Couldn’t they have predicted that?


I am following up, smoothly, on my last update in French, namely « Quel rapport avec l’incertitude comportementale ? », and so I give a little prod to the path of scientific research possible do develop around my work on the EneFin project. I am focusing on the practical assumptions of the project itself, and I am translating them into science. There is one notable difference between business planning and science (I mean, there is more than one, but this one is the one I feel like moaning about a little). In business, when you make bold assumptions, you can make people cautious or enthusiastic, it depends, really. In science, bold assumptions are what Agatha Christie’s characters used to describe as ‘a particularly laborious way to commit suicide’. Bold assumptions, in a scientific publication, are like feebly guarded doors to a vault full of gold: it is just a matter of time before someone tries and breaks in.

Thus, I am translating my bold assumptions from the business plan into weak scientific assumptions. A weak scientific assumption is the one which does not really assume a lot. The less is being assumed, the weaker is the assumption, hence the stronger it is against criticism. Sounds crazy, but what do you want, that’s science.

Anyway, the whole idea of EneFinc came to my mind as I was comparing two types of end-user, retail prices in the European market of electricity: those offered to small users, like households, and those, noticeably lower, reserved for the big, institutional customers. EeFin is a scheme, which allows small users of electricity to get it at the actual low price for big customers, and, in the same time, still allows the suppliers to benefit from the surplus between the small-customer prices, and the big-customer ones, only in the form of equity, not sales as such.

There are markets, thus, where, at a moment t, there is a difference between the price of electricity for small users PESU(t), and that for the big ones: PEBU(t). Formally, I express it as PESU(t) > PEBU(t) or as PESU(t) – PEBU(t) > 0. The difference PESU(t) > PEBU(t) comes from different levels of consumption (Q) per user, thus from QSU(t) < QBU(t).

Now, I further (weakly) assume that the difference PESU(t) – PEBU(t) > 0 can make a behavioural incentive for the small users to migrate towards suppliers, who minimize that gap. Alternatively, a supplier can offer additional economic utility ‘U’ to the user, on the top of the energy supplied. I imagine two different markets of energy, with two different games being played. In the market A, small users migrate between suppliers so minimize the differential in prices, and the desired outcome of the game is min[PESU(t) – PEBU(t)]. In the market B, a similar type of migration occurs, just with a different prize in view, namely maximizing the additional economic utility offered by the suppliers of energy to compensate the PESU(t) – PEBU(t) gap. In other words, in the market B, the desired outcome of the game is max{U = f[PESU(t) – PEBU(t)]}. That utility can consist, for example, of claims on the equity of the suppliers, just as in my EneFin concept. Still, we experience the same type of scheme from the part of our usual suppliers. As an example, I can give the contractual scheme that my current supplier, the Polish company Tauron, uses to secure the loyalty of customers. The thing is called ‘Professional 24’ and is a 24/24 emergency service for all that touches to electrical and/or mechanical maintenance in the user’s house. If my dishwasher breaks down, I have the option to call ‘Professional 24’ and they will fix the thing at the cost of spare parts, no labour compensation. All I have to do in order to benefit from that wonder scheme is to sign a fixed-term contract for 2 years. In other words, I pay that high price for small users, and thus I pay a really juicy surplus over the price paid by big users, and in exchange Tauron gives me the opportunity to use those maintenance services at no cost of labour.

Now, I assume that both markets, namely A and B, and their corresponding games can overlap in the same physical market. Thus, there are two games being played in parallel, the min[PESU(t) – PEBU(t)] and the max{U = f[PESU(t) – PEBU(t)]} one. Both are being played by a population of users NU, and that of suppliers MS. A third game, that of status quo, is hanging around as well. The general theoretical questions I ask is the following: « Under what conditions can each of the three games – the min[PESU(t) – PEBU(t)], the max{U = f[PESU(t) – PEBU(t)]}, or the status quo – prevail in the market, and what can be the long-term implications of such prevalence? Should the max{U = f[PESU(t) – PEBU(t)]} game prevail, under what conditions can the U = f[PESU(t) – PEBU(t)] utility find its expression in claims on the equity of suppliers?   ».

The next step consists in translating those general questions into hypotheses, which, in turn, should have two basic attributes. In the first place, a good hypothesis is simple and coherent enough to enable rational classification of all the observable phenomena into two subsets: those conform to the hypothesis, on the one hand, and those which make that hypothesis sound false, on the other hand. Secondly, a good hypothesis is empirically verifiable, i.e. I can devise and apply a rational method of empirical research to check the veracity of what I have hypothesised.

Intuitively, I turn towards one of the most fundamental economic concepts, i.e. that of equilibrium. I hypothesise that there is an equilibrium point, where the outcomes of the min[PESU(t) – PEBU(t)] game are equal to those of the max{U = f[PESU(t) – PEBU(t)]} game, thus min[PESU(t) – PEBU(t)] = max{U = f[PESU(t) – PEBU(t)]}. This is my hypothesis #1. Postulating the existence of an equilibrium is sort of handy, as it gives all the freedom to explore the neighbourhood of that equilibrium.

My second hypothesis goes a bit more in depth of the avenue I am following in my EneFin concept. I assume that the max{U = f[PESU(t) – PEBU(t)]} game makes sort of a framework, within which distinct subgames emerge, oriented on different kinds of that utility ‘U’, like U = {U1, U2, …, Uk}. In that set of utilities, one item is made of claims on the equity of suppliers. I call it Ueq. From there, I can hypothesise in two directions. One way is to postulate a hierarchy inside the U = {U1, U2, …, Uk} set, and Ueq maxing out in that hierarchy, so as Ue  = max{U = f[PESU(t) – PEBU(t)]}.

The other way is to open up, once again, with the concept of equilibrium, and postulate that although, basically, we have U1 ≠ U2 ≠ … ≠ Uk in the U = {U1, U2, …, Uk} set, there is a set of equilibriums, where Ueq = Ui. Going into the equilibrium department, instead of the hierarchy one, is just simpler. I can make like the function of Ueq, as an equation, put it at equality with any other function, and, as long as those identities are solvable at all, Bob’s my uncle, essentially. In that sense, equilibrium, or the absence thereof, is almost self-explanatory. On the other hand, hierarchies need a structuring function, more complex than that of an equilibrium. A structuring function is a set of conditions expressed as inequalities, and I need to nail down quite specifically the conditions for those inequalities being real inequalities. Seen from this perspective, the hypothesis with equilibrium is sort of conducive towards the one with hierarchy.

My mind makes a leap, now, towards that thing of political systems. Playing a game means winning or losing, and one of the biggest prizes to win or lose is a country, i.e. the controlling package of political power in said country. I teach a few curriculums which involve the understanding of political systems, and I did quite a bit of research in that field. Anyway, the hot topic I want to refer to is Brexit, and more exactly the policy paper entitled ‘The future relationship between the United Kingdom and the European Union’, issued by Her Majesty’s Department for Exiting the European Union. The leap I am doing, from that model of the energy market towards Brexit, I am doing it with some method. I started developing on the theory of games, and politics are probably one of the most obvious and straightforward applications thereof.

My students frequently ask me questions like: ‘Why this stupid government does things this way? Couldn’t they be more rational?’. The first thing I am trying to get across as I attempt to answer those questions is that in public governance some strategies just work, and some others just don’t, with little margin of manoeuvre in between. Policies are like complex patterns of behaviour, manifest in complex, intelligent entities called ‘political systems’. In the case of Brexit, the initial game played by the Her Majesty’s government was akin the strategy used by the government of the United States. The United States are signatory member to multilateral, international agreements like the GATT (General Agreement on Tariffs and Trade), or the NAFTA. Still, the dominant institutional contrivance that the US Federal Government uses to design their international economic relations is the bilateral agreement. The logic is simple: in any bilateral agreement, the US are the dominant party to the contract, and they can dictate the conditions. In multilateral schemes, they can be outvoted, and you don’t like being outvoted when you know you have a bigger button than anyone else.

Before I go further, there is an important distinction to grasp, namely that between an international agreement, and a treaty. An agreement is essentially made by executives – usually ministers or Prime Ministers – who sign it on behalf of their respective governments. Parliaments do not need to ratify signed agreements; neither do such agreements require to run a referendum. Agreements remain essentially executive acts, and, as such, they are flexible. Countries can easily back off from those schemes. The easiest way to do it sort of respectably is to vote non-confidence regarding a Prime Minister, and to label what they had done as a series of mistakes. Treaties, on the other hand, are being ratified. Parliaments, presidents, monarchs, and, in the case of the European Union, whole nations voting in referendums, give their final fiat to the signature of an executive. It is bloody hard to pull out of a treaty, as it essentially requires to walk back on your tracks, i.e. to revert the whole sequence of ratifying decisions.

The Britons seem to have bet on a similar horse. They decided to pull out of the European Union – a multilateral treaty, bloody limiting and clumsy to renegotiate – and to govern their economic relations with other countries with a set of bilateral agreements. Each of those bilateral agreements was supposed to be sort of tailored for the specific economic relations between Britain and the given country. Being an agreement, and not a treaty, each such understanding was supposed to be much more manœuvrable than a multilateral treaty.

Mind you, the game was worth playing, as I see it, and still there was a risk. The prize to win was a lot of local business deals, impossible or very hard to achieve under the common rules of the European Union. The big hurdle to jump over, on the way, was the specific geopolitical structure of the EU. If you want to replace your multilateral relations with a set of countries by a range of bilateral relations, you need to look at the hierarchy of the whole tribe. In the European village, we have two big blokes: France and Germany. Negotiating bilateral treaties must have started with them, and there was clearly no point in going and knocking on other doors, as long as these two bilateral schemes were not nailed down and secured.

Without entering into highly speculative details, one thing is sure and certain: this particular step in the Perfect Plan simply didn’t work. Neither France nor Germany expressed any will to play one-on-one with the British government. Instead, they quickly secured beachheads in that sort of international political void being created by Britain pulling out of the EU, and worked towards brutally pushing the Britons against the wall. As a result, today, we have that strange architecture expressed in the ‘Future relationship…’ policy paper, where Britain enters an agreement with the whole of EU, without being a member of the EU anymore.

In theoretical terms, this political episode demonstrates an important trait in games: they are made of successive moves. When you play chess, or any other game with sequenced moves, you have that little voice in your head saying: ‘This is just a game. In real life, no sensible person would wait until their opponent makes a move’. Weelll, yes and no. It is true that in real life we play few games with gentleman’s rules in place. Most real games involve a fair dose of sucker punches, coming from the least expected directions. Still, there is that thing: even if you firmly intend to be the meanest dog in the pack, you need to adapt accordingly, and in order to adapt, you need to observe other players and figure them out. You just need to leave them that little window in time, during which you will be watching them and learning from their actions. This is why in theoretical games we frequently assume sequential moves. It has nothing to do with being fair and honest; it is much more about having to learn by observation.

This is what comes to mind when somebody studies the Brexit policy finally adopted by the government of Her Majesty. ‘Couldn’t they have predicted that…[put whatever between those parentheses]?’. No, they couldn’t. When you want to know the move of another player, you have to make your move in order to force them to make theirs. Once you have made that move, it can be too late to back off. This is probably the biggest difference between mainstream economics and the theory of games. The former assumes the existence of equilibriums, which we can sort of come close to, and adjust, in a series of essentially reversible actions. The theory of games assumes, on the other hand, that most of our actions bring irreversible consequences, as what we do makes other people do things.

After that short distractive excursion into Brexit, I come back to my scientific development on the market of energy. The political distraction allowed me to define something important in any kind of game: a single move. In those three games, which I imagine being played in parallel in the market of energy – the min[PESU(t) – PEBU(t)] game, the max{U = f[PESU(t) – PEBU(t)]} game, and the conservation of status quo – a single move can be defined as what people usually do when dealing with a supplier of energy. My intuition wanders around what I do, actually, and what I do is signing, every two years, a contract with my supplier for another fixed term of two years. Batter that than nothing. I assume that one move, in my energy games, consists in negotiating and signing a fixed-term, two-year contract.

As I define one move in this manner, I intuitively feel like including quantities in the formal expression of those games. Thus, I transform the min[PESU(t) – PEBU(t)] game into min{QSU(t)* [PESU(t) – PEBU(t)]}, and the max{U = f[PESU(t) – PEBU(t)]} into max{U = f[QSU(t)*PESU(t) – PEBU(t)]}. I just remind you that QSU(t) is the typical consumption of energy per one small user, like one household. An explanation seems due. Why have I made that match between ‘one move <=> one 2-year contract’ and the inclusion of quantity consumed into my equations? A contract for 2 years is a mutual promise of supplying-consuming a certain amount of energy.

That QSU(t) can be provisionally identified with the average, individual consumption of energy on one year. Hence, and individual move – contract for two years – amounts to committing to [PESU(t+1)*QSU(t+1)]+[PESU(t+2)*QSU(t+2)]. Such a formal expression allows further rewriting of my two games, namely I have:

Game A: min{QSU(t+1)*[PESU(t+1) – PEBU(t+1)] + QSU(t+2)*[PESU(t+2) – PEBU(t+2)]}

Game B: max{U = f{QSU(t+1)*[PESU(t+1) – PEBU(t+1)] + QSU(t+2)*[PESU(t+2) – PEBU(t+2)] }

With this formulation, my two games are very nearly identical. They both contain an identical aggregate, calculated between the ‘{ }’ parentheses. As I put it a few paragraphs ago, I want to explore my model through the testing of a hypothetical equilibrium point between those two games. This, in turn, amounts to searching a function, which, for a given range of Q and P, can yield a maximal utility out of {QSU(t+1)*[PESU(t+1) – PEBU(t+1)] + QSU(t+2)*[PESU(t+2) – PEBU(t+2)] }, and, in the same time, has at least one intersection point with a function that minimizes the same aggregate.

As I think about it, I need to include transaction costs in the model. I mean, moves in those games consist in signing contracts. A contract implies uncertainty, probability of opportunistic behaviour, and commitment of assets to a specific purpose. In other words, it implies transaction costs, as in: Williamson 1973[1]. I need to wrap my mind around it.

I am consistently delivering good, almost new science to my readers, and love doing it, and I am working on crowdfunding this activity of mine. As we talk business plans, I remind you that you can download, from the library of my blog, the business plan I prepared for my semi-scientific project Befund  (and you can access the French version as well). You can also get a free e-copy of my book ‘Capitalism and Political Power’ You can support my research by donating directly, any amount you consider appropriate, to my PayPal account. You can also consider going to my Patreon page and become my patron. If you decide so, I will be grateful for suggesting me two things that Patreon suggests me to suggest you. Firstly, what kind of reward would you expect in exchange of supporting me? Secondly, what kind of phases would you like to see in the development of my research, and of the corresponding educational tools?

[1] Williamson, O. E. (1973). Markets and hierarchies: some elementary considerations. The American economic review, 63(2), 316-325.

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A project name has come to my mind: EneFin

My editorial

And so I have made a choice. In my last update in French (Plus ou moins les facteurs associés) I finally decided what I want this FinTech business plan to be about. I want it to be about FinTech in the market of energy, and that FinTech should serve to promote renewable energies, possibly in the environment of smart cities. One decision drags others behind it, and so it is happening this time. I have an idea for further scientific research. A title has come to my mind: ‘Fiscalization or monetization of energy?’. I mean, what can governments do in the market of energy, with their budgets vs. the things that monetary systems can change? I have just connected two more dots in my scientific memory. In my book, entitled Capitalism and Political Power, I presented a curious correlation I had found out, namely that between the total amount of political power in the political system, on the one hand, and the amount of capital controlled by said system, on the other hand.

Long story short: the amount of political power can be measured as the number of distinct entities, in the political systems, who can effectively wield a veto against a new policy. The more veto players in the same system, the more political power the system contains. There is even a whole methodology to assess political systems in that line of logic: it is called The Database of Political Institutions (DPI). I used that database to test a simple intuition: each veto player needs control over some capital in order to be actually able to wield his veto power, and so the more veto players, the more capital they need, in total, to play their vetos. My intuition turned out to be correct: I found strong correlation between the metrics used in DPI and the amount of capital held by the public sector in the form of liquid financial assets deducible from the gross public debt. You take one official, fiscal aggregate, namely gross public debt. Then you take another one, called net public debt. You subtract the latter from the former and Bob’s your uncle: you have the residual difference, i.e. the financial assets possible to interpret as claims on the rest of the world. The amount of those claims in the balance sheet of public debt is strongly and positively correlated with the amount of political power in the veto players of the given system.

This is just part of the story. I know, it should have been short a story, but what can I do: I am a scientist. I love telling people things I think they don’t know and I think I know. What? That’s the same as gossiping? Nonsense. Gossiping has much broader an audience than science. This is the difference: science means I tell people things I think I know and I think they don’t know and don’t want to listen to. Anyway, my story is a bit longer than just a short story. Both my research and the one to find in the World Bank’s ‘World Development Report 2017 : Governance and the Law’ suggest that governments are sort of shrinking, across the world and over time. There are less and less real veto players in political systems, more and more facade democracy, and, in economic terms, less and less hold of fiscal policies over the available capital balances in the private sector. Still, in the background, there is another story going on. Monetary systems swell, and I am talking just about the so-called fiat money (i.e. the money blessed by central banks, so as it goes and breeds happily).

So, there is my new thinking. Governments can promote the transition towards renewable energies in two ways: fiscal or monetary. In the fiscal approach, governments take taxes in one hand, subsidies in the other hand, and they can directly meddle inside the energy sector. In the monetary approach, governments basically act so as to make the monetary system as liquid and flexible as possible and then they let the money do the thinking. The scientific work that I am taking on is focused on studying the modalities, opportunities and threats correlated with each of these directions. The business plan I am starting to write is about developing a FinTech project, which, whilst being workable and profitable, will contribute to promoting renewable energies.

By the way, I have just come up with a working name for this project: EneFin.

After the study of three cases – Square Inc., FinTech Group AG and Katipult  – my internal curious ape suggests me to develop four lines of business in EneFin: trade in purchasing power, organisation of payment services, trade in the equity of energy companies, and, finally, trade in their corporate debt. I am going to study each of these four in terms of its economics, legal regime and technology. Trade in purchasing power is probably the closest to my once-much-honed concept of the Wasun (see, for example, Taking refuge during the reign and my other posts from late spring, and summer 2017) and I start with this one. The basic idea is to buy, from the providers of electricity, standardized deeds of purchasing power, like coupons for electricity, and to buy them at a wholesale price, in order to resell them at a retail price. The most elementary economics of the thing begin with the definition of 6 sets: power installations, grid operators, output of energy, deeds of purchasing power, resellers of deeds, consumers of electricity.

The set PR = {pr1, pr2, …, prn} of n power installations encompasses anything able to generate electricity, ranging from household-scale local installations all the way up to big power plants.  This set is immediately, functionally, and imperfectly connected to the set GR = {gr1, gr2, …, gro} of o grid operators, i.e. the resellers of energy. Note that functional connection between the sets PR and GR largely depends on the regulatory regime in force. If the law allows each power installation to sell directly its power, any t-th element in the PR set can become identical an element in the GR set. As the law imposes limitations on direct sales of electricity, the GR set becomes more rigid in its size and structure.

Both the PR, and the GR set are functionally connected to the set of output, or Q, made of m kilowatt hours; Q = {kWh1, kWh2, …, kWhm}. Note two things about m. Firstly, m is a compound value: it is the arithmetical product of a constant number of hours in the year (basically 24*365 = 8760, 8784 in an odd year), on the one hand, and the total capacity of kilowatts available. Secondly, m is really big, and as all big sets, it gains greatly in its overall workability when split into smaller, local subsets. By the way, as I look at that Q, I realize how much fun I will provide my French readers with, when taking on the topic in my updates written in French. Who speaks French knows what I am talking about. Still, Q is the sacro-saint symbol of quantity in economics, so let there be fun when fun is possible.

The Q set is, in turn, connected to a set of deeds in purchasing power. I call this set D (I know, not very original, plainly reproduces the initial of ‘deeds’, but I just want to get on with the thing), and I assume it is composed of l deeds, and so I have D = {d1, d2, …, dl}. Those deeds can have various forms. They can be like purchasing coupons, or they could be fancily made into a cryptocurrency. They can be futures contracts as well, and even options, if you are really keen on financial engineering. Sorting out this aspect is a separate chapter in my work, still one guiding light shines in the darkness, and this is not a train coming from the opposite direction: FinTech is supposed to minimize transaction costs.

Question: which legal form(s) of purchasing deeds for electricity allow(s) the lowest transaction costs? Options, tokens of cryptocurrency etc.? Answer: the one which combines the lowest uncertainty as for its price with the best shielding against opportunistic behaviour in other market participants, as well as with the greatest liquidity in the assets. I know, this answer looks more like another question and this is not exactly the way actual answers should look like. What do you want, I am a gentleman of a certain age, like half a century, and I advance forward with the due gravitas.

Question: what is the exact relationship between Q and D, thus between their respective sizes m and l? Answer: it depends. It depends on the overall liquidity of the market, i.e. on the capacity of your average kilowatt hour in the Q to be assigned a sibling deed D. It is exactly like humans: you can be an only child, you can have one twin sibling, or you can have a lot of brothers, sisters and cousins. A given kilowatt hour in the Q can be an only child, i.e. not to have any corresponding, tradable deed in the D. If at least some kilowatt hours in the Q are such lonely wolves, this is the case of low, de facto inexistent liquidity in the Q, and l < m. If I ramp it up like by one level, and I give each kilowatt hour in the Q one corresponding, twin deed of purchasing power, like one token of a cryptocurrency, in the D, I have l = m and my Q is sort of liquid.

We can ramp it up even further, and give each kilowatt hour in the Q many siblings in the D, like a futures contract, which can be the base security for an option, and both can become tokenized in a Blockchained network of cryptocurrency. On the top of that, you can add a tradable insurance as for the available capacity in each given kWh, i.e. insurance claimable in case you don’t actually have your kilowatt hour in the time and place you can expect it with the purchasing deed you hold. Insane? Perhaps, but this is how financial markets have been working since there is historical record of how they work. Anyway, in such case, the Q becomes hyper-liquid, and l(D) is waaay bigger than m(Q) (the triple ‘a’ in ‘waaay’ is an emphatic way to show how big the way is).

Four sets out of six laid nicely on the table, there are two more. So, the resellers’ set, or R = {r1, r2, …, rk} handles the whole purchasing deeds business. The elements of R move around the elements of D. The R set is there, in my line of thinking, as a formal approach to competition in the business planned for EneFin. My EneFin project would belong to R, and, let’s face it: there are and will be others in the set. As a matter of fact, when I sign a contract for electricity with my local provider (mine is Tauron, one of the big Polish distributors of electricity), the company actually acts as a reseller of purchasing deeds, to a large extent. They sign a contract of their own with power plants, and they commit to buy a certain amount of kWh (although at this scale, we are rather talking about gigawatt hours), and this commitment is largely a ‘use-it-and-resell-it-anyway-pay-for-it’ type. The R set is largely overlapping with the GR set (that of grid operators). The EneFin business, to the extent that it goes into trading those purchasing deeds for the market of electricity, will enter both into competition and cooperation with the resellers of energy.

Finally, the set of consumers, or end-users of electricity: CN = {cn1, cn2, …, cnz}. Right, now, what about those sets? Why have I just defined them? It is coming back, just wait a minute. I know! I remember now! I want to translate the business concept of EneFin into a functional description of the accompanying digital technology. Thinking in terms of sets helps in that respect. So, out of those 6 sets, EneFin would operate most of all the D = {d1, d2, …, dl} set of purchasing deeds. That would be the core dataset of the whole system. Each t-th d in the D will have a vector of characteristics, and the most important among them are: the hour of the year (i.e. one of the 8760 in even years and 8784 in odd years), the point(s) of supply that accept the given deed as payment, the amount of energy assigned to the deed. I basically thought about making the last one constant and equal to 1 kWh.

Now, a short explanation as for the notion of the ‘point of supply’. Electricity is distributed in a complex network. The part of network which just channels power to its end users is commonly designated as ‘the grid’. Inside the grid sensu largo, we can distinguish the high-voltage grid of distribution, which connects to local grids of supply, which, in turn, operate in medium-voltage and low-voltage. The grids of supply attach to the end users via the points of supply. Simplifying the thing a bit, every electric counter is a point of supply. Each such final point of supply is functionally connected, and mechanically wired, to its nearest converter in the grid. I would like the EneFin purchasing deeds to be valid means of payment at every point of supply in the given national power grid. That would be one of the characteristics of nearly-perfect liquidity in those purchasing deeds. Still, the market of electricity is largely feudal: it is full of imperfectly monopolistic contracts, which bind the end-users to their distributors by the means of fixed-term contracts endowed with very heavy contractual penalties for premature termination. How would those local feuds of the energy market see those purchasing deeds I want my EneFin project to trade? Good question. I don’t know the answer.

I have a general thought to share, sort of a punchline in my today’s update. Last spring and summer, when I was coining up the concept of the Wasun, or cryptocurrency attached to the market of renewable energies, I was struggling. I had the impression to bang my head against a brick wall, in intellectual terms. Now, working on that EneFin project seems easy, and now, I know why: last year I had been trying to invent something economically perfect and now, I am putting together the concept of a financial product, which, in turn, has an opportunity to pitch something really sound. This is one of those deep understandings I developed over the last year: financial markets, FinTech included, are like an endocrine system, where each financial product is like a hormone. The bottom line in finance is to create something that works. As long as it works, it gives a chance to channel human effort into something new and maybe useful.

I am consistently delivering good, almost new science to my readers, and love doing it, and I am working on crowdfunding this activity of mine. You can support my research by donating directly, any amount you consider appropriate, to my PayPal account. You can also consider going to my Patreon page and become my patron. If you decide so, I will be grateful for suggesting me two things that Patreon suggests me to suggest you. Firstly, what kind of reward would you expect in exchange of supporting me? Secondly, what kind of phases would you like to see in the development of my research, and of the corresponding educational tools?