redefined subjective probability as a degree of logical rather than factual confirmation, which led him to introduce the very questionable notion of partial logical implication. Now, against this background, Ludwig von Mises' contribution is truly groundbreaking as it offers a complete and coherent alternative framework. Probability is neither objective nor subjective. It is the evolving knowledge relationship between a learning acting subject and the changing objective reality. In this framework, the acting individual has two tools to improve his knowledge of reality and has to make his future better predictable and to increase the chances of fulfilling a successful action. These tools are statistics and speculation. Statistics are the foundation of the natural sciences, but also of insurance. And insurance protects property from risky events. By paying a premium, the insured transforms a risky future event into a known present-day cost. In so far as the insurer has properly identified the class to which the insured event belongs and also has collected enough premium to cover the damages which will occur, insurance is always possible. Now, the extent to which the acting individual will effectively have recourse to insurance in order to fix some of the aspects of his future conditions will depend on his attitude towards risk. Now, things are somehow different with the other tool to improve future action, namely speculation. The use of speculation could not possibly be avoided by whoever is part of the social division of labor. And it is precisely as regards speculation that entrepreneurship and betting display a common ground. The capitalist entrepreneur invests his safe property with the goal to increase its value thanks to the future sales. Monetary calculation allows for an easy comparison of costs and receipts, both of which in a developed economy consist in monetary layouts. With respect to estimating costs, in addition to the entrepreneur's speculative skills, market studies and intelligence about competitors can also be helpful. But when it comes to anticipating future receipts, the entrepreneur engages exclusively in speculation about the behavior of his prospective customers and potential competitors. He has absolutely no way to know upfront how the patterns of his business will value his products, how the valuations of the customers will change in time, or what the impact on future prices will be of his potential competitors. Costs to the extent that they have been incurred already are known, and a large variety of long-term contractual relationships also allows to some extent to fix costs. However, no businessman knows upfront how receptive the demand for his products will be, or how strong the pressure from his potential competitors will be. If his speculations about the future market conditions are relatively better than those of his competitors, then he will make a profit and improve the value of his property. And conversely, if his competitors display stronger speculative skills of better understanding other people's behavior, he will suffer a loss. Now, this relative comparison between speculative skills is of some importance here. By investing his property in the specific production of the product A, let's say, an entrepreneur offers the opportunity to invest in the production of B. This puts an upward pressure on the cost of reducing A and makes the cost of reducing B lower than what they would have been otherwise. This implies that differences between the future profitability of producing A, or B, can be traced back to the failure of competing businessman to invest in the product with the higher profitability. And this failure, in turn, reveals weaker speculative skills. Thus, while profit and loss stem from the uncertainty of the future, how exactly they affect individual's wealth depends on each one's relative speculative capacity. This is fully consistent with Mises' view that speculation is a specific human tool for improving our knowledge of the uncertain future. The relatively better speculators are those who anticipate better the future before it unports. Accordingly, they can better adapt their present actions and make a more informed use of their property, which results ultimately in an improvement of its value. Now, betting makes use of exactly this same cognitive tool of speculation, let me quote Mises. A bet is the engagement to risk money or other things against another man on the result of an event about the outcome of which we know only so much is can be known on the ground of understanding. Understanding has a specific tool as Verstehen, a specific cognitive tool for dealing with case probable events, anything. Now, again, paramount among such events are human choices. Some human choices, for instance, deciding on the name of the third heir of what is called the British monarchy or selecting the winner of a popular TV show have insignificant social implications. Bet on such events do not interest anyone beyond those who take part into them. They are a sort of leisure games. Based on the evolving number of participants in these games and their willingness to wage money, the bookmaker can adjust the odds in a way to himself retain and determine some of money which will be the fact of the price for creating the game. Competition between bookmakers, together with better eagerness to play, regulates this aggregate price of organizing the game. Now, how this price will eventually be spread between the better players will depend on how successful their individual bets turn out to be. Some other human choices, however, have important social and market implications. The choice of the US president will greatly influence who the next net taxpayers and the net tax consumers will be. Betting odds on this outcome provide helpful guidance to businessmen who can use this piece of information for their investment decisions. To be sure, the betting odds do not say who the next US president will be. None of the betters has this knowledge. However, the odds reflect a kind of consensus opinion that is eventually determined by the marginal better. This opinion gains in credibility as more people substantiated by waging parts of their own resources. As a matter of fact, empirical evidence indicates that most of the time, though not always, betting odds are more accurate predictors than surveys. It is crucial to emphasize, though, that betting odds do not make our knowledge of the future perfect. They only express what could be called an average speculative judgment. Now, this average will interest those individuals who believe they have low speculative skills with respect to understanding and predicting their specific outcome. Others who think they have a superior speculative capacity would naturally have little consideration for the betting odds. Now, this observation about the different relative speculating skills, I believe becomes crucial for understanding that specific instance of betting, which is most relevant in daily life, namely the financial market of derivatives. Derivatives, better known as futures, options, and swaps, engage their seller to a predetermined payment irrespective of the future price of an asset or a commodity. That way, against a known fee, the buyer of a derivative locks in a price. Because future prices are not binary events, but could be anywhere in a range, derivatives are not quoted by their implicit betting odds, but by their own price. However, for any future price of the underlying asset, a definite betting ratio between the derivatives price and the future net payoff could be constructed. Let me give an easier example that of the credit default swaps, which is based on a simpler binary outcome, namely the default or survival of a borrower. The buyer of such a swap pays a fee, let's say 50,000 euros, in order to get a one million euro payment by the seller of the swap if a designated borrower was to default on his liabilities within a year. In financial parlance, this fee is called spread, and the spread is quoted in basis points, each of which is 100% of a percent. In my example, the credit default swap spread is 500 basis points, which implies a betting odds on default of one to 20. Now it is popular to speak of a prediction market of a sort and to interpret this ratio as implying a 5% probability of default. There is nothing wrong in using this expression. It should nevertheless be made clear what it means and what it does not mean. It does not mean that one out of 20 similar borrowers will go bankrupt within a year. It does not mean either that 20 lenders of one million euro could ensure themselves against losses from default if each of them contributed 50,000 euros in a common pool. These would be or would have been valid implications of statistical knowledge describing classifiable events. The future behavior of a borrower on a given loan does not fall into this category. It is a sui generis individual phenomenon determined by various specific factors that lenders typically try to grasp by means of a speculative credit analysis. The CDS spread, even if expressed as a numerical probability of default, which is just one way of expressing it, does not describe the statistical occurrence of default within a group of borrowers. It tells how much money speculators are asking in order for them to endure the effect of future uncertainty on the value of an asset, instead and in place of the current owner of the asset. In a sense, this is the price for transferring the yet unknown impact of uncertainty. The betting opportunities offered by the financial derivatives market have a strong positive social impact. They foster the division of labor and promote capital accumulation. The buyer of a derivative by fixing the future price or the value of an asset gets rid of the uncertainty of the future insofar as it would have affected him. This yet unknown impact is now endured by somebody else who thereby declares to possess better speculative skills. So derivatives allow for dissociating the purely entrepreneurial function, which consists in bearing uncertainty, from the managerial function, which consists in buying, renting, and arranging factors of production. Some acting individuals might have a great deal of accumulated property and good managerial capabilities, but very poor speculative skills. Others might combine poor technological and managerial knowledge with great speculative skills. And thanks to the derivatives market that is betting, these persons can associate with each other for an investment project that otherwise would have not happened. Each of them can specialize in what he knows best. He can learn more of it and thereby create new association opportunities. So a market for bets on future prices stimulates the emergence of two distinct types of businessmen, the managing type and the speculating type. The managing businessman is conversant with technological and organizational processes, with market data, and with other statistical knowledge. He is firmly anchored in the present and looks at innovations with the eyes actually of an engineer. The speculating businessman is very different. He knows little about the technical aspects of the production and does not inquire much about past and present regularities. He looks for innovations and sees them as if from the future. He's the one that takes upon the real entrepreneurial function in the economy. So in conclusion, betting appears indeed related to learning, but in a very specific way. The betting odds, whether they concern prices or other future phenomena, express personal opinions, not objective data. Thus, there is nothing really to be learned from the odds themselves, but the personal opinions of the betas. These opinions would be a valuable piece of knowledge and therefore worth learning about for all those who believe their own opinions about the matter are somehow inferior. However, there is more to betting, especially when it comes to betting on future prices. Derivative markets have a definitive impact on the organization of the division of labor and on the acquisition of knowledge in society. Derivatives create the conditions under which one can specialize in acquiring the type of knowledge, statistical or speculative, at which he is best. Therefore, betting contributes to improving our learning process. However, and once again, this improved learning is not due to the betting odds, that is to the derivatives prices, which only express opinions. The improved learning is due to the new conditions offered by the betting transaction itself. New conditions in which the impact of uncertainty on the value of an asset is being transferred from the owner of that asset to the betting counterpart. Thank you.