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.
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