I keep developing on a few topics in parallel, with a special focus on two of them. Lessons in economics and management which I can derive for my students, out of my personal experience as a small investor in the stock market, for one, and a broader, scientific work on the civilizational role of cities and our human collective intelligence, for two.
I like starting with the observation of real life, and I like ending with it as well. What I see around gives me the initial incentive to do research and makes the last pitch for testing my findings and intuitions. In my personal experience as investor, I have simply confirmed an initial intuition that giving a written, consistent and public account thereof helps me nailing down efficient strategies as an investor. As regards cities and collective intelligence, the first part of that topic comes from observing changes in urban life since COVID-19 broke out, and the second part is just a generalized, though mild an intellectual obsession, which I started developing once I observed the way artificial neural networks work.
In this update, I want to develop on two specific points, connected to those two paths of research and writing. As far as my investment is concerned, I am seriously entertaining the idea of broadening my investment portfolio in the sector of renewable energies, more specifically in the photovoltaic. I can notice a rush on the solar business in the U.S. I am thinking about investing in some of those shares. I already have, and have made a nice profit on the stock of First Solar (https://investor.firstsolar.com/home/default.aspx ) as well as on that of SMA Solar (https://www.sma.de/en/investor-relations/overview.html ). Currently, I am observing three other companies: Vivint Solar (https://investors.vivintsolar.com/company/investors/investors-overview/default.aspx ), Canadian Solar (http://investors.canadiansolar.com/investor-relations ), and SolarEdge Technologies (https://investors.solaredge.com/investor-overview ). Below, I am placing the graphs of stock price over the last year, as regards those solar businesses. There is something like a common trend in those stock prices. March and April 2020 were a moment of brief jump upwards, which subsequently turned into a shy lie-down, and since the beginning of August 2020 another journey into the realm of investors’ keen interest seems to be on the way.
Before you have a look at the graphs, here is a summary table with selected financials, approached as relative gradients of change, or d(x).
|Change from 01/01/2020 to 31/08/2020|
|Company||d(market cap)||d(assets)||d(operational cash-flow)|
|First Solar||+23,9%||-6%||Deeper negative: – $80 million|
|SMA Solar||+27,5%||-10%||Deeper negative: -€40 million|
|Vivint Solar||+362%||+11%||Deeper negative: – $9 million|
|SolarEdge||+98%||0||+ $50 million|
|Canadian Solar||+41%||+4%||+ $90 million|
There are two fundamental traits of business models which I am having a close look at. Firstly, it is the correlation between changes in market capitalization, and changes in assets. I am checking if the solar businesses I want to invest in have their capital base functionally connected to the financial market. Looks a bit wobbly, as for now. Secondly, I look at current operational efficiency, measured with operational cash flow. Here, I can see there is still a lot to do. Here is the link to You Tube video with all that topic developed: Business models in renewable energies #3 Solar business and investment opportunities [Renew BM 3 2020-09-06 09-20-30 ; https://youtu.be/wYkW5KHQlDg ].
Those business models seem to be in a phase of slow stabilization. The industry as a whole seems to be slowly figuring out the right way of running that PV show, however the truly efficient scheme is still to be nailed down. Investment in those companies is based on reasonable trust in the growth of their market, and in the positive impact of technological innovation. Question: is it a good move to invest now? Answer: it is risky, but acceptably rational; once those business models become really efficient, the industry will be in or close to the phase of maturity, which, in turn, does not really allow expecting abnormally high return on investment.
This is a very ‘financial’, hands-off approach to business models. In this case, business models of those photovoltaic businesses matter to me just to the extent of being fundamentally predictable. I don’t want to run a solar business, I just want to have elementary understanding of what’s going on, business-wise, to make my investment better grounded. Looking from inside a business, such an approach is informative about the way that a business model should ‘speak’ to investors.
At the end of the day, I think I am most likely to invest in SolarEdge. It seems to have all the LEGO blocks in place for a good opening. Good cash flow, although a bit sluggish when it comes to real investment.
As regards COVID-19 and cities, I am formulating the following hypothesis: COVID-19 has awakened some deeply rooted cultural patterns, which date back to the times of high epidemic risk, long before vaccines, sanitation and widespread basic healthcare. Those patterns involve less spatial mobility in the population, and social interactions within relatively steady social circles of knowingly healthy people. As a result, the overall frequency of social interactions in cities is likely to decrease, and, as a contingent result, the formation of new social roles is likely to slow down. Then, either digital technologies take over the function of direct social interactions and new social roles will be shaping themselves via your average smartphone, with all the apps it is blessed (haunted?) with, or the formation of new social roles will slow down in general. In that last case, we could have hard times with keeping up our pace of technological change. Here is the link to You Tube video which summarizes what is written below: Urban Economics and City Management #4 COVID and social mobility in cities [ Cities 4 2020-09-06 09-43-06 ; https://youtu.be/m3FZvsscw7A ].
I want to gain some insight into the epidemiological angle of that claim, and I am passing in review some recent literature. I start with: Gatto, M., Bertuzzo, E., Mari, L., Miccoli, S., Carraro, L., Casagrandi, R., & Rinaldo, A. (2020). Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures. Proceedings of the National Academy of Sciences, 117(19), 10484-10491 (https://www.pnas.org/content/pnas/117/19/10484.full.pdf ). As it is usually the case, my internal curious ape starts paying attention to details which could come as secondary for other people, and my internal happy bulldog follows along and bites deep into those details. The little detail in this specific paper is a parameter: the number of people quarantined as a percentage of those positively diagnosed with Sars-Cov-2. In the model developed by Gatto et al., that parameter is kept constant at 40%, which is, apparently, the average level empirically observed in Italy during the Spring 2020 outbreak. Quarantine is strict isolation between carriers and (supposedly) non-carriers of the virus. Quarantine can be placed on the same scale as basic social distancing. It is just stricter, and, in quantitative terms, it drives much lower the likelihood of infectious social interaction. Gatto el al. insist that testing effort and quarantining are essential components of collective defence against the epidemic. I generalize: testing and quarantine are patterns of collective behaviour. I check whether people around me are carriers or not, and then I split them into two categories: those whom I strongly suspect to host and transmit Sars-Cov-2, and all the rest. I define two patterns of social interaction with those two groups: very restrictive with the former, and cautiously bon vivant with the others (still, no hugging). As the technologies of testing will be inevitably diffusing across the social landscape, that structured pattern is likely to spread as well.
Now, I pay a short intellectual visit to Jiang, P., Fu, X., Van Fan, Y., Klemeš, J. J., Chen, P., Ma, S., & Zhang, W. (2020). Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour. Journal of Cleaner Production, 123673 https://doi.org/10.1016/j.jclepro.2020.123673 . Their methodology is based on correlating spatial mobility of cars in residential areas of Singapore with the risk of infection with COVID-19. A 44,3% ÷ 55,4% decrease in the spatial mobility of cars is correlated with a 72% decrease in the risk of social transmission of the virus. I intuitively translate it into geometrical patterns. Lower mobility in cars means a shorter average radius of travel by the means of available urban transportation. In the presence of epidemic risk, people move across a smaller average territory.
In another paper (or rather in a commented dataset), namely in Pepe, E., Bajardi, P., Gauvin, L., Privitera, F., Lake, B., Cattuto, C., & Tizzoni, M. (2020). COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown. Scientific data, 7(1), 1-7. https://www.nature.com/articles/s41597-020-00575-2.pdf?origin=ppub , I find an enlarged catalogue of metrics pertinent to spatial mobility. That paper, in turn, lead me to the functionality run by Google: https://www.google.com/covid19/mobility/ . I went through all of it a bit cursorily, and I noticed two things. First of all, countries are strongly idiosyncratic in their social response to the pandemic. Still, and second of all, there are common denominators across idiosyncrasies and the most visible one is cyclicality. Each society seems to have been experimenting with the spatial mobility they can afford and sustain in the presence of epidemic risk. There is a cycle experimentation, around 3 – 4 weeks. Experimentation means learning and learning usually leads to durable behavioural change. In other words, we (I mean, homo sapiens) are currently learning, with the pandemic, new ways of being together, and those ways are likely to incrust themselves into our social structures.
The article by Kraemer, M. U., Yang, C. H., Gutierrez, B., Wu, C. H., Klein, B., Pigott, D. M., … & Brownstein, J. S. (2020). The effect of human mobility and control measures on the COVID-19 epidemic in China. Science, 368(6490), 493-497 (https://science.sciencemag.org/content/368/6490/493 ) shows that without any restrictions in place, the spatial distribution of COVID-19 cases is strongly correlated with spatial mobility of people. With restrictions in place, that correlation can be curbed, however it is impossible to drive down to zero. In plain human, it means that even as stringent lockdowns as we could see in China cannot reduce spatial mobility to a level which would completely prevent the spread of the virus.
By the way, in Gao, S., Rao, J., Kang, Y., Liang, Y., & Kruse, J. (2020). Mapping county-level mobility pattern changes in the United States in response to COVID-19. SIGSPATIAL Special, 12(1), 16-26 (https://arxiv.org/pdf/2004.04544.pdf ), I read that the whole idea of tracking spatial mobility with people’s personal smartphones largely backfired because the GDS transponders, installed in the average phone, have around 20 metres of horizontal error, on average, and are easily blurred when people gather in one place. Still, whilst the idea went down the drain as regards individual tracking of mobility, smartphone data seems to provide reliable data for observing entire clusters of people, and the way those clusters flow across space. You can consult Jia, J. S., Lu, X., Yuan, Y., Xu, G., Jia, J., & Christakis, N. A. (2020). Population flow drives spatio-temporal distribution of COVID-19 in China. Nature, 1-5. (https://www.nature.com/articles/s41586-020-2284-y?sf233344559=1) .
Bonaccorsi, G., Pierri, F., Cinelli, M., Flori, A., Galeazzi, A., Porcelli, F., … & Pammolli, F. (2020). Economic and social consequences of human mobility restrictions under COVID-19. Proceedings of the National Academy of Sciences, 117(27), 15530-15535 (https://www.pnas.org/content/pnas/117/27/15530.full.pdf ) show an interesting economic aspect of the pandemic. Restrictions in mobility give the strongest economic blow to the poorest people and to local communities marked by relatively the greatest economic inequalities. Restrictions imposed by governments are one thing, and self-imposed limitations in spatial mobility are another. If my intuition is correct, namely that we will be spontaneously modifying and generally limiting our social interactions, in order to protect ourselves from COVID-19, those changes are likely to be the fastest and the deepest in high-income, low-inequality communities. As income decreases and inequality rises, those adaptive behavioural modifications are likely to weaken.
As I am drawing a provisional bottom line under that handful of scientific papers, my initial hypothesis seems to hold. We do modify, as a species, our social patterns, towards more encapsulated social circles. There is a process of learning taking place, and there is no mistake about it. That process of learning involves a downwards recalibration in the average territory of activity, and smart selection of people whom we hang out with, based on what we know about the epidemic risk they convey. This is a process of learning by trial and error, and it is locally idiosyncratic. Idiosyncrasies seem to be somehow correlated with differences in wealth. Income and accumulated capital visibly give local communities an additional edge in the adaptive learning. On the long run, economic resilience seems to be a key factor in successful adaptation to epidemic risk.
Just to end up with, here you have an educational piece as regards Business models in the Media Industry #4 The gaming business[ Media BM 4 2020-09-02 10-42-44; https://youtu.be/KCzCicDE8pc]. I study the case of CD Projekt (https://www.cdprojekt.com/en/investors/ ), a Polish gaming company, known mostly for ‘The Witcher’ game and currently working on the next one, Cyberpunk, with Keanu Reeves giving his face to the hero. I discover a strange business model, which obviously has hard times to connect with the creative process at the operational level. As strange as it might seem, the main investment activity, for the moment, consists in terminating and initiating cash bank deposits (!), and one of the most important operational activities is to push further in time the moment of officially charging customers with some economically due receivables. On the top of all that, those revenues deferred into the future are officially written in the balance sheet as short-term liabilities, which CD Projekt owes to…whom exactly?
I continue developing my ideas. Most people do, all the time, actually: they keep developing their own ideas, and other people’s ideas, and, on the whole, we just develop our ideas.
Good. Linguistic warm up done, I go to work. I continue what I started in my last update ( Steady inflow of assets and predictable rules ): a workable business concept for restarting local economies after COVID-19 lockdowns, and during the ongoing pandemic. Last time, I studied the early days of the Bitcoin, in the hope of understanding how a completely new economic scheme emerges. As hope crystalizes into something more structured, ideas emerge. I am going to make a quick sketch of what I have come up with, and then I will try give it some shine by using my observations as regards the early infancy of the Bitcoin.
As I observe the present situation, I can see that local communities both need and accumulate some typical goods and assets. The most immediately needed, and semi-instinctively accumulated goods are those serving personal protection and hygiene: gloves, facial protections (masks, covers, googles etc.), scrubs and aprons, bonnets, soap, ethanol-based sanitizers. I wonder, and, honestly, I would gladly do with the consultation of an epidemiologist, to what extent an abundant use of those hygienic goods can be substitute to social distancing. I mean, to what extent can we restart social interactions with adequate protection?
Anyway, I am quite confident that local communities will be accumulating what I provisionally call ‘epidemic assets’. The challenge consists in using that phenomenon, and those assets, so as to give some spin to economies brought down by lockdowns.
Now, I am using basic laws of economics. Whenever and wherever some stock of medical supplies will be accumulated, it will be inventories, i.e. circulating assets subject to storage and endowed with direct economic utility, but not to amortization. Sooner or later, substantial inventories of anything attract the company of some fixed assets, such as buildings, equipment, and intellectual property, on the one hand, as well as the company of other circulating assets (e.g. receivable claims on third parties), and, finally, the company of JOBS, which are the key point here.
Now, let’s imagine the following scenario. A local community, e.g. local hospital plus local city council, need to have a given amount of ‘epidemic assets’ stored and ready to use, just to keep the local epidemic situation under control. They need those epidemic assets, yet, as the local economy is stricken by epidemic lockdown, they don’t have enough money (or no money at all) to pay for those assets. Here starts the gamble. The local community offers the suppliers of epidemic assets to be paid in tokens of a virtual currency, where each token corresponds to a futures contract with claims on a future stock of epidemic assets.
The central idea is that with the virus around, everybody will have a keen interest in having enforceable claims on epidemic assets. That keen interest will be driven by two motives. In the first place, many people will need to use those epidemic assets like directly and personally. Secondly, those assets will be valuable, and futures contracts on them will have monetizable, financial value. It should be possible to create a circulation of those tokens (futures), where the direct supplier of epidemic assets can use those tokens to pay their own suppliers of intermediate goods, as well as to pay a part of the payroll. Those whom he pays will either consume those futures to grab some epidemic assets, or make those futures circulate further.
As those tokenized futures contracts on epidemic assets get developed and put in circulation, we can use the relatively recent invention called ‘smart contract’. A complex contract can be split into separate component parts, like LEGO blocks, each endowed with a different function. Users can experiment with each part separately, and the actual contracts they sign and trade are compound legal schemes. For now, I can see 3 principal LEGO blocks. The first one is the exact substance of the claim incorporated in the tokenized contracts. Futures contracts have this nuance in them: they can embody claims on a certain quantity of specified goods or assets, e.g. 100 kg of something, or on a nominal financial value of those goods or assets, like $100 worth of something. Maturity of the claim is another thing. Futures contracts have a time horizon in them: 1 month, 6 months, 12 months etc. In this specific case, maturity of claims is the same as the lifecycle of one tokenized contract, and, honestly, if this scheme is applied in real life, we will be sailing uncharted waters. Those tokens are supposed to keep local economies going, and therefore they’d better have a long lifecycle. Hardly anyone would trust quasi – monetary tokens with a lifespan of 3 months. On the other hand, the longest futures I have seen, like those on coffee or wheat, stretch over 6 months, rarely longer. Here comes the third building block, namely convertibility of the claim. If we want the system to work smoothly, i.e. inspire trust in exchange, and be realistic in the same time, we can make those tokens convertible into something else. They could convert into similar tokens, just valid over the next window of trade, or into something else, e.g. shares in the equity of newly built local hospitals. Yes, we are certainly going to build more of them, trust me.
Building blocks in hand, we start experimenting. Looking at the phases I distinguished in the early infancy of the Bitcoin (once again, you can look up Steady inflow of assets and predictable rules ), I see three essential steps in the development of this scheme. The first step would consist in creating a first, small batch of those tokenized contracts and test them in deals with whoever would like to try. The experience of the Bitcoin shows that once the thing catches on (and IF the thing catches on), i.e. once and if there are any businesspeople interested, it should spread pretty quickly. Then comes the second phase, that of building large portfolios of those tokenized contracts in a relatively small and select community, sort of Illuminati of medical supplies. In that phase, which is likely to be pretty long, like 1,5 year, said Illuminati will be experimenting with the exact smart structure those contracts, so as to come up with workable, massively reproducible patterns for the third phase, that of democratization. This is when the already hammered and hardened contractual patterns in those tokens will spread to a larger population. Individual balances of those tokens are likely to shrink in that third phase and become sort of standardized. This could be the moment, when our tokenized contracts can start being used as a vehicle for saving economic value over time, and it looks like a necessary condition for driving it out of its so-far autonomous, closed market into exchangeability against money.
That would be all for today. If you want to contact me directly, you can mail at: email@example.com . If anyone wants to bounce this ball off their bat, you are welcome. I am deeply convinced that we need to figure out some new s**t. Our world is changing, and we’d better make that change liveable.
Clink! The coin dropped… I have been turning that conceptual coin between my synapses for the last 48 hours, and here it is. I know what I have been thinking about, and what I want to write about today. I want to study the possible ways to restart business and economy in the midst of the COVID-19 pandemic.
There is a blunt, brutal truth: the virus will stay with us until we massively distribute an efficient vaccine against it, and that is going to take many months, most probably more than a year. Until then, we need to live our lives, and we cannot live them in permanent lockdown. We need to restart, somehow, our socio-economic structures. We need to overcome our fears, and start living in the presence of, and in spite of danger.
Here come three experiences of mine, which sum up to the financial concept I am going to expose a few paragraphs further. The first experience is that of observing a social project going on in my wife’s hometown, Starachowice, Poland, population 50 000. The project is Facebook-named ‘The Visible Hand’ (the original Polish is: Widzialna Ręka), and it emerged spontaneously with the COVID-19 crisis. I hope to be able to present the full story of those people, which I find truly fascinating, and now, I just give a short glimpse. That local community has created, within less than two weeks, something like a parallel state, with its supply system for the local hospital, and for people at risk. They even go into developing their own technologies of 3D printing, to make critical medical equipment, such as facial masks. Yesterday, I had a phone conversation with a friend, strongly involved in that project, and my head still resonates with what he said: ‘Look, the government is pretty much lost in all that situation. They pretend a lot, and improvise a lot, and it is all sort of more pretending than actually doing things. Our local politicians either suddenly evaporated, or make clumsy, bitchy attempts to boost their popularity in the midst of all that s**t. But people… Man, people are awesome. We are doing together things that our government thinks it is impossible to do, and we are even sort of having fun with it. The sense of community is nothing short of breath-taking’.
My second experience is about the stock market. If you have been following my updates since the one entitled ‘Back in the game’, you know that I decided to restart investing in the stock market, which I had undertaken to do just before the s**t hit the fan, a few weeks ago. Still, what I am observing right now, in the stock market, is something like a latent, barely contained energy, which just seeks any opportunity to engage into. Investors are really playing the game. Fear, which I could observe two weeks ago, has almost vanished from the market. Once again, there is human energy to exploit positively.
There is energy in people, but it is being locked down, with the pandemic around. The big challenge is to restart it. Right now, many folks lose their jobs, and their small businesses. It is important to create substantial hope, i.e. hope which can be turned into action. Here comes my third experience, which is that of preparing a business plan for an environmental project, which I provisionally call Energy Ponds (see Bloody hard to make a strategy and The collective archetype of striking good deals in exports for latest developments). As I prepare that business plan, I keep returning to the conclusion that I need some sort of financial scheme for situations when a local community, willing to implement the technology I propose, is short of capital and needs to sort of squeeze money out of the surrounding landscape.
Those three experiences of mine, taken together, lead me back to something I studied 3 years ago, when I was taking my first, toddler’s steps in scientific blogging: the early days of the Bitcoin. Today, the Bitcoin is the big, sleek predator of financial markets, yet most people have forgotten how that thing was born. It was an idea for safe financial transactions, based on an otherwise old concept of financial law called ‘endorsement of debt’, implemented in the second year of the big financial crisis, i.e. in 2009, to give some liquidity to small networks of just as small local businesses. Initially, for more than 18 first months of existence, the Bitcoin was a closed system of exchange, without any interface with any established currency. As far as I know, it very much saved the day for many small businesses, and I want to study the pattern of success, so as to see how it can be reproduced today for restarting business in the context of pandemic.
Before I go analytical, two general remarks. Firstly, there is plenty of folks who pretend having the magical recipe for the present s**t we are waist-deep in. I start from the assumption that we have no fresh, general experience of pandemics, and pretending to have figured the best way out is sheer bullshit. Still, we need to explore and to experiment, and this is very much the spirit I pursue.
Secondly, the Bitcoin is a cryptocurrency, based on the technology designated as Blockchain. What I want to take away is the concept of virtual financial instrument focused on liquidity, rather than the strictly spoken technology. Of course, platforms such as Ethereum can be used for the purpose I intend to get across, here below, still they are just an instrumental option.
Three years ago, I used data from https://www.quandl.com/collections/markets/bitcoin-data, which contains the mathematical early story of what has grown, since, into the father of all cryptocurrencies, the Bitcoin. I am reproducing this story, now, so as to grasp a pattern. Let’s walse. I am focusing on the period, during which the Bitcoin started, progressively acquired any exchangeable value against the US dollar, and finished by being more or less at 1:1 par therewith. That period stretches from January 3rd, 2009 until February 10th, 2011. You can download the exact dataset I work with, in the Excel format, from this link:
Before I present my take on that early Bitcoin story, a few methodological remarks. The data I took originally contains the following variables: i) total number of Bitcoins mined, ii) days destroyed non-cumulative, iii) Bitcoin number of unique addresses used per day, and iv) market capitalization of the Bitcoin in USD. On the basis of these variables, I calculated a few others. Still, I want to explain the meaning of those original ones. As you might know, Bitcoins were initially mined (as far as I know, not anymore), i.e. you could generate 1 BTC if you solved a mathematical riddle. In other words, the value you had to bring to the table in order to have 1 BTC was your programming wit plus computational power in your hardware. With time, computational power had been prevailing more and more. The first original variable, i. e. total number of Bitcoins mined, is informative about the total real economic value (computational power) brought to the network by successive agents joining it.
Here comes the first moment of bridging between the early Bitcoin and the present situation. If I want to create some kind of virtual financial system to restart, or just give some spin to local economies, I need a real economic value as gauge and benchmark. In the case of Bitcoin, it was computational power. Question: what kind of real economic value is significant enough, right now, to become the tool for mining the new, hypothetical virtual currency? Good question, which I don’t even pretend to have a ready-made answer to, and which I want to ponder carefully.
The variable ‘days destroyed non-cumulative’ refers to the fact that Bitcoins are crypto-coins, i.e. each Bitcoin has a unique signature, and it includes the date of the last transaction made. If I hold 1 BTC for 2 days, and put it in circulation on the 3rd day, on the very same 3rd day I destroy 2 days of Bitcoins. If I hold 5 Bitcoins for 7 days, and kick them back into market on the 8th day, I destroy, on that 8th day, 5*7 = 35 days. The more days of Bitcoin I destroy on the given day of transactions, the more I had been accumulating. John Maynard Keynes argued that a true currency is used both for paying and for saving. The emergence of accumulation is important in the shaping of new financial instruments. It shows that market participants start perceiving the financial instrument in question as trustworthy enough to transport economic value over time. Note: this variable can take values, like days = 1500, which seem absurd at the first sight. How can you destroy 1500 days in a currency born like 200 days ago? You can, if you destroy more than one Bitcoin, held for at least 1 day, per day.
The third original variable, namely ‘Bitcoin number of unique addresses used per day’, can be interpreted as the number of players in the game. When you trade Bitcoins, you connect to a network, you have a unique address in that network, and your address appears in the cumulative signature that each of the Bitcoins you mine or use drags with it.
With those three original variables, I calculate a few coefficients of mine. Firstly, I divide the total number of Bitcoins mined by the number of unique addresses, on each day separately, and thus I obtain the average number of Bitcoins held, on that specific day, by one average participant in the network. Secondly, I divide the non-cumulative number of days destroyed, on the given day, by the total number of Bitcoins mined, and present in the market. The resulting quotient is the average number of days, which 1 Bitcoin has been held for.
The ‘market capitalization of the Bitcoin in USD’, provided in the original dataset from https://www.quandl.com/collections/markets/bitcoin-data, is, from my point of view, an instrumental variable. When it becomes non-null, it shows that the Bitcoin acquired an exchangeable value against the US dollar. I divide that market capitalization by the total number of Bitcoins mined, and I thus I get the average exchange rate of Bitcoin against USD.
I can distinguish four phases in that early history of the Bitcoin. The first one is the launch, which seems to have taken 6 days, from January 3rd, 2009 to January 8th, 2009. There were practically no players, i.e. no exchange transactions, and the number of Bitcoins mined was constant, equal to 50. The early growth starts on January 9th, 2009, and last just for 3 days, until January 11th, 2009. The number of Bitcoins mined grows, from 50 to 7600. The number of players in the game grows as well, from 14 to 106. No player destroys any days, in this phase. Each Bitcoin mined is instantaneously put in circulation. The average amount of Bitcoins per player evolves from 50/14 = 3,57 to 7600/106 = 71,7.
On January 12th, 2009, something changes: participants in the network start (timidly) to hold their Bitcoins for at least one day. This is how the phase of accelerating growth starts, and will last for 581 days, until August 16th, 2010. On the next day, August 17th, the first Bitcoins will get exchanged against US dollars. On that path of accelerating growth, the total number of Bitcoins mined passes from 7600 to 3 737 700, and the daily number on players in the network passes from an average around 106 to about 500 a day. By the end of this phase, the average amount of Bitcoins per player reaches 7475,4. Speculative positions (i.e. propensity to save Bitcoins for later) grow, up to an average of about 1500 days destroyed per address.
Finally, the fourth stage of evolution is reached: entry into the financial market, when we pass from 1 BTC = $0,08 to 1 BTC = $1. This transition from any exchange rate at all to being at par with the dollar takes 189 days, from August 17th, 2010 until February 10th, 2011. The total number of Bitcoins grows at a surprisingly steady rate, from 3 737 700 to about 5 300 000, whilst the number of players triples, from about 500 to about 1 500. Interestingly, in this phase, the average amount of Bitcoins per player decreases, from 7475,4 to 3 533,33. Speculative positions grow steadily, from about 1500 days destroyed per address to some 2 400 days per address.
Below, you will find graphs with a birds-eye view of the whole infancy of the Bitcoin. Further below, after the graphs, I try to give some closure, i.e. to guess what we can learn from that story, so as to replicate it, possibly, amid the COVID-19 crisis.
My first general conclusion is that the total number of Bitcoins mined is the only variable, among those studied, which shows a steady, quasi linear trend of growth. It is not really exponential, more sort of a power function. The total number of Bitcoins mined corresponds, in the early spirit of this cryptocurrency, to the total computational power brought to the game by its participants. The real economic value pumped into the new concept was growing steadily, linearly, and to an economist, such as I am, it suggests the presence of exogenous forces at play. In other words, the early Bitcoin was not growing by itself, through sheer enthusiasm of its early partisans. It was growing because some people saw real value in that thing and kept bringing assets to the line. It is important in the present context. If we want to use something similar to power the flywheels of local markets under the COVID-19 restrictions, we need some people to bring real, productive assets to the game, and thus we need to know what those key assets should be. Maybe the capacity to supply medical materials, combined with R&D potential in biotech and 3D printing? These are just loose thoughts, as I observe the way that events are unfolding.
My second conclusion is that everything else I have just studied is very swingy and very experimental. The first behavioural transition I can see is that of a relatively small number of initial players experimenting with using whatever assets they bring to the table in order to generate a growing number of new tokens of virtual currency. The first 7 – 8 months in the Bitcoin show the marks of such experimentation. There comes a moment, when instead of playing big games in a small, select network, the thing spills over into a larger population of participants. What attracts those new ones? As I see it, the attractive force consists in relatively predictable rules of the game: ‘if I bring X $mln of assets to the game, I will have Y tokens of the new virtual currency’, something like that.
Hence, what creates propitious conditions for acquiring exchangeable value in the new virtual currency against the established ones, is a combination of steady inflow of assets, and crystallization of predictable rules to use them in that specific scheme.
I can also see that people started saving Bitcoins before these had any value in dollars. It suggests that even in a closed system, without openings to other financial markets, a virtual currency can start giving to its holders a sense of economic value. Interesting.
That would be it for today. If you want to contact me directly, you can mail at: firstname.lastname@example.org .
Life can be full of surprises, like really. When I was writing my last update, on March 7th and 8th, the one entitled ‘Lettres de la zone rouge’, I was already writing about the effects of coronavirus in the stock market. Yet, it was just sort of an external panic, back then. External to me, I mean. Now, I am in, as we all are in Europe. Now, more than ever before, I use blogging, i.e. writing and publishing content, as a device for putting order in my own thoughts.
At the university, I had to switch to online teaching, and I am putting a lot of myself into preparing good stuff for students. By the way, you can assess the quality of my material by yourself. I have two lectures on Vimeo, in a course entitled ‘Fundamentals of Finance’. Both are password-locked and the password is ‘akademia’. Pay attention to the ‘k’. Not ‘academia’, but ‘akademia’. Lecture 1 is available at https://vimeo.com/398464552 and Lecture 2 fires on
I can’t help philosophizing. I should be focusing, in my blogging, on melting, hammering, and hardening my investment strategy in the stock market. Yet, financial markets are like an endocrine system, and given the way those hormones just fountain, right now, I am truly interested in studying the way the whole organism works. According to the personal strategy of writing and publishing, which I laid out in the update entitled ‘Back in the game’, as well as those which followed, since February 10th, 2020, I should be using my blog mostly for writing about strategies to apply for investment in the stock market. Still, life can be surprising, and it is being bloody surprising right now. There is a thin line between consistency and obstinacy, and I want to keep walking on its consistency side. In order to coin up a sensible strategy for investment, I need to understand the socio-economic environment: this is elementary stuff which I teach my students in the first year. Besides, as I observe myself right now, I think I have some affinities with some squids and octopuses: when I sense serious cognitive dissonance coming my way, I release a cloud of ink. Just in case.
When I go deep into thinking, I like starting from what I perceive as my most immediate experience. Now, my most immediate experience consists in observing my own behaviour and the behaviour of other people. On Tuesday the 17th, I recorded those two video lectures, and I had to go to the campus of my university, where we have a state-of-the-art recording facility. I was cycling through the nearly empty city, and memories popped up. I remember the late 1970ies, when I was a little kid, and lived in the communist Poland. When I would walk the streets, back then, they were similarly empty. It is only now, when human traffic in the streets has gone down to like 5% of what it used to be until recently, that I realized how much more mobile and interactive a society we have become, in Poland, since that communist past.
I am thinking about the way we, humans, adapt to new circumstances. How is social mobility, even that most immediately observable daily traffic, connected to the structure of our social life. How is my GDP per capita – I mean, it is per capita, and thus I can say it is my per capita – related to the number of pedestrians per hour per square kilometre out there, in the streets? My most immediate experience of street traffic is that of human energy, and the intensity of its occurrence. It looks as if the number of human steps on the pavement, together with the stream of vehicles, manifested an underlying flow of some raw, hardly individuated at all, social force. What is the link between this raw social energy, and social change, such as what we have experienced, all over Central Europe, since the collapse of the Berlin wall? Well, this is precisely what I am trying to figure out.
Now, I go deeper, as deep as William James used to go in his ‘Essays in Radical Empiricism’, published, for the first time, in 1912. Human energy, out there, manifests itself both in the streets as such, and in me, in my perception. Phenomenologically, the flow of human traffic is both outside of me, and inside my mind. The collective experience is that of roaming the city, and, in the same time, that of seeing other people doing it (or even knowing they keep doing it). Same for the stock market, real business, teaching etc. All those streams of human activity are both out there, as intersubjectively observable stuff, and inside my mind, as part of my consciousness.
What we do is both in us, and out there. Social life is a collection of observable events, and a collection of corresponding, individual experiences. My experience right now is that of reorganizing my activity, starting with my priorities as for what to work on. It is fully official, the Minister of Science and Higher Education has just signed the emergency ordinance that all classes in universities are suspended until April 10th and that we are all encouraged to take on any form of distance learning we can use, even if it isn’t officially included in syllabuses. Given that right after April 10th it will be the Easter break, and that, realistically, classes are highly unlikely to restart afterwards, I have a lot of free time and a lot of things to stream smoothly inside of that sudden freedom.
I start with making a list. I structure my activity into 3 realms: pure science, applied science, and professional occupation.
As for the strictly speaking scientific work, i.e. the action of discovering something, I am working on using artificial intelligence as a tool for simulating collective intelligence in human societies. I have come up with some interesting stuff, but the first exchange I had about it with publishers of scientific journals is like ‘Look, man, it sounds interesting, but it is really foggy, and you are really breaking away from established theory of social sciences. You need to break it down so as to attach the theory you have in mind to the existing theory and to sort. In other words: your theory is not marketable yet’. I humbly accept those criticisms, I know that good science is to be forged in such fire, and I know that science is generally about figuring out something intelligible and workable.
The concept of collective intelligence is even more interesting right now. Honestly, that COVID-19 looks to me as something collectively intelligent. I know, I know: viruses don’t even have anything to be intelligent with, them having no nervous system whatsoever. Still, juts look. COVID-19 is different from his cousins by its very progressive way of invading its host’s body. The COVID-19’s granddad, the SARS virus from 2003, was like Dalton brothers. It would jump on its prey, all guns out, and there was no way to be asymptomatic with this f**ker. Once contaminated, you were lucky if you stayed alive. SARS 2003 was sort of self-limiting its range. COVID-19 is like a jihadist movement: it sort of hangs around, masking its pathogenic identity, and starts reproducing very slowly, sort of testing the immune defences of the organism, and each consecutive step of that testing can lead to ramping up the pace of reproduction.
All this virus has, as a species, is a chain of RNA (ribonucleic acid), which is essentially information about reproducing itself, without any information about any vital function whatsoever. This chain is apparently quite long, as compared to other viruses, so it takes some time to multiply itself. That time, unusually long, allows the host’s body to develop an immune response. The mutual pacing of reproduction in the virus, and of immune kickback in the host creates that strange phase, when the majority of hosts act like postmen for the virus. Their bodies allow the COVID-19 to proliferate just a little, but just enough to become transmissible. Allowing some colonies of itself to be killed, the virus brings a new trait: it is more pervasive than deadly, and it is both in the same time. At the end of the day, COVID-19 achieves an impressive reach across the human species. I think it will turn out, by the end of this year, that COVID-19 is a record holder, among viruses, as for the total human biomass infected per unit of time.
Functionally, COVID-19 looks almost like a civilisation: it is able to expand by adaptation. As I read scientific articles on the topic of epidemics, many biologists anthropomorphise pathogens: they write about those little monsters ‘wanting’ something, or ‘aiming’ for some purpose. Still, there is nothing in a virus that could be wanting anything. There is no personality or culture. There is just a chain of RNA, long enough to produce additional time in proliferation.
Let’s compare it to human civilisation. Any human social structure started, long ago, as a small group of hominids trying to survive in an ecosystem which allows no mistakes. One of the first mistakes that our distant ancestors would make consisted in killing and gathering the shit out of their immediate surroundings, and then starving to death. Hence, they invented the nomadic pattern, i.e. moving from one spot to another before exhausting completely the local resources. Our apish great-grandparents were not nomadic by nature: they probably picked it from other species they observed. Much later, more evolved hominids discovered that nomadism could be replaced by proper management of local resources. If you domesticate a cow, and that cow shits in the fields, it contributes to regenerating the productive capacity of that soil, and so we can stay in one place for longer.
Many generations later, we had figured out still another pattern. Instead of having a dozen children per woman and letting most of them die before the age of 10, we came to having less offspring but taking care to bring that smaller number up, nicely and gently, all the way to adulthood. That allows more learning within one individual lifetime, and thus we can create a much more complex culture, and more complex technologies. In our human evolution, we have been doing very much what the COVID-19 virus does: we increase our own complexity, and, by the same means, we slow down our pace of reproduction. At the end of the day, slowing down pays off through increased range, flexibility and biomass.
My theoretical point is that collective intelligence is something very different from the individual one. The latter requires a brain, the former not at all. All a species needs at the level of collective intelligence is to make an important sequence of actions (such as the action of reproducing a long chain of nucleotides) complex and slow enough for allowing adaptation to environmental response, in that very sequence.
I assume I am a virus. I slow down my action so as to allow some response from outside, and to adapt to that response. It has a name: it is a game. An action involving two or more distinct agents, where each agent pends their action on the action of the other(s) is a game. Let’s take a game of chess. Two players: the collective intelligence of humans vs. the collective intelligence of COVID-19. Someone could say it is a wrong representation, as the human civilisation has a much more complex set of pieces than the virus has, and we can make more different moves. Really? Let’s look. How much complexity and finesse have we demonstrated so far in response to the COVID-19 pandemic? It turns out we are quite cornered: if we don’t temporarily shut down our economy, we will expose ourselves to seeing the same economy imploding when the reasonably predictable 7% of the population develops acute symptoms, i.e. respiratory impairment. What we do is essentially what the virus does: we play on time, and delay the upcoming events, so as to gain some breathing space.
We can change the rules of the game. We can introduce new technologies (e.g. vaccines), which will give is more possible moves. Still, the virus can respond by mutating. The most general rules of the game we play with the virus is given by the epidemic model. I tap into the science published in 2019 by Olusegun Michael Otunuga, in the article entitled ‘Closed-form probability distribution of number of infections at a given time in a stochastic SIS epidemic model’ (Heliyon, 5(9), e02499, https://doi.org/10.1016/j.heliyon.2019.e02499 ).
A crazy scientific idea comes to my mind: as we are facing a pandemic, and that pandemic deeply affects social life, I can study all of social life as concurrent pandemics: a pandemic of going to restaurant, a pandemic of making vehicles and driving them around, a pandemic of making and consuming electricity etc. COVID-19 is just one among those pandemics, and proves being competitive against them, i.e. COVID-19 prevents those other pandemics from carrying on at their normal pace.
What is the cognitive value of such an approach, besides pure intellectual entertainment? Firstly, I can use the same family of theoretical models, i.e. epidemic models, to study all those phenomena in the same time. Epidemic models have been in use, in social sciences, for quite some time, particularly in marketing. The diffusion of a new product or that of a new technology can be studied as the spreading of a new lifeform in an ecosystem. That new lifeform can be considered as candidate for being a pathogen, or a symbiont, depending on the adaptive reaction of other lifeforms involved. A new technology can both destroy older technologies and enter with them in all sorts of alliances.
A pathogen able to kill circa 3% of the population, and temporarily disable around 10%, can take down entire economic systems. In the same time, it stimulates the development of entire industries: 3D printing, biotech, pharmacy, and even basic medical supplies. One year ago, would anyone believe that manufacturing latex gloves could be more strategic than manufacturing guns?