Chitchatting about kings, wars and medical ventilators: project tutorial in Finance

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I continue with educational stuff, so as to help my students with their graduation projects. This time, I take on finance, and on the projects that my students are to prepare in the curriculum of ‘Foundations of Finance’. The general substance of those projects consists in designing a financial instrument. I know that many students struggle already at the stage of reading that sentence with understanding: they don’t really grasp the concept of designing a financial instrument. Thus, I want to sort of briefly retake it from the beginning.

The first step in this cursory revision is to explain what I mean by ‘financial instrument’. Within the framework of that basic course of finance, I want my students to develop intellectual distinction between 5 essential types of financial instruments: equity-based securities, debt-based securities, bank-based currencies, virtual currencies (inclusive of cryptocurrencies), and insurance contracts. I am going to (re)explain the meaning of those terms. I focus on those basic types because they are what we, humans, simply do, and have been doing for centuries. Those types of financial instruments have been present in our culture for a long time, and, according to my own scientific views, they manifest collective intelligence in human societies: they are standardized parcels of information, able to provoke certain types of behaviour in some categories of recipients. In other words, those financial instruments work similarly to a hormone. Someone drops them in the middle of the (social) ocean. Someone else, completely unknown and unrelated picks them up, and their content changes the acquirer’s behaviour. 

When we talk about securities, both equity-based and debt-based, the general idea is that of securing claims, and then making those secured claims tradable. Look up the general definition of security, e.g. on Investopedia. If you want, in your project, to design a security, the starting point is to define the assets it gives claim on. Equity-based securities give direct, unconditional claims on the assets held by a business (or by any other type of social entity incorporated in a business-like way, with an explicit balance sheet), as well as conditional, indirect claims on the dividend paid out of future net income generated with those assets. Debt-based securities give direct, unconditional claim on the future cash flows, generated by the assets of the given business. The basic idea of tradable securities is that all those types of claims come with a risk, and the providers of capital can reduce their overall risk by slicing the capital they give into small tradable portions, each accompanied by a small portion of adjacent risk. Partitioning big risks and big claims into small parcels is the first mechanism of reducing risk. The possibility to trade those small parcels freely, i.e. to buy them, hold them for however long pleases, and then sell them, is the second risk-reducing device.

The entire concept of securities aims, precisely, at reducing financial risks connected to investing big amounts of capital into business structures, and thus at making that investment more attractive and easier. Historically, it literally has been working like that. Over centuries, whenever people with money were somehow reluctant to connect with people having bold ideas, securities usually solved the problem. You were a rich merchant, like in the 17th century-France, and your king asked you to lend him money for the next war he wanted to fight. You would answer: ‘Of course, my Lord, I would gladly provide you with the necessary financial means, yet I have a tiny little doubt. What if you lose that war, my Lord? Who’s going to pay me back?’. Such an answer could lead into two separate avenues: decapitation or securitization of debt. The former was somehow less interesting financially, but the latter was a real solution: you lend to the King, in exchange he hands you his royal bonds (debt-based securities), and you can further sell those bonds to whoever is interested in betting on the results of war.      

Thus, start with a simple business concept, e.g. something of current interest, such as a factory of medical ventilators. You have a capital base, i.e. some assets, and you finance them with equity and liabilities. Classical. You can skip the business planning part by going to the investors relations site of any company you know, taking their last financial report and simply simulating a situation when those guys want to increase their capital base, i.e. add to their assets. I mentioned medical ventilators, so you could go and check Medtronic’s investors relations site ( ), and pick their latest quarterly financials. They have assets worth $92 822 mln, financed with $51 953 mln in equity and $40 869 in debt. Imagine they see big business looming on the horizon, and they want to accumulate $10 000 mln more in assets. They can do it either through additional borrowing, or through the issuance of new shares in the stock market.

You can go through the reports of Medtronic as well as through their corporate governance rules, and start by taking your own stance at the basic question: if Medtronic intends to accrue their assets by $10 000 mln, would you advise them to collect that capital by equity, or by debt, or maybe to split it somehow between the two. Try to justify your answer in a meaningful way.

If you go for equity-based securities (shares in equity), keep asking questions such as: what should be the nominal value (AKA face value) of those shares? How does it compare with the nominal value of shares already outstanding with this company? What dividend can shareholders expect, based on past experience? How are those new shares expected to behave in the stock market, once again based on the past experience?

If your choice is to bring capital through the issuance of debt-based securities, go for answering the following: what should be the interest rate on those corporate bonds? What should be their maturity time (i.e. for how long should they stay in the market of debt before Medtronic buys them back)? Should they be convertible into something else, like in the shares in equity, or in some next generation of bonds? Once again, try to answer those questions as if I were just a moderately educated hominid, i.e. as if I needed to have things explained simply, step by step.

See? Chitchatting, talking about kings, wars and medical ventilators, we have already covered the basics of preparing a project on equity-based securities, as well as on the debt-based ones.

If you want to go somehow further down those two avenues, you can check two of my blog updates from the last academic year: Finding the right spot in that flow: educational about equity-based securities , and  Unconditional claim, remember? Educational about debt-based securities.

Now, we talk about money, i.e. about a hypothetical situation when my students design a new currency in the framework of their project. Money is strange, to the extent that technically it should not have any intrinsic value of itself, as a pure means of exchange, and yet any currency can be deemed mature and established once its users start hoarding it a little bit, thus when they start associating with it some sort of intrinsic value. Presently, with the development of cryptocurrencies, we distinguish them from bank-based or central-unit-based currencies. In what follows immediately, I am focusing on the latter category, before passing to the former.

So, what is a bank-based currency, AKA central-unit-based currency? A financial institution, e.g. a bank, issues a certain number of monetary units (AKA monetary titles), which are basically used just as a means of exchange. The bank guarantees the nominal value of that currency, which, in itself, does not embody any claim on anything. This is an important difference between money and securities: securities secure claims, money doesn’t. Money just assures liquidity, understood as the capacity to enter into exchange transactions.   

When designing a new currency, step #1 consists in identifying a market with liquidity problems, e.g. we have 5 developing countries, which do business with each other: they trade goods and services, business entities from each of those countries invest in the remaining four etc. Those 5 countries have closed or semi-closed monetary systems, i.e. their national currencies either are not exchangeable at all against any other currency, or there are severe limitations on such exchange (e.g. you need a special authorization from some government agency). Why do those countries have closed monetary systems? Because their governments are afraid that if they make it open, thus when they allow free exchange against foreign currencies, the actual exchange rate will be so volatile, and so prone to speculative attacks (yes, there are bloody big sharks in those international financial waters) that the domestic financial system will be direly destabilized. Why any national currency should be so drastically volatile? It happens when this currency is not really exchanged a lot against other currencies, i.e. when exchange is sort of occasional and happens in really big bundles. There is not enough accumulated transactional experience. Long story short, we have national currencies which are closed because of the possible volatility and are so prone to volatility because they are closed systems. Yes, I know it sounds stupid. Yet, once you see that mechanism at work, you immediately understand. In the communist Poland, we had a closed monetary system, with our national currency, the zloty, technically being not exchangeable at all against anything else. As a result, whenever such exchange actually took place, e.g. against the US dollar, you needed to be a wizard, or a prime minister, to predict more or less accurately the applicable exchange rate.

Those 5 countries have two options. For one, they can use a third-country, strong currency as a local means of exchange, i.e. their governments, and their national business entities can agree that whenever they do business transnationally, they use a reference currency to settle their mutual obligations. The second option consists in creating an international currency, specifically designed for settling business accounts between those countries. This is how the ECU, the grandpa of the euro, was born, back in the day. The ECU was a business currency – you couldn’t have it in your wallet, you just could settle your international accounts with it – and then, as banks got used to it, the ECU progressively morphed into the euro. What you need for such a currency is a financial institution, or a contractually established network thereof, who guarantee the nominal value of that business currency.

If our 5 countries go for the second option, the financial institution(s) who step in as guarantors if the newly established currency need to bring to the table something more than just mutual trust. They need to assign, in their balance sheets, specific financial assets which back the aggregate nominal value of the new currency put in circulation. Those assets can consist of, for example, a reserve basket of other currencies. Once again, it sounds crazy, i.e. money being guaranteed with money, but this is how it works.

Therefore, step #2 in designing a new, bank-based currency, requires giving some aggregate numbers. What is the aggregate value of transactions served by the new currency? Let’s go, just as an example, for $100 billion a year. How long will each unit of the new currency spend on an individual bank account? In a perfectly liquid market, each unit of currency is used as soon as it has been received, thus it just has one night to sleep on a bank account, and back to work, bro’. In such a situation, that average time on one account is 1 day. Therefore, in order to cover $100 billion in transactions, we need [$100 / 365 days in the year] = $0,2739726 billion = $274 million in currency. If people tend to build speculative positions in that currency, i.e. they tend to save some of it for later, the average time spent on an individual account by the average unit of that new money could stretch up to 2 weeks = 14 days. In such case, the amount of currency we need to finance $100 billion in transactions is calculated as [$100 / (365/14)] = [$100 * 14 / 365] = $3,8356 billion.

There is a catch. I talk about introducing a new currency, but I keep denominating in US dollars, whence the next question and the next step, step #3, in a project devoted to this topic. The real economic value of our money depends on what we do with that money, and not really on what we call it. One of the things we do with an international currency is to exchange it against national currencies. In this case, we are talking about 5 essentially closed national currencies. For the sake of convenience, let’s call them: Ducat A, Ducat B, Ducat C, Ducat D, and Ducat E. Once again for sheer convenience we label the new currency ‘Wanderer’. So far, our 5 countries have been using the US dollar for international settlements, whence my calculations denominated therein. The issue of exchange rate of the Wanderer against the US dollar, as well as against our 5 national Ducats, is a behavioural one. Yes, behavioural: it is about human behaviour.

We have businesspeople doing international business in USD, and we want to convince them to switch to the Wanderer. What arguments can we use? There are two: exchange rate per se, and exchange rate risk. Whoever is a national of our 5 countries, needs to exchange their national Ducat against the US dollar and the other way around. As neither of the Ducats is freely convertible, exchange with the dollar takes place, most probably, in the form of big, bulk transactions, like once a month, mediated by the central banks of our 5 countries. Those bulk transactions yield an average exchange rate, and an average variance around that average.

We want to put in place an alternative scheme, where the national Ducats (A, B, C, D, E) are exchanged in real time against the Wanderer, and then the Wanderer gets exchanged against the US dollar. The purpose is to make the exchange {Ducat Wanderer USD} more attractive, average-rate-wise or variance-in-rate-wise, than the incumbent {Ducat Individual, National Central Bank USD} one. Some of you might think it is not realistically possible, yet it really is. If 5 central banks of developing countries gang up together to buy and sell US dollars, they can probably achieve a better price, and less volatile a price, as compared to what each of them separately could have. There is even an additional trick, and this is like really a trick: central banks of our 5 countries could hold some of their financial reserves in US dollars, more specifically the part devoted to backing the Wanderer. That’s the trick that our central bank in Poland, the National Central Bank of Poland, uses all the time. We are in the European Union, but we do not belong to the European Monetary Union, and yet we do a lot of business with partners in the eurozone. The National Bank of Poland holds important financial reserves in euros, and thus gives itself a better grip on the exchange rate between the Polish zloty and the euro.

Summing up the case of graduation projects focused on designing a new bank-based currency, here are, rephrased once again, the basic logical steps. Start with identifying a market with liquidity problems, such as closed monetary systems or very volatile national currencies. This is usually an international market made of developing countries. Imagine a situation, when the central banks of the countries in question place some of their financial reserves in a strong currency, e.g. the US dollar, or the Euro, and then the same central banks introduce a currency for international settlements in that closed group of countries. Keep in mind that the whole group of countries will need an amount of currency calculated as: [Aggregate value of international transactions done in a year * [Average number of days that one user holds one unit of currency / 365].  

The whole scheme consists, at the end of the day, in obtaining a better and less volatile exchange rate of individual national currencies against the BIG ONES (e.g. the US dollar) through aggregating their exchange transactions in the financial market.       

That would be all in this tutorial. I have covered three types of financial instruments that my students can possibly design for their graduation: equity-based securities, debt-based securities, and bank-based currencies. In the coming weeks I will try to write something smart on designing cryptocurrencies and insurance contracts. Till then, you can additionally read entry March, 26th, 2019 – More and more money just in case. Educational about money and monetary systems – and entry March 31st, 2019 – The painful occurrence of sometimes. Educational about insurance and financial risk.

Fast + slower = compound rhythm, the rhythm of life

My editorial on You Tube

I am continuing and expanding my so-far line of thinking and writing, into something both more scientific and more educational (we are still in full distance learning mode, at the university). I want to develop on that simple model I have recently presented in the update entitled ‘Acceptably dumb proof. The method of mean-reversion’. I am going to develop and generalize on its cognitive and behavioural implications. By the way, I have just used it (it is April 10th, 15:40 p.m.) to buy a bit into Asseco Business Solutions and to open a position on a company active in stem cells: PBKM. I spotted a moment, when their mean-reversed stock price was passing the 0 point and going up. According to this method, there is very likely to be an upcoming spike, with an opportunity to sell at a profit.

Good. The behavioural context. When I trade in the stock market, with my own money, emotions grow strong. After a few years of pause in investing, I had actually forgotten how strong those emotions can unfold. The first thing which I already know this method has given me is emotional step-back, and the capacity to calm down. This is the mark of a good strategy: it is simple (this model of mine is really simple, as financial forecasts come), thus workable, and it gives that special sort of calm flexibility in decisions.

The capacity to step back from the emotions of the moment, to get some perspective, and make more informed decisions is based on one essential assumption: the distinction between the normal and the alarming. There is a state of things, which I accept as ‘normal’, when I just can do something, but I don’t need to. By opposition, I define a state of things-which-consist-in-me-experiencing-reality, where my perception urges me to take action.

This is about my perception of reality, right? In the stock market, reality is made of numbers, right? I mean, there is much more in trade, there are people, for example, yet the reality which I am most of all supposed to pay attention to is made of numbers: the stock prices. Prices change. This is their normal way of being in the stock market. By the way, some of you might think that stationary a price, in a security, is the best way of being for a long-term investment. Not really. When you try and do some trade, one day, you will see that durably stationary prices can frighten the s**t out of you. It is like a frozen reality: scary. When prices swing, their ebb and flow gives information. When they stop moving, there is no more information. You are in a dark room.

Good, to the numbers that make my reality in the stock market – prices – change constantly and they’d better keep changing. What I observe, thus, is change in prices rather than prices themselves. Mathematically, I observe the values of a function (stock prices), and the values of its derivatives (change in prices, and coefficients calculated thereupon). It is the old intuition of Isaac Newton: what we really perceive is change and difference rather than absolute states of reality.

I define two classes in all the possible types of change I observe in reality. Class #1, the relax-bro type, covers normal change and allows me to sit back and watch what happens next. I can do some action, if I really feel like, yet it is all up to me. Class #2, the c’mon-do-something one, jumps into being when change becomes somehow abnormal, like highly stimulating. There is normal change and abnormal change, then, and I want to define these two states of reality with the toolbox of mathematics. From there on, it is highly subjective. Mathematics provide many ways of defining what’s normal. In my model, I go for a classic: the normal distribution. The normal state of change, seen through the lens of normal distribution, is acceptable oscillation around the expected value of price. The expected value is arithmetical average of prices observed over a given period of time. Seen under this angle, the average price is something like an immediate projection of my past experience: I expect to see, here and now, something aligned with the states of reality I have experienced so far.

The ‘so far’ part is subjective. Do I expect the current change in prices to be somehow in line with what has been happening over the last year, over the last 3 years, or maybe just over the last week? You can see a glimpse of that choice when you go and check stock prices online, with a graph. Most online utilities give you the choice between snapshotting the current day, the last 2 weeks, the last month etc. People have different temporal frames of reference as for what is normal to them. In my personal model, the one I hinted at in ‘Acceptably dumb proof. The method of mean-reversion’, I set my frame of reference at the last month, or, to me more specific, at the last 30 trading days, which actually makes a little more than a calendar month.

Subjectivity is scalable and measurable. I am going to focus on two ramifications of this principle. Firstly, I can make typical change my unit of measurement. Secondly, I can shift between different time frames and see what kind of change it brings in terms of strategic behaviour. Before I walk down these two paths, I am reminding the general mathematical frame of what I am talking about (see picture below).

What happens, mathematically, when I follow the old Newtonian intuition of observing change rather than stationary states of nature? Logically, a given magnitude of change becomes my unit of measurement. In basic statistics, i.e. as long as we stay in the safe realm of Gaussian distributions, standard deviation, i.e. mean expected deviation from the mean expected average, can be such a Sevres-meter of my perception. Let’s keep in mind it is deep in our human perception: there are differences and variations large enough for us to notice, and the remaining part of all the chaos happening in that stuff we call reality passes essentially unnoticed to us.

When standard deviation becomes my gauge, and it serves me to assess whether anything is worth my attention, I can interestingly decompose the basic equation of mean-reversion, as residual difference between the actual value observed (price, in this case) and denominated in its own standard deviation, and the expected average value, denominated in the same way. In other words, mean-reversed price is the residual difference between the locally observed deviation from what I call ‘normal and expected’, and the general variability of what I observe (average divided by standard deviation).  

There is a simply and technically useful aspect of that approach. When standard deviation becomes the unit of measurement, I can directly compare the actions I should take on many investment positions, when they are in very different price ranges. Let’s study it on two different cases in my portfolio: Airway Medix, and 11Bit. The former is market-priced at less than PLN 1 per share, the latter is currently around PLN 380. When I mean-reverse their prices, I drive them both to the same scale, like inside the interval -3 ≤ x < 3. The local magnitude of mean reversed prices is directly comparable between the two.  

As I talk about comparisons, let’s compare these two – Airway Medix and 11Bit – in different time frames. My basic one is the last 30 trading days, but what if I look differently at time and change? What if I take a shorter view over the timeline, or a longer one? In tables below, I show four alternative temporal perspectives on those two stocks: last 30 days, 7 days, 14 days, and finally the past 6 months of trade.

 Mean-reversed price of Airway Medix
Trading dayWindow 30 daysWindow 7 daysWindow 14 daysWindow 6 months
 Mean-reversed price of 11Bit
Trading dayWindow 30 daysWindow 7 daysWindow 14 daysWindow 6 months
01.04.2020(0,47)0,490,62         (0,90)
02.04.2020(0,42)0,300,57         (0,90)
03.04.2020(0,31)0,730,90         (0,82)
06.04.20200,522,513,01           0,06 
07.04.2020(0,23)(0,10)0,25         (0,83)
08.04.2020(0,04)0,210,61         (0,68)
09.04.20200,411,021,46         (0,31)
10.04.20200,440,791,27         (0,30)

As I study the two tables above, my first question is: what do I actually see? What the differences between those numbers are actually informative about? Positive numbers tell me that the current price is sort of high as compared to the moving average, and negative say the opposite. As I look at the last days of trade before Easter, 11Bit appears as being kind of moderately positive in the 30-day view, and it means: rather hold than sell, unless you strike a really good deal. A timeframe of 7 days tells me more or less the same. When I set my timeframe at 14 days, it says: definitely look for a good sell, the price is abnormally high. Still, when I take a really long step back and look at the whole thing from the perspective of a 6-month temporal horizon, it says: ‘no, you dumb f**k, don’ even think about selling; if you feel the urge to do something, go and buy some of these’.

You can see empirically that my subjective perception of what is a long time, as opposed to what is just a moment impinges directly on the strategy I am supposed to adopt. It is a deep, general principle of human action. Farmers look at life differently from stock market brokers: their time frames differ.

What if I apply the same logic, i.e. the logic of mean-reversion, to volumes traded, instead of prices? What the mean-reversed volume is informative about? Let’s see. Here below, you can see comparative graphs of Airway Medix with, respectively, stock price and volumes traded daily, both mean-reversed over a window of the last 30 days of trade. You can see that volumes swing much more frequently than prices. It is as if they were two musical tunes: volumes modulated at a faster pace, and prices going at a slower one. Familiar? No? It is rock’n roll. Fast + slower = compound rhythm. The rhythm of life.

How can I generalize into any market? You can go and watch my tutorial in economics, the one about prices and quantities. It connects interestingly: .

Acceptably dumb proof. The method of mean-reversion.

My editorial on You Tube

It is 5:43 a.m. (yes, forty-three minutes after five o’clock in the morning, and I am completely sane), and I am starting another day of fascinating life. I know I could say: another day of this horrible epidemic, or another day of that limiting lockdown. I know I could, yet I am not. I say: fascinating life. This is how I feel. This whole situation, i.e. the pandemic and the resulting lockdown, it all makes my blood flow faster. There is a danger, out there, and there are us, who can face this danger. Us, not just me. There is the collective ‘us’ who adapts, organizes, and collectively says: ‘There is no f**king way we surrender’. This is the beauty of life.

Would I say the same to someone who has just lost their job, due to the lockdown, and has a family to take care of? In spite of all the apparent ridicule of such a claim in such a situation, yes, I would say the same, and you know why? Because there is no viable alternative. Should I say to this person: ‘Yeah, they’re completely right, those people who say you are f**ked. There is nothing you can do, just sink into despair and complain occasionally’.

I am drawing a bottom line under my yesterday’s quick trade, in the Polish stock market. You can read about the details in A day of trade. Learning short positions. I am progressively wrapping my mind around the day of yesterday. Conclusions start floating on the surface of my mind. When I go into a quick, daily trade on short positions, the best moment for making decisions seems to be around 11 – 12 o’clock CET, in the middle of the day. Deciding early in the morning, e.g. starting to trade with a morning sell-out, is not really a good idea. Deciding by the end of the day is tricky, too: the end of the trading day frequently pushes me to selling or buying just out of sheer rush, under the hot breath of time rather than the cool breath of reason.

Recently, a student of mine asked me what I think about short trade. I answered that it is interesting, but it generally sucks for me. It is true that never before have I done any short trade successfully. I remember feeling the pump of adrenaline, peculiar to gambling, yet the financial results were never good. I said it generally sucks for me, and then I tried again, yesterday. This is something I discovered lately: facing my fears and apprehensions can be a fascinating experience. At my age, 52, fears and apprehensions come out of accumulated learning, and the big thing about it is that we accumulate learning in order to stop learning. Facing the things which I am wary or afraid of means questioning my acquired knowledge and habits. It is like digging into one of those cellars, full of objects from the past: I discover new kinds of beauty.

And so, I did it again: I tried short trade, and I meant confronting my acquired wariness. I can see that trading on short, daily positions is a useful skill, and I can develop that skill, to a reasonable level, quite quickly. It is most of all about being aware what I am doing, i.e. cognitively stepping back from action, for a moment, and correct it slightly, so as to make it coherent and purposeful. The key is to own my own story. When I have both cards in my hand: that little gambling nerve, and the intellectual discipline in self-questioning the gambling reflexes, I can thrive on that mix. I love it, actually. My action leads me to forming new ideas about myself. I have just realized that I thrive, as an investor, on two types of action. I can be like a gardener, for one, watching my long-term positions grow and bring fruit in due time. For two, I can be like a hunter, going out for an informed, wise kill.

Wise kill means predating, i.e. violently harvesting from the ecosystem, not killing for the sake of it. There comes an important question I ask myself: how to practice short trade, every now and then, and stay sort of constructive in my investment? I have already learnt, after the day of yesterday, that short trade is a powerful method of quickly adapting my investment to just as quick a change in external conditions.  On the other hand, I want to join, in an informed way, a big stream of investment in positive technological change. Can I reconcile these two: short-term, wisely predatory strategies of adaptation with long-term, positive orientation?

There comes an afterthought, which has just popped up in my mind: wise hunters wait for their prey, instead of running after it. My experience of short trade tells me that it is wise to have a strategy prepared for those days of short positions. To me, short trade is adaptation, and, logically, I should do it in the presence of quickly changing conditions. Just as logically, I should tool myself with some kind of early detection mechanism for violent outbursts in the stock market, when a local speculative bubble is about to swell, or about to implode. Detection in place, I should have strategies for riding a mounting wave, as well as surfing down a collapsing one.

My point is that I can stay constructive in my episodes of short trade when I stay strategic, informed, and prepared. Blueprints seldom work perfectly in real life, yet they provide robust structure. I can become destructive in my days of short trade if I go chaotic, and to the extent of chaos in my actions.

A numerical strategy comes to my mind. I target a handful of companies I would like to sort of hang around with, equity wise. Let’s suppose they are Polish companies from the biotech – medical complex, plus some interesting IT ones. I check regularly their prices in the stock market, as well as the volumes traded. I assume that the market can be in two alternative states, from my point of view: either it allows me to be the placid gardener of my investment positions, or it forces me to become the alert and violent hunter. The ‘gardener’ state is when I don’t need to do anything quick, i.e. when I don’t need to adapt through daily short trade. I need to go for a day of short trade hunting when the market somehow goes off the rails. I need to define those rails.

Mathematically, I assume that whatever happens to those stock prices, happens inside a stochastic process, i.e. something slightly crazy, yet crazy in a generally predictable manner. Within that stochastic process, there is the calm and picturesque Gaussian process, where local values go hardly away from their moving average, like no more than one moving standard deviation away either way (i.e. plus or minus). Anything outside that disciplined Gaussian happening triggers the hunter in me and makes me go short trade. This is an approach similar to mean-reversion: the further something drifts away from the expected state, the more alarming it is.   

I assume that cognitively, the still waters of Gaussian process, from my subjective point of view, are set by the behaviour of prices over the last 30 days. I take the moving average price, and the moving standard deviation from that price, from the 30 preceding days. Below, I am exemplifying this logic with historical prices of the company whose shares I sold yesterday – and I regret having been too hasty – namely Biomed Lublin. The curve in the graph shows values calculated as:

Mean_reversed Price (day xi) = {[Price(day xi)] – [Mean(Price xi-30, …, Price xi)]} / Standard deviation (Price xi-30, …, Price xi).

On the graph, I marked with green dashed lines the corridor of ‘calm’ variance, within one moving standard deviation around the moving average ( -1 ≤ x ≤ 1). Inside that corridor, I assume I can just hold whatever stock of Biomed Lublin I have, or, conversely, I should abstain from buying it, unless I really want. The bubble marked with red dashed line shows an example of price wandering way out of that safe corridor. It is an example of alarm zone: it is price rocketing up, and a possibly good occasion for the short trade I planned, and did not complete finally, for yesterday: selling in the morning for a higher price, and buying back, for a lower one, by the end of the day, or next day. If the curve flares in the opposite direction, i.e. below the bottom green line, it is a signal to buy quickly, with an expectation to sell at a higher price.

The graph shows a time window between May 27th, 2019, and yesterday, April 8th, 2020, thus some 10 months with a small change. During that period, should I have been actively trading Biomed Lublin, I should be about half of the time on alert, and going into short trade. As you can see, this otherwise simple strategy of trading involves behavioural assumptions about myself: do I want to go hunting, in the grounds of short trade, as frequently as the graph suggests? It is reasonable not to narrow down the zone of calm, i.e. below one moving standard deviation away from the moving average. On the other hand, I can increase my zone of tolerance (calm) beyond one moving standard deviation.  

Summing up, I have two perspectives on trading a given stock, with this simple model. First of all, in the long view, I can observe how does the curve of mean-reversed closing price behaves generally. Is it rather wild, i.e. does it swing a lot out of the safety zone between -1 and 1, or, conversely, is it rather tame? The more swinging is the curve, the more the given stock is made for a series of short-term trading operations, like buy in and sell out, in a sequence. If, on the other hand, the mean-reversed price tends to stay a lot in the safety zone, that is the type of stock to hold for a long time rather than to prance around a lot. Secondly, I can observe the short-term tendency over the last few days, like the last week of trading, and make myself an idea as for the immediate stance to take.

I use this simple tool to study my own current portfolio of investment positions, plus the two stocks I sold yesterday but I sort of keep them in my crosshairs, as they are biotech, presently dear to my heart sort of generally. Biomed Lublin, to follow, is a wild one, especially those last weeks. Its mean-reversed price has been swinging a lot out of the – 1 ≤ x ≤ 1 zone. This is the type of stock to watch closely, and to be ready to go for a quick kill about it. As for the last days, you can see it gently returning from a ‘quick sell’ zone, and getting into the ‘hold’ one.

Mean-reversed price of Biomed Lublin

01.04.2020      3,196722673

02.04.2020      3,590790488

03.04.2020      4,173460856

06.04.2020      3,713915308

07.04.2020      1,870944561

08.04.2020      1,71190807

As regards 11Bit, it used to be a wild one, with a high potential for ‘sell’ recommendations. Yet, since the COVID-19 panic erupted in the stock market, and after the Polish stock market started to flirt a lot more with biotech, 11Bit has gone sort of tame. A few weeks ago, there had been a short window for buying, which I missed, unfortunately, like between February 27th and March 27th. The latest developments suggest holding.

Mean-reversed price of 11Bit

01.04.2020      -0,470302222

02.04.2020      -0,418676901

03.04.2020      -0,308375679

06.04.2020      0,518241443

07.04.2020      -0,230731307

08.04.2020      -0,036589487

Asseco Business Solutions is in a different situation. In the past, before the COVID crisis, it would stay a lot above the 1 barrier, thus offering a lot of incentives to sell and consume profits. Yet, over the last month or so, it has nosedived into the alarm zone below -1, just to climb into the -1 ≤ x ≤ 1 safety belt recently. Looks like it morphed from something to kill into something to farm patiently.  

Mean-reversed price of Asseco Business Solutions

01.04.2020      -0,498949327

02.04.2020      -0,454984411

03.04.2020      -0,467396289

06.04.2020      -0,106632042

07.04.2020      -0,062469251

08.04.2020      -0,006786983

Airway Medix is another wild type, with a lot of spikes out of the -1 ≤ x ≤ 1 zone. Still, since May 2019, there was more occasions to buy rather that to sell. Those last weeks, it seems to have really changed its drift, and has rocketed up above 1. I have to be vigilant about this one.

Mean-reversed price of Airway Medix

01.04.2020      2,362791403

02.04.2020      1,922976365

03.04.2020      3,70150467

06.04.2020      3,768162474

07.04.2020      1,973153986

08.04.2020      1,441837178

Biomaxima is a strange case, at least as compared to others. For months, like until the first days of 2020, it had been mostly in the safety zone, with occasional spikes down, below -1, thus with occasional incentives to buy. Since January 2020, it started to sort of punch the ceiling and to burst more and more frequently above 1. Right now, it seems to be in the ‘sell or hold’ zone, with a visible drift down. To watch and react quickly.

Mean-reversed price of Biomaxima

01.04.2020      3,81413095

02.04.2020      3,413908533

03.04.2020      3,001585581

06.04.2020      2,378442856

07.04.2020      1,631660778

08.04.2020      1,668652998

Bioton is a still different story. Over the last 10 months, it had remained like half in the calm zone between – 1 and 1, whilst spending most of the remaining time in the ‘buy’ (x < -1) belt. There was one spike up, in July 2019, when there was some incentive to sell. Yet, now, it is a different story. As it is the case of many Polish biotech companies, the last 2 months have dragged Bioton out of that grey lethargy, into the spotlight of the market. Right now, the mean-reversed price from the last week suggests selling (if I have profit on it) or to hold. Looks like I bought this one on a selling wave: a mistake I could have avoided, had I remembered and applied earlier that method of mean-reversion in price (which I read about regarding the market of electricity).  

Mean-reversed price for Bioton

01.04.2020      1,219809883

02.04.2020      1,50983756

03.04.2020      3,76644111

06.04.2020      3,986920426

07.04.2020      2,434789898

08.04.2020      1,888320575

Mercator Medical is another case where, although I have currently some profit, I should have rather bought earlier (August – September 2019, something like that). That had been a relatively long window of ‘buy’ recommendation. Right now, as I have been investing in it, it is rather the ‘sell or hold’ time.  

Mean-reversed price for Mercator Medical

01.04.2020      1,664368071

02.04.2020      1,605024371

03.04.2020      2,408595698

06.04.2020      3,673484581

07.04.2020      1,846496909

08.04.2020      2,130831881

That cursory, technical analysis of my investment portfolio, together with my immediate targets in the biotech sector, brings me a few interesting insights. First of all, and once again, it pays to do things, and to write about me doing things. The urge I felt to phrase out my feelings after the yesterday’s intense day of short trade pushed me to formalize an acceptably dumb-proof strategy, based on the method of mean-reversion, which I knew theoretically but never thought to apply in practice to my own investment business.

A day of trade. Learning short positions.

My editorial on You Tube

I am betting on short-term developments in the stock market. Yesterday, the stocks of biotech and medical companies in the Warsaw Stock Market went through a rapid depreciation. I decided to play short-term today. This is something that has NEVER worked for me in the past, yet, this year, I want to learn new things about investing in the stock market.

During the day of yesterday, the profits I described in my last update, entitled ‘Doing things we don’t quite know how to do well is what we, humans, do all the time’, suddenly melted down, to a large extent. The strategy I am going to test today consists in selling, in the morning, three of my positions – Airway Medix, Biomed Lublin, Biomaxima – betting that their price will fall today just as deeply as it had fallen yesterday, and then buy them back at the end of the day, at a lower price. Selling them today in the morning will allow me to consume the profits I have still left on them, and, if I am betting correctly on the today’s developments in the market, their price will fall even more today. By the end of the today’s trading session, I should be able to buy them back at a lower price.

In the table below, you can see a short summary of the situation.

Company (position)Rate of return on April 7th, 2020 (YESTERDAY MORNING)Rate of return on April 8th, 2020 (THIS MORNING)Remarks
Asseco Business Solutions-5,88%-5,88% 
Biomed Lublin410,20%246,94%For sale in the morning, to buy back by the end of the day
Biomaxima21,82%1,82%For sale in the morning, to buy back by the end of the day
Airway Medix116,82%72,73%For sale in the morning, to buy back by the end of the day
Mercator Med.19,33%-5,95% 

Why am I not waiting for the early-morning developments in the stock market? I could wait like 30 minutes, from 9:00 to 9:30 a.m., and then decide whether I sell. If the prices of those three – Airway Medix, Biomed Lublin, Biomaxima – bounce back in the morning, there will be no point in selling. There is one caveat to that: if the day is a downwards revision day, the first 30 minutes of trade, precisely between 9:00 and 9:30, are usually marked with a very sharp drop in price. This is a recurrent pattern I have already noticed. Thus, if wait that first half-an-hour, I can lose some opportunities to make profit.

I need a plan B, in case the daily developments in the market go against my expectations. There are two issues, as regards my expectations. Firstly, it is possible that prices of those three stocks rise during the day and I cannot buy them back at a lower price. Buying them back at a higher price would not be good business. I need a plan what to do with the proceeds from the morning sell-out, if these particular events play out differently from what I expect to happen. I thought I could observe the movements in prices on the remaining 4 positions –  11Bit, Asseco Business Solutions, Bioton, and Mercator Medical – and maybe buy into those. I am particularly interested in Bioton. In the past, that stock gave me a huge gain, and in that whole portfolio of mine, this is the only clearly undervalued position, with a market-to-book ratio of 0,73. There is potential for growth in this company.

Secondly, for the moment, I assume there will be no big quake on my other positions. What of the entire market goes amok about downwards revision, today? That is a good question. There are two opposite logics to that. Logic A says ‘cut your losses short, don’t keep positions with negative returns’, whilst logic B protests: ‘it is a first principle of business that you sell at a higher price than the one you bought at, unless you really need cash or unless that thing is just never going to go up in price’. From my own experience, which I developed more broadly in the update entitled ‘Which table do I want to play my game on?’, I know a third logic, a cognitive pattern in myself: I need to have at least the impression I understand the rules of the game. Sometimes, I feel that my investment decisions – at least some of them – become so uninformed that what I am doing is actually pure gambling for the gambling’s sake. My experience is that in such moments I should just pull out of the game.

That third logic, which is strictly my own, is certainly an impediment when it comes to quick trade on short positions. I intuitively pull out of situations when I feel forced to make very quick moves, or, if I stay in such a situation, I start making haphazard moves. I have hard times to step back emotionally, and to figure out a quick, on-the-spot strategy. By doing what I am doing today, I expect, precisely, to develop my skills for such situations. I want to force myself to understand quickly the rules of a short-term game in daily trade.  

That’s an interesting thing from the scientific point of view. What is my personal, cognitive distinction between a game I know the rules of – the Abraham de Moivre’s game – on the one hand, and the Bayesian game, where I have to figure out the very space of the game and my essential bearings inside of it?

I have just realized another thing. I can update myself on how the daily trade is going on, at the Warsaw Stock Exchange, with a 15-minute-lag (in practice, it is 20 minutes of lag), and this sets something like a pace of observation for playing out my today’s strategy. Oookay, here comes a report from the battlefield: my selling orders have been executed. Let’s see. Biomed Lublin sold at PLN 3,13 per share, 219,39% of return on this one. Right now, I mean at 9:28, it was at PLN 3,03. For this one, my plan seems to be unfolding nicely, as for now. You know, that’s the thing about big plans: they seem to be unfolding nicely, up to a point. Airway Medix sold at PL 0,718 per share, 63,18% of return in this position. Keeps falling, was at 0,68 on 9:28. Biomaxima sold at PLN 21,60 per share, and, unfortunately, this one comes with a loss of – 1,82%. In this case, the follow up is less clear. It plunged in the morning, but now (9:35) it is climbing back and is at PLN 20,8 per share.

OK, step A done, let’s outline the strategy for step B, to be carried out during the today’s trading day. From the sales of 1000 shares of Biomed Lublin, I have proceeds amounting to PLN 3 130,00  PLN, and I had to pay a brokerage fee of 0,35%, which I will have to pay once again should I be buying back into this stock. Thus, my break-even price for the daily trade would be: PLN 3,13 * (1 – 2*0,35%) < PLN 3,108. That’s the condition I need to strike.

As I have sold my position of 2300 shares in Airway Medix, I have PLN 1 645,62  PLN of proceeds net of brokerage fee. I do the same calculation as for Biomed Lublin, and it goes: PLN 0,718 * (1 – 2*0,35%) < PLN 0,713. In the case of Biomaxima, I can reuse, to buy back in, the PLN 430,49 of proceeds net of brokerage fee, provided the condition PLN 21,60 * (1 – 2*0,35%) < PLN 21,449 is met. Ve vill zee…

Now, a quick look at the remaining sheep in the herd: 11Bit, Asseco Business Solutions, Bioton, and Mercator Medical. 11Bit jumped nicely right after the opening of trade, up to PLN 375, which reduces slightly my loss on this position. Asseco Business Solutions remains stationary, no movement at all. Bioton, my tacit preferee, is at PLN 4,77. Good. It is climbing nicely. If my intuition is correct, investors are moving capital inside the biotech-medical sector, from the clearly overvalued positions (see ‘Doing things we don’t quite know how to do well is what we, humans, do all the time’) to the undervalued ones. It is good financially, as my so-far loss on Bioton is getting shallower each minute, yet it is bad cognitively. If Biomed Lublin, Airway Medix, and Biomaxima go down, as I expect, and Bioton goes up, as I expect as well, which way to go: buy back into those three sold ones, or buy further into Bioton? Oh dear, life is complicated…

Mercator Medical is going nicely up, it was PLN 27,10 on 9:57, which puts me back in saddle, so to say. I start making profit on this one, just 0,74% for the moment, barely to pay for the brokerage fee, yet it looks promising. As I look at the volumes traded, there is a lot of reshuffling. Big volumes get purchased. Looks as if people were buying into this one.

Now, I face two alternative paths. Path A, I go psycho, I keep staring at the quotes in the stock market, whilst writing a live account in this log. Path B, I step back, into the safe realm of science, I think and write a bit about collective intelligence, and then I come back into the market like early in the afternoon, to decide about the closure of my trade for today. I think I like stepping back more than going psycho, and I choose path B. I am busying myself at phrasing out some intuitions about collective intelligence. What we do is in loop with what we claim we should do, and what we do is the stronger of the two. In other words, behaviour is in loop with consciously formulated cultural content, and, on the long run, behaviour is the spiritus movens of that interaction. In my so-far work, I apply this claim mostly to strategies and ethical values. The latter, i.e. collective ethical orientations, are particularly fascinating for me. I have developed a very simple neural network to uncover the values of a society, out of quantitative socio-economic data. As regards this path of thinking, at the limit of science and philosophy, you can find it developed a bit more in the You Tube video ( ), which accompanies this update.

It is 12:05. A quick update on the market. Biomed Lublin – on 11:50, it was at PLN 3,53, and it is essentially climbing. Much above my break-even threshold. The situation unfolds, as for now, unfavourably for my strategy. With that price, there is no way I should buy it back. Airway Medix – on 11:52, it was at PLN 0,74. Too expensive. Am not going to buy back in. Biomaxima – the price is growing, on 11:50 it was at PLN 23,60. Not buying back.  11Bit –  falling gently, on 11:56 was at PLN 359. Asseco Business Solutions stays firmly stationary, almost no trade at all. Bioton – sort of hesitating, swinging up and down. On the whole, it shows a descending trend. On 11:57, it was at PLN 4,45. Mercator Medical shows a gently ascending trend in price. On 11:58, it was at PLN 27,50.

For the moment, my attempt at short-term trade in the surfing-the-descending-wave style has failed lamentably. Even if I decided to sell the same positions I have actually sold, the later during the day, the better profit I would have. I yielded to panic, and this is something I need to work on. I noticed that I tend to consider profit on my investment positions as something really my own: I develop an emotional attachment to those margins. I need to step back. Still, this is good learning. There is some hope, though. Yesterday, prices really collapsed by the end of the day. Maybe today it will be the same?

As I have feeble prospects to unfold my initial strategy, the plan B, i.e. buying into the positions still held, sounds like a good idea. I am going to wait until around 2 p.m., and then it will be time to go into the fine details of the plan B. For now, I take a partial decision: I am buying further into Mercator Medical. The price is growing steadily over the day, there is no apparent reason why it should fall. I decide to place a ‘buy’ order on this one, 40 shares.

As I am waiting for the right moment to conclude on my biotech positions, I am observing the market. There is that gaming company, Artifex Mundi, sort of a cousin to the 11Bit I already have in my portfolio. I wonder: maybe it would be a good step to diversify, from that overexposure in the biotech sector, into the IT? That Artifex Mundi thing has a nice growth today, and it looks as if they were bouncing back from a temporary trough. Looks like a classical configuration of bull horns. What if I spread the cash I have in hand between Bioton, 11Bit and Artifex Mundi?

I ask myself strange questions. I have set my limits for buying back into Airway Medix, Biomed Lublin, and Biomaxima. Does it mean that I will ever buy their stock again only if their respective prices go below those limits? What if they don’t? Should I refrain like forever from buying those stocks? Funny, I haven’t thought about it before. How long is enough to forget that I could have done a better business?

In the meantime, I notice that I have received the money transfer from my international investment account with the DEGIRO platform. Happened faster than I thought. I am forwarding this money into my Polish investment account.

2:15 p.m. Another market check today. 11Bit keeps swaying gently. It could be interesting to buy in. Biomed Lublin is anchored around PLN 3,50, above my critical threshold. Airway Medix is at PLN 0,71. Just at my threshold, buying those shares back would be stupid now. Artifex Mundi keeps an interesting high, could be worth having a go. Asseco Business Solutions went down slightly. I don’t know what to think about it. Bioton is at PLN 4,40. It does not look good. I prefer to wait with buying into this position. Mercator is around the same position. Biomaxima at PLN 23,80, way above my break-even-threshold.

3 p.m. Decision time. I split my investment between four companies: 11 Bit, Artifex Mundi, Bioton, Airway Medix (at 0,7, below threshold, I buy back 2400 shares; a bit of risk, but workable).

Doing things we don’t quite know how to do well is what we, humans, do all the time

My editorial on You Tube

Here I go again with my investment strategy, and with a live account of what is happening in a tiny little, Central European stock market, namely in Poland. This is a crazy rush on biotech and medical companies, with their market value growing like hell. I joined the fun, like 2 weeks ago, and this is madness, like really. In this update, I am trying to find some method to that madness, and more specifically, I am going to investigate the kind of business, and the kind of assets I have invested in.

Before I develop further, a few words about my stance on the current situation. As I go on any medium, social or general mainstream, everybody is taking a position regarding the COVID-19 pandemic. I am a strong partisan of getting my s**t together in the presence of danger, rather than moaning and complaining. I guess the way I can get my s**t together is to be a good person to the people whom I am close to – my son, my wife, my elderly aunt – then to be a good teacher to my students, and, on the top of that, to be an inspirational scientific blogger for whomever wants to read my blog (  ) and follow my You Tube channel ( ). When I see a lot of people freaking out about things which they don’t have any leverage on or which are really secondary in the present situation, I say to myself: ‘This is the right moment to remain calm and be the glue which holds at least some things together’.

Yes, things are rough now, and they are going to stay this way for quite some time, and they are likely to drift into even stormier waters. Life is brutal, as we used to say in Poland, back in the times of communism. Yes, it is, and whatever kind of coziness we develop, it is just a soap bubble. Thus, however rough things are going to be, there is always a tomorrow, and it is a good idea to work (work, not moan) to make that tomorrow a better place.

Now, a tough question comes: do I really think that investment in the stock market, even successful, can make tomorrow a better place for anyone else than me? I am honest: there is egoistic pursuit of gain in what I do, yet there is more. I deeply believe that the Beasty (you know, THAT virus) is already changing our civilization. We will have to be tougher and more resilient, and healthcare is one of the fields which the Beasty has really exposed as f**king feeble. We will need better healthcare, and more of it, and we will need a lot of good, new science in the game, properly developed into something workable in real life. I hope that massive investment in biotech stocks, currently taking place in Poland, means a deeper, fundamental drift of resources towards that industry as a whole. I hope that by investing in this sector via the stock market, I am taking part in something socially valuable, which will pay off in the future at many levels of economic utility. I want to find my bearings in that social change.

Moral stance taken on the virus and its corollaries, I pass to the substance of my update: my investment strategy and its scientific development, peppered with some educational content addressed to students of economics and management, my students as well as students in general.

Here are the positions open in my portfolio (hyperlinked names send you to investor-relations’ sites of those companies): 11Bit (IT), Asseco Business Solutions (IT), Bioton (biotech), Biomed Lublin (Biotech), Biomaxima (Biotech), Airway Medix (medical equipment), Mercator Medical (medical equipment). 11Bit and Asseco Business solutions are pre-COVID-crisis acquisitions (beginning of February 2020), and I bought all the rest over the last 2 weeks. As for April 7th, 2020, in the morning, thus ahead of the trading day, my weighted rate of return on investment with that portfolio is 188,4%. Yes, you have seen right. The thing almost tripled in value, and still, I have some positions with negative returns. I start the detailed analysis of that stuff with specifying the individual rates of return I have on each position. Here comes the table with a snapshot of my portfolio.

Company (position)Number of shares heldPrice per shareValue in portfolioRate of return on investment, net of brokerage fee
11Bit4       469,50  PLN    1 878,00  PLN-16,39%
Asseco Business Solutions25         31,40  PLN       785,00  PLN-5,88%
Bioton200           5,30  PLN    1 060,00  PLN-15,87%
Biomed Lublin1000           5,00  PLN    5 000,00  PLN410,20%
Biomaxima20         26,80  PLN       536,00  PLN21,82%
Airway Medix2300           0,95  PLN    2 194,20  PLN116,82%
Mercator Med.20         32,10  PLN       642,00  PLN19,33%

As I am writing these words, I am lurking on how the market is doing, in real time. Bioton falls by 14%. Biomed Lublin falls too. There is visibly a market correction. Do I cut my losses short and sell, or is it just some trading game, and I should hold? Example of emotions vs intellect. As I observe these two, since the beginning of the trading day, i.e. since 9:00 Central European time, there have been a few spikes in volume traded. Some people have either decided to consume their profits from the past days, or to punch the market a bit so as to make the price go down, and they buy back in. Still, both stocks climb back. The morning loss folds onto itself.

Right now, I am experiencing that discrepancy between the long-range view, proper to investment strategy, and the immediate shot of adrenaline on the moment of trading and seeing the market change in front of my eyes (literally, I see it on the screen of my MacBook).

Good. I detach myself a bit from the immediate experience, and I give my mind a kick, so as it takes flight, back into the high registers of prudent, long-seeing strategy. I am going to develop on two points. The method of calculating the weighted rate of return on the whole portfolio, in the first place. That’s educational, skip it if you know it. Then comes the market-to-book analysis, just to see the size of financial bubbles on each of those positions, as well as on the whole thing together.   

I go educational. The first step is to estimate the structure of the portfolio: I calculate the percentage share or the percentage contribution of this specific position to the whole portfolio.

In the next step I take the individual rate of return that comes with any individual investment position, and I multiply it by the share of the corresponding stock in my portfolio. I go like: ‘how important is that thing multiplied by what pay-off that thing brings me’. Once that individual multiplication done, I get the weighted individual rate of return. I do the same for each company, whose shares I hold. Next, I sum up all the thus-calculated, weighted rates of return. The sum total is my WEIGHTED AVERAGE RATE OF RETURN.  

Good, having delivered the parcel of basic teaching, I go into strategizing, i.e. into trying to predict things which are essentially impossible for a human to predict 100% accurately. Doing things we don’t quite know how to do well is what we, humans, do all the time. This is probably how we do so well, at the end of the day.

I walk down a classical financial analysis called ‘market to book’. I take the market capitalization of each company (data from market closure on April 6th, 2020), and I divide it by the book value of its equity. The table below summarizes the results. You see? I like weighted averages. I did it again with the ‘market-to-book’ ratio.    

Company (position)Total market capitalization (PLN mln)The coefficient ‘market-to-book’ (to book equity)
Asseco Business Solutions1094,333,46
Biomed Lublin311,39,47
Airway Medix55,731,67
Mercator Med.339,912,55
Weighted average4,74

By the look of it, the whole thing looks pretty swollen. Only Bioton keeps a low profile, and there is visibly some potential for long term growth. As I am writing these precise words, it is 1:30 p.m., April 7th, 2020, and I keep lurking at the stock price graphs in real time, and what I see is a downwards revision. Not much, yet prices go down a bit. Minds calm down, gambling yields to strategizing. That’s good, on the whole. Yes, I lose some money from my portfolio, as the day grows older, but I have a comfortable cushion under my ass, anyway, and too much of a speculative bubble is never good for any market. Besides, as I look at those intraday quotes, it was a nosedive in the morning, followed by a gentle growth, yet too gentle to compensate the dive. I will see tomorrow. If it is the same, I will sell, just to keep my gains and see what happens next. By the way, this is a good example of balance between the perceived value of financial stock, and the perceived value of money.   

Now, I want to walk a bit down the avenue I hinted at in my previous update, the one entitled ‘Which table do I want to play my game on?’: to what extent that rush on the stock of biotech companies will reflect in a fundamental change as regards their business? I want to focus on one specific question: ‘What if these companies reacted to that push from the stock market, by   accumulating capital in assets at the same pace as their market capitalization grows?’. From now on, I will focus on the biotech and medical companies in my portfolio. I assume that right now, those from the IT sector follow slightly different a trajectory. I summarize that hypothetical change in the table below.

Company (position)% change in market capitalization over the COVID crisis, since January 1st 2020Assets now (PLN mln)Hypothetical assets, if following the market push (PLN mln)
Bioton33,0%914,181 215,84
Biomed Lublin376,2%81,11386,26
Airway Medix68,6%43,0072,48
Mercator Med.206,3%386,711 184,52
Sum Total1 468,423 182,01

I quickly check the active side of those companies’ balance sheets, so as to nail down the distinction between fixed assets and current assets. I translate the simulation from the table above into a hypothetical investment in fixed assets. Here are the results, i.e. the hypothetical amounts of capital, to be possibly invested in the productive base of those five biotech and medical players: Bioton +PLN 254,39 mln (+ €56,03 mln), Biomed Lublin + PLN 249,62 mln (+ €54,98 mln), Biomaxima + PLN 167,68 mln (+ €36,93), Airway Medix + PLN 24,96 mln (+ €5,50 mln), Mercator Medical + PLN 403,64 mln (+ €88,91).

Now, I have a stupid question. If I were the CEO of Biomaxima (which I am pretty sure I am not likely to be in the predictable future), and I were offered €36,93 of capital to invest in the fixed assets of my business, would I know at all what to invest that money into? I mean, that would mean making my business more than seven times bigger, like in one go. Interesting.     

Lettres de la zone rouge

Mon éditorial sur You Tube

Ça fait du temps depuis ma dernière mise à jour en français. Après une période de silence complet, suivie par une période de mises à jour exclusivement en anglais, je retourne à écrire en français aussi. C’était le rythme que je suivais dans le passé et j’aimais bien. Écrire en anglais et en français, sur les mêmes sujets, me donne comme une perspective sous deux angles différents. Oui, je sais, vu que nous avons des traducteurs automatiques, à présent, nous devenons habitués à l’idée que des langues différentes sont des façons alternatives de dire la même chose. À travers mon expérience personnelle, je peux dire que ce n’est pas vrai. Bien sûr, il y a dans chaque langue cette couche parfaitement traduisible, comme les jours de la semaine. Néanmoins, il y a plus : une langue est une structure cognitive que j’utilise pour appréhender la réalité. Mon polonais natal, l’anglais et le français, bien que pas très distants géographiquement, sont pour moi des structures cognitives distinctes.

Le fait de réalité que je suis en train d’appréhender à travers ces paires de lunettes différentes est le fait de perdre de l’argent en Bourse. Douloureux mais éducatif. Je veux faire cette expérience encore plus éducative en la discutant en des langues différentes. C’est le truc ninja que j’ai découvert en bloguant : lorsque je décris et discute par écrit ce que je fais je développe mes compétences dans ce champ d’activité spécifique.  Ça fait quelques semaines que j’avais décidé de retourner dans le jeu boursier, j’utilise mon blog pour développer ma stratégie d’investissement à long terme et j’ai déjà donné un compte rendu progressif de ce retour dans mes mises à jour en anglais : « Back in the game »  , « Fathom the outcomes », « Sharpen myself », « Bloody hard to make a strategy » et enfin « Rowing in a tiny boat across a big ocean ».        

J’avais décidé de retourner dans le jeu boursier juste avant la panique coronavirus. C’est comme dans ces films, où le personnage principal s’arrête dans un hôtel paisible et le jour suivant l’endroit est attaqué par des loup-garous ou bien un volcan explose dans la proximité. La panique explose dans les marchés financiers et moi, je me dis deux choses. Premièrement, bien sûr, je me dis : « Merde ! Fallait vraiment que ça arrive juste au moment où j’ai décidé de redevenir investisseur… ». Ensuite, lorsque je passe au-delà de ce gémissement de base, je me dis : « Des stratégies efficaces à long terme, ça se forge plus que ça s’invente. Il faut de l’adversité pour se faire une idée juste de ce que mes idées valent vraiment. Une bonne stratégie d’investissement sur plusieurs années – donc précisément ce que je veux développer – je ferais mieux de la tester dans un environnement difficile ».

Le contexte, c’est surtout du rouge. Dans mon portefeuille de valeurs, le sang coule abondamment. Cette métaphore veut dire que je note des pertes – habituellement affichées en rouge – sur presque toutes mes positions d’investissement. Presque toutes : je vois une petite tâche verte, donc un retour positif sur l’investissement. C’est Incyte Corporation où je note un gain de +1,01% sur le prix initial d’ouverture. La question intuitive est « pourquoi ? », donc pourquoi est-ce que je gagne sur cette position spécifique pendant que le reste sombre dans le bain de jus de betterave (je ne veux pas répéter le mot « sang » tout le temps ; la betterave, ça peut être tout aussi dramatique, sous certaines conditions). Les questions qui viennent à l’esprit en premier lieu ne sont pas nécessairement les plus pertinentes. La recherche scientifique, ça m’a appris qu’au lieu de demander pourquoi, il vaut mieux demander « comment ? ». Lorsque je développe une compréhension approfondie de la façon dont les évènements surviennent, je peux généraliser en forme des raisons et causalités.

Lorsque je veux comprendre le comment des choses, j’aime bien utiliser la comparaison, bien dans l’esprit des empiristes. Je compare donc ce qui s’est passé avec Incyte Corporation avec ce qui est arrivé à Virgin Galactic Holdings , qui est la perte la plus vertigineuse dans mon portefeuille : – 34,13% en moins de deux semaines. Je teste donc la qualité du service et je fraye mon chemin à travers la première couche du « comment ? » : l’analyse technique. J’étudie les prix transactionnels et les volumes des transactions, pour ces deux valeurs (actions d’Incyte Corporation et celles de Virgin Galactic), afin de trouver des régularités. Puisque je veux expliquer la différence en termes de mon retour sur l’investissement en ces deux positions, je couvre la période de celui-ci, depuis le 18 février 2020 jusqu’à la dernière cotation, vendredi le 6 mars. Les chiffres correspondants à mon analyse se trouvent dans les deux tableaux ci-dessous. Plus loin, donc en-dessous des deux tableaux, je développe mon analyse.       

Incyte Corporation
Date  Volume des transactions  Prix  Valeur totale des transactions
2020, Février 18                 1 209 877   $                     79,30  $       95 943 246,10
2020, Février 19                 1 895 420   $                     82,42  $     156 220 516,40
2020, Février 20                 2 653 348   $                     82,77  $     219 617 613,96
2020, Février 21                 1 413 961   $                     80,89  $     114 375 305,29
2020, Février 24                 1 366 786   $                     78,87  $     107 798 411,82
2020, Février 25                 2 174 593   $                     77,32  $     168 139 530,76
2020, Février 26                 1 442 275   $                     77,97  $     112 454 181,75
2020, Février 27                 1 641 737   $                     75,84  $     124 509 334,08
2020, Février 28                 2 525 548   $                     75,41  $     190 451 574,68
2020, Mars 2                 2 261 393   $                     79,06  $     178 785 730,58
2020, Mars 3                 1 939 411   $                     77,80  $     150 886 175,80
2020, Mars 4                 2 043 844   $                     80,16  $     163 834 535,04
2020, Mars 5                 1 430 221   $                     78,61  $     112 429 672,81
2020, Mars 6                 1 800 123   $                     76,04  $     136 881 352,92
Virgin Galactic
Date  Volume des transactions  Prix  Valeur totale des transactions
2020, Février 18             104 077 763   $                     30,30  $   3 153 556 218,90
2020, Février 19               84 891 132   $                     37,35  $   3 170 683 780,20
2020, Février 20               45 297 426   $                     37,26  $   1 687 782 092,76
2020, Février 21               45 297 426   $                     33,87  $   1 534 223 818,62
2020, Février 24               46 110 165   $                     34,29  $   1 581 117 557,85
2020, Février 25               44 092 654   $                     34,04  $   1 500 913 942,16
2020, Février 26               40 127 391   $                     28,75  $   1 153 662 491,25
2020, Février 27               47 987 693   $                     21,97  $   1 054 289 615,21
2020, Février 28               35 531 152   $                     24,60  $      874 066 339,20
2020, Mars 2               20 098 112   $                     25,98  $      522 148 949,76
2020, Mars 3               20 098 112   $                     24,71  $      496 624 347,52
2020, Mars 4               15 466 394   $                     23,76  $      367 481 521,44
2020, Mars 5               14 124 114   $                     24,09  $      340 249 906,26
2020, Mars 6               12 867 806   $                     21,67  $      278 845 356,02

Le truc de base à se mettre en tête est que ces chiffres représentent, en partie, mais seulement en partie, des comportements humains – des décisions complexes prises en des situations d’incertitude – et la partie non-comportementale (ou plutôt pas immédiatement comportementale) correspond aux transactions automatisées sur la base des logiciels d’intelligence artificielle. Je décris les décisions des logiciels IA comme pas immédiatement comportementales puisque à l’origine, leurs algorithmes sont basés sur une logique imposée par leurs créateurs humains. D’habitude, des logiciels d’investissement contiennent une partie génétique, où l’algorithme s’optimise lui-même en écrivant des lignes de code supplémentaires, donc une fois lâchés de leur laisse, ces trucs peuvent former leur propre logique. Encore, il faut se souvenir que la plupart de ces logiciels achèvent une optimisation linéaire tout à fait simple, du type « donne mois plus de retour que celui offert par l’indice boursier ».

Chaque décision individuelle – donc strictement, humainement comportementale – prise dans le jeu boursier ressemble à surfing. Il y a une force motrice prédominante, soit la tendance temporaire du marché. L’investisseur comprend quelque peu de cette tendance, mais cette compréhension est toujours partielle. Ce que moi je veux comprendre maintenant est la tendance du marché dans ces deux cas – Incyte Corporation et Virgin Galactic Holdings – ainsi que des fines déclinaisons de cette tendance, des déclinaison qui font la différence dans mon retour sur ces deux investissement.

Par vertu de la théorie économique de base j’assume que le comportement de base dans le  marché boursier est la triade sacrée : acheter, garder ou vendre. Moi, pour le moment, vu la panique « coronavirus » je garde mes positions d’investissement comme elles sont, sans acheter plus et sans vendre. Les décisions d’acheter et de vendre sont largement symétriques : elles influencent le prix d’une valeur boursière lorsqu’elles rencontrent l’une l’autre et lorsqu’une transaction est conclue. En termes de comportement, la variable la plus intéressante est le volume des transactions, soit le nombre des valeurs échangées, dans la première colonne numérique de chaque tableau.

Là, dans les cas respectifs d’Incyte Corporation et de Virgin Galactic Holdings, deux modèles se dessinent. Le volume des transactions sur Incyte Corporation oscille, en le dernier volume enregistré, vendredi 6 mars, est en fait supérieur au premier volume observé le 18 février. L’intensité d’échange sur cette valeur démontre quelque chose comme réflexion intense de la part des investisseurs. Ce volume n’est pas du tout corrélé avec les variations des prix : le coefficient de corrélation de Poisson tombe à r = 0,06. Vu la structure mathématique de ce coefficient, il y a probablement trop d’à-coups soudains dans les deux variables. Ça remue, quoi. Si je gagne ou je perds sur cette position dans le marché, c’est précisément parce que ça remue. Dans le cas de Virgin Galactic Holdings, le volume des transactions suit une trajectoire descendante sans équivoque – tout comme le prix – et les deux sont significativement, positivement corrélés, avec r = 0,59. En même temps, bien le volume des transactions strictement dit que la valeur agrégée de ces transactions étaient beaucoup plus élevées dans le cas de Virgin Galactic Holdings que dans celui d’Incyte Corporation.

Je vois donc que les investisseurs se comportent de façon différente vis-à-vis de ces deux valeurs. Le marché boursier est complexe, il marche largement sur anticipation faite sur la base d’information vraiment disparate, et ces différences peuvent être largement le résultat des facteurs autres que les traits individuels de ces sociétés. Ceci dit, les caractéristiques individuelles de ces deux business respectifs peuvent jouer un rôle important pour leur performance boursière. Je passe dont de l’analyse technique à l’analyse fondamentale et jette commence à feuilleter (figurativement, bien sûr, ce sont des documents PDF) leur rapports annuels.   

Incyte Corporation c’est du business bien ancré financièrement. Plus de deux milliards de dollars de revenu en 2019, avec presque 447 millions de bénéfice net, c’est du solide et du hautement profitable. En plus, lorsque j’observe leur compte d’exploitation sur la période 2015 – 2019, je vois in progrès constant et solide. En revanche, Virgin Galactic Holdings c’est plutôt du futur que du présent. Le modèle de business consiste surtout en des dépenses substantielles sur la recherche et le développement des nouvelles technologies (presque 133 millions de dollars) – il s’agit des technologies de voyage spatial commercial – orné ci et là avec des revenus symboliques de 3,8 millions de dollars. Bien sûr, les opérations courantes de ce business sont profondément déficitaires.

Je connecte ces deux observations à la théorie d’investissement formulée par James Tobin et William Brainard, linguistiquement intéressante pour les francophones puisqu’que dans le jargon économique elle est désignée comme la théorie du « q » (regardez, par exemple : Yoshikawa 1980[1]). Dans cette perspective théorique, les titres financiers sujets à l’échange boursier sont surtout et avant tout des titres de contrôle d’actifs productifs exploités par les sociétés émettrices de ces titres. Dans la longue perspective, le marché boursier est donc fortement connecté au marché d’actifs productifs – donc le marché des technologies et de l’immobilier industriel – et cette connexion est plus importante que la mécanique purement interne de la Bourse.

Je me pose la question suivante : comment cette connexion entre les actifs et l’échange boursier d’actions marche dans les deux cas étudiés ici ? Dans le cas d’Incyte Corporation , le 18 février les investisseurs avaient fait des transactions égales à 2,8% d’actifs totaux de la société et le 6 mars les transactions journalières avaient fait 3,99% de la valeurs comptable d’actifs. Avec Virgin Galactic Holdings , c’est une histoire différente : le 18 février le mouvement boursier sue leurs actions avait fait 520,78% de la valeur comptable de leurs actifs, pour descendre à 46,05% desdits actifs dans la journée du 6 mars. Je vois donc deux modèles comportementaux complètement différents dans les décisions d’investissement boursier dans ces deux sociétés. La différence entre ces deux modèles comportementaux peut être liée de la différence sectorielle : Incyte Corporation c’est de la biotechnologie bien tassée et Virgin Galactic Holdings c’est un rêve follement charmant d’organiser des vols orbitaux à l’échelle commerciale et ce rêve semble avoir un fort potentiel de générer des retombées technologiques substantielles.

Maintenant, j’applique la même méthode de comparaison – volume des transactions, valeur totale des transactions – aux deux autres valeurs dans mon portefeuille, toutes les deux dans le même secteur cette fois. Je parle du secteur des technologies photovoltaïques et là-dedans, j’ai investi dans les actions de First Solar (- 21,07% de perte dans mon portefeuille) et dans celles de Vivint Solar (perte – 7,96%). Bien que dans le rouge après vendredi dernier, ces deux valeurs c’étaient défendues longtemps contre la panique « coronavirus ». Encore mardi dernier, j’avais un retour positif sur ces deux positions. Toutes les deux démontrent une proportion similaire entre la valeur totale des transactions boursières et la valeur comptable des actifs. Dans le cas de First Solar , cette proportion était de 1,04% le 18 février et 0,84% vendredi 6 mars. En ce qui concerne Vivint Solar , on parle de 0,54% le 18 février et 0,80% le 6 mars.

Ci-dessous, dans deux autres tableaux, je présente les données détaillées à propos de ces deux sociétés. Je continue mon développement plus loin.  

First Solar
Date  Volume  Prix  Valeur totale des transactions
2020, Fevrier 18   1 407 357   $                     55,65  $       78 319 417,05
2020, Fevrier 19     1 945 614   $                     57,37  $     111 619 875,18
2020, Fevrier 20   4 156 485   $                     59,32  $     246 562 690,20
2020, Fevrier 21   9 774 901   $                     50,59  $     494 512 241,59
2020, Fevrier 24    3 700 847   $                     51,21  $     189 520 374,87
2020, Fevrier 25 2 807 226   $                 48,57  $     136 346 966,82
2020, Fevrier 26 2 670 436   $                     46,11  $     123 133 803,96
2020, Fevrier 27 2 699 288   $                  44,25  $     119 443 494,00
2020, Fevrier 28 2 950 667   $                     45,77  $     135 052 028,59
2020, Mars 2 2 730 409   $                     44,95  $     122 731 884,55
2020, Mars 3 1 569 455   $                     44,21  $       69 385 605,55
2020, Mars 4 1 340 145   $                     45,48  $       60 949 794,60
2020, Mars 5 1 259 142   $                     45,47  $       57 253 186,74
2020, Mars 6 1 448 658   $                     43,37  $       62 828 297,46
Vivint Solar
Date  Volume  Prix  Valeur totale des transactions
2020, Fevrier 18 1 319 176   $                    11,04  $        14 563 703,04
2020, Fevrier 19 2 290 068   $                    11,80  $        27 022 802,40
2020, Fevrier 20 4 279 615   $                    12,85  $        54 993 052,75
2020, Fevrier 21 3 125 854   $                    11,44  $        35 759 769,76
2020, Fevrier 24 2 476 290   $                    11,76  $        29 121 170,40
2020, Fevrier 25 2 004 507   $                    11,59  $        23 232 236,13
2020, Fevrier 26 3 798 572   $                    11,91  $        45 240 992,52
2020, Fevrier 27 3 563 184   $                    11,08  $        39 480 078,72
2020, Fevrier 28 2 526 386   $                    11,24  $        28 396 578,64
2020, Mars 2 3 188 036   $                    11,19  $        35 674 122,84
2020, Mars 3 2 886 017   $                    11,69  $        33 737 538,73
2020, Mars 4 1 539 854   $                    11,91  $        18 339 661,14
2020, Mars 5 1 478 135   $                    11,73  $        17 338 523,55
2020, Mars 6 1 990 593   $                   10,78  $        21 458 592,54

Voilà donc qu’une régularité se dessine. Dans la panique ambiante des marchés financiers, parmi les quatre valeurs que je viens d’analyser point de vue prix et volume, les deux gagnants – Incyte Corporation toujours dans le vert et Vivint Solar juste un peu dans le rouge – démontrent un trait commun intéressant. Dans les deux cas, entre le 18 février et le 6 mars, le coefficient « valeur totale des transactions boursières par jour divisée par la valeur comptable des actifs » démontre une tendance croissante, tout en restant relativement modeste.

Par ailleurs, dans le cas des sociétés du photovoltaïque, on peut remarquer les retombées des derniers développement aux États-Unis. Selon, en janvier 2020, l’administration du président Donald Trump avait donné le feu vert pour la construction de la première méga-ferme solaire dans le désert californien et cette ferme va être construite précisément par First Solar. On peut voir qu’entre le 18 et le 21 février le volume des transactions en actions de First Solar avait bondi tout à coup, tout en faisant des vagues côté et Vivint Solar.    

Bon, c’est tout dans cette mise à jour. Vous pouvez me contacter à travers la boîte électronique de ce blog : .

[1] Yoshikawa, H. (1980). On the” q” Theory of Investment. The American Economic Review, 70(4), 739-743.

Sharpen myself

My editorial on You Tube

On February 17th, I sold my position in ATM Grupa. I managed to strike a deal at PLN 4,9 per share, which, after transactional fees, gave me a two-week rate of return at 1,74%. Once again, I broke the rules I declared I would follow. I was supposed to take investment decisions once a month, and here I made one half-way through that period. I wonder what exactly is at work in me, when I suddenly do things like that. The simplest answer would be: ‘Lack of discipline’ etc. Yes, it was lack of discipline, and it occurred in a person – me – who is prone to compulsive discipline, like really. In many other fields of my life, I tend to be overly consistent. I am like one of those golems in Terry Pratchett’s novels. When you tell me to dig a hole in the ground, I will keep digging until you tell me to stop, and if you forget to tell me to stop, well… I will keep digging. People around make me understand, every now and then, that it would be a good thing to accept a bit of chaos into my order.

Thus, what makes me suddenly less consistent when it comes to financial investment? Would it be about a subjectively new type of match between information and decision? Looks like… Another hypothesis is that what I see, for the moment, as lack of consistency, is precisely the right amount of consistency. Maybe my initial assumptions – making investment decisions once a month, as I collect my rent from real estate once a month – were wrong. This is a tricky one: on the one hand, investing capital at the same pace it comes to me is pretty intuitive, and yet, on the other hand, financial investment is supposed to have liquidity, and my own investment strategy should bring me more than just the average rate of return based on market indexes.

One thing is certain: given my ordinary schedule of work, it takes many days, even weeks, to plough through the information I need to make really informed investment decisions. Maybe I can use a strategy in two steps: once a month big shopping with the freshly received rent, and mid-month a correction of the course.

For the moment, I have just taken into account the advice that professionals give: cut your losses short. After having sold ATM Grupa, I have just decided to sell the positions I was losing money on: OAT, Aprea Therapeutics, Vir Biotechnology, Aston Martin, Black Diamond Group, PGE, Cyfrowy Polsat. I sold them all at market price. With the proceeds from selling and the Polish CDM platform, thus with proceeds from selling ATM Grupa, Cyfrowy Polsat, PGE, and OAT, I bought into one position, a gaming company: 11 BIT Studios. This particular egg in my basket is partly what I initially outlined as my strategy, and partly completely not. I guess something similar can be said about most things I do in life. Anyway, with an equity of roughly PLN 106,07 mln, and a market capitalization of PLN 255,93 mln, the company is clearly overvalued in the market. Still, they have good fundamentals, and their stock price growing like hell.

There is an interesting hypothesis to ponder, like generally: the financial count of equity, in a business, can be more or less accurate. The financial value of equity is an expression of underlying economic value in assets net of debt, and the interplay between financial value and economic value can take different forms. Debt is debt, and as long as I don’t want to make that debt tradable in the form of securities, it has a clear nominal value. Assets are a different story. When assets are being valued for the purposes of a balance sheet, two methods can (and should) be used concurrently: the book accounting, and the market valuation. I take the value of assets from the last time I counted it, I subtract depreciation from the current period, and I get the book value net of depreciation. From time to time, I can ask myself what price I could get for my assets if I decided to sell them. This is market valuation, and this is supposed to estimate quite closely the implicit economic utility of my assets, net of any subjective calculations of mine. It is possible that book valuation goes a long way above or below the market valuation.

Financial markets, such as the stock market, have a peculiar property, which was noticed, apparently, hundreds of years ago. When instead of trading assets in big chunks, like whole factories, we just trade small participatory titles in those assets, the financial market yields very sharp valuations of economic value. What? It is just about expectations? Hell, yes. The value of productive assets is all about expectations. Do you buy a factory in order to live inside? I guess it is for having some future business outcomes: it is about expectations. Anyway, in cases like 11BIT Studios, when equity is overvalued, but the stock price keeps flying high, and with good fundamentals, it can be hypothesised that some of their assets have greater an economic value than the official book valuation in their balance sheet. I know, I know: assuming that I see things that other people can’t see is tricky. Still, when that bloody price keeps growing, I guess other people see the same ghosts which I see, and this is reassuring.

I return to my corrective investments. In the DEGIRO platform, after having sold my positions in Aprea Therapeutics, Vir Biotechnology, Aston Martin, and Black Diamond Group, I decided to strengthen the ‘energy’ component of my portfolio. My assets of choice have been: Vivint Solar, and Norsk Hydro.  Vivint Solar’s fundamentals are sort of intriguing. On the one hand, they still lose money. On the other hand, they lose much less than they used to, and they seem being terribly resilient. I remember I spotted their financial reports in early Spring 2017, for the first time, and I was like: ‘What a sad story… Another ambitious bunch of innovators going bankrupt soon’. Still, they haven’t gone bankrupt. They are still there, they keep their head above the water, and they develop, step by step, their technological concept of small smart grids based on renewable energies. As for Norsk Hydro, these guys are fundamentally solid, period. I consider that position as a stabilizer.     

Now, once again, drums: I am drawing a bottom line under my so-far investment decisions. I sum up the state of my possessions as for today, i.e. February 19th, 2020, and I compare with the initial values on February 3rd. My account on the Polish platform CDM comes first. Starting point: February 3rd, cash 2693 PLN. Action #1: buying Cyfrowy Polsat, OAT, PGE, and ATM Grupa. Action #3: selling ATM Grupa at a negotiated deal price. Action #4: selling PGE, OAT, and Cyfrowy Polsat at market price. Action #5: buying 11 Bit at market price. Current status: cash PLN 584,73 + position on 11BIT PLN 1 936 = PLN 2520,73. Net loss of PLN -172,27, or -6,4%.

I pass to my account on the DEGIRO platform, for international investment positions. Starting point: February 3rd, 2020, cash: PLN 2 550. Action #1: I buy into Black Diamond Group, Macrogenics, Incyte, Vir Biotechnology, Amundi Epra (tracker fund), Frequency Therapeutics, Aprea Therapeutics, Aston Martin. Action #2: I buy into First Solar Inc. Action #3: I sell Black Diamond Group, Vir Biotechnology, Aprea Therapeutics, Aston Martin. Action #4: I buy into Vivint Solar and Norsk Hydro. Current status: cash €37,43 + € 512,54 worth of positions on Amundi Epra, First Solar, Vivint Solar, Norsk Hydro, Incyte, Frequency Therapeutics, Macrogenics = € 549,97 = PLN 2 348,37. Net loss: PLN – 201,63, or – 7,9%.   

In the first blog update in this fresh cycle (see Back in the game ), I wrote I am aware how humbling this learning will be. Well, it is humbling. Those losses are the cost of my learning. I understand why those tracker funds are so popular. Many people try what I am trying, i.e. learn by trial and error to invest profitably, and if one is not prepared to pay the price of learning, it is really frustrating. Yet, I am ready to pay the price, and I need to get the most value for that price. I need to learn as much as I can. In my plan, the moment of the next big shopping approaches. By the very end of February, or in the first days of March, I am supposed to invest the next rent, the PLN 2500. I have a few days to sharpen myself for that next step.

Back in the game

My editorial on You Tube

I am starting a new log of activity: investment. After some 18 months of pausing in active investment in financial markets, I am going back into the game, and I want to do it as rationally and as artfully as possible, using all the science I have in order to achieve three consecutive goals: a) achieving predictable, attractively positive growth of market capitalization in my portfolio b) adding positive cash flow to that growth of value (i.e. turning my portfolio into a source of cash revenue, and c) creating an investment fund, i.e. a fund where I manage capital entrusted by third persons. One word of explanation as for that last one, as it could seem overly pretentious. I simply want to develop my skills in investment up to a point, where a group of other people – probably a relatively small group – would trust those skills of mine enough to coordinate their capital investment in businesses of interest common to all of us. I want to develop at least one business connected to renewable energies, and to tackling climate change. Becoming a trusted fiduciary for other people’s investment, and standing up to the corresponding promises, could be quite a good step on that way.    

Over the last 3 years, starting in Spring 2017, I used a scientific blog as a tool to boost my scientific creativity and I think it worked: I reached a level where I make true discoveries, and I feel I bring a real contribution to the development of social sciences. For the time being, my biggest scientific achievement is research published: “Energy efficiency as manifestation of collective intelligence in human societies”. I intend to stay humble and consider what I do just as a contribution to the development of social sciences, not as personal glory. I also intend to develop on that science I already have, Still, achievement is achievement, I know I have gone a path of personal development as a scientist, I think I understand how I have accomplished what I have accomplished, and I want to repeat the experience with a practical application of social sciences, i.e. with financial investment.

The method I intend to use consists in keeping a log of exhaustive, written auto-analysis of what I do, publishing that analysis in the form of updates on my blog “Discover Social Sciences”, and using the insights I develop in the process so as to develop my skills as professional investor. In other words, I know that if I write a lot about what I think I do in a specific line of activity, it makes me think about what I do, and true insights appear. It is a long, laborious process, still it has one advantage from my point of view: I already know the pace of that work, and I know how to structure it, because I have already done it in another line of work, namely in science.

Publishing that investment writing on my blog will be painfully humbling. I will certainly make laughable mistakes in my investment decisions, and many a professional broker will have good times mocking how stupid and pretentious I am if I think I can become proficient enough to create an investment fund of my own. Yes, that’s the desert to walk through, and I know that walking it through brings a reward.     

I start with the account – and the analysis – of what I have done as my first steps, during those last two weeks. I am investing via two digital platforms: a Polish brokerage house CDM PeKaO, and DEGIRO for investment in foreign financial instruments. I put 2500 PLN thus some €585 in each of them, and I did some very intuitive, quick shopping. Precisely, I just did a bit of thinking before buying my first basket of financial instruments. I am learning the way I observe it in neural networks I use. Error is learning, and more error means more learning, as long as I can sustain the consequences. I make errors, I study my errors, I try to understand how exactly I make errors, and this understanding will help me to make more and more informed decisions in the future.

The way I intend to pace myself in that learning of investment is precisely based on the sequence: decision >> analysis and definition of errors >> outline of a strategy free of those errors >> implementation of the new strategy, i.e. next investment decision(s) >> analysis etc. My plan is to practice that loop on a monthly basic, i.e. I invest once a month, in a relatively short window of time, and I spend the rest of the month on studying my own decisions.   

Before I go into describing the details of those first investments of mine, which I made in the first days of February 2020, one thing as sort of popped into my mind. When I was starting to use my account with DEGIRO, I was dealing with something new. DEGIRO is not exactly a brokerage house: it is a transactional platform, something like a very fluid investment fund, where I decide what exact assets I want to have for the money I pay into my DEGIRO account. It was new for me, and I made a series of, if my memory is correct, 3 consecutive transactions where I just paid money onto the DEGIRO account and then withdrew it back onto my main bank account. Why was I doing that? Good question. When I look back at those specific decisions of mine, they were quite emotional and impulsive. I remember being sort of vibrant in my thinking, as I was stroking an unknown animal, wondering whether it is going to leap to my throat. Lesson #1: when I do a new type of financial operation, and I use a new type of financial instrument, I experience strong emotions and those emotions tend to blur my rational thinking. In this case, I was probably afraid that once I pay my money onto the DEGIRO account, there could be problems with recouping it, e.g. very high fees. As a matter of fact, none of that happened. Conclusion: I can make irrational, possibly erroneous investment decisions out of fear. I need to understand what I am afraid of, in my investment, in order to make as informed decisions as possible.

It is interesting to understand my own fears. What exactly was I afraid of, in connection with investment through the DEGIRO platform, and what triggered those fears? In the first place, I freaked out because I did not quite do my homework as for the functionalities available. When I invest with DEGIRO, my account has a few metrics. Among them, I have the amount of cash available, and the so-called ‘free space’, or the exact amount of cash I can use to buy financial assets. The default currency of DEGIRO is the euro, and my balances appear in euro. Right after I effectively transferred Polish zlotys on that account, i.e. right after they became visible as the cash balance as euros, they mirrored in the ‘free space’ account. Still, when I tried to use them for buying financial assets, the platform blocked me and an error message of ‘Insufficient free space’ was displayed. Then I freaked out. ‘They stole my money!’, I thought. I know this was stupid. DEGIRO is a licenced operator, and they are legit as for financial reliability. However, seeing that I have no full access to my cash made me extremely nervous and irrational. This is when I suddenly withdrew, back onto my main bank account, all the cash I had paid onto the DEGIRO account.

Only after having done that, I did my homework in the FAQ section of the DEGIRO page and found out what exactly happened to my money. The default currency at DEGIRO is the euro, but display in euros is not exactly the same as conversion into euros. When I do my transfer in Polish zlotys, they are recalculated into euros in real time, for the needs of display on the cash account, and in the free space account. Yet, they are not immediately converted into euros, and thus not immediately available for transactional purposed. Conversion into euros takes place automatically once a day (technically, once a night) or I can do it manually whenever I want. Thus, when I want to use the zlotys I have just transferred, I need to convert them manually into euros, or I have to wait until the next day, i.e. wait for automatic conversion.

That’s the homework I neglected to do before starting with DEGIRO, and the lack thereof made me do those frantic transfers back and forth between my basic bank account and the DEGIRO account. What exactly was I afraid of? As I try to deconstruct my behaviour, I was anxious because I thought I haven’t immediate control over my money. Fear #1: loss of control, possibly loss of immediate liquidity. It’s funny, but John Maynard Keynes wrote about the same thing: many people truly feel they have money when they are convinced they can spend it whenever they want. He called it propensity to conserve liquidity or something in these lines. Lesson #2: when I invest, I tend to be afraid of losing liquidity, i.e. immediate transactional control over my money.

My fear #2, as I think about the situation, is reputational. I was afraid that someone I know could like have a look on what I do and say: ‘You have done something stupid and you lost money’. Here comes a nice paradox: I invest online, privately, and yet I tend to be very concerned about the possible opinions of other people. A part of me want to look 100% professional in my investment decisions. I know, that’s stupid. A few paragraphs earlier I stated that I want to learn how to be a pro. Lesson #3: when I invest, I need to define my true ‘free space’, i.e. the amount of money I am ready to put on stake without being afraid of losing immediate control over its liquidity. Lesson #4: I need to work through the classical question of personal development, namely ‘How will other people know I am successful in my investment decisions?’. Good question, once again, and I think it is the right moment to describe my first investment decisions.

My general idea was, and still is, to focus on three sectors: biotechnology, renewable energies, and IT. Why? The most honest explanation is that I am interested in those fields of technological change. As it is frequently the case with general ideas, they remain sort of general. As I was sailing the ocean of investment opportunities, and as I took a total of 13 investment positions, 6 among them are biotech businesses: OAT – OncoArendi Therapeutics, APREA THERAPEUTICS , FREQUENCY THERAPEUTICS INC, INCYTE CORPORATION , MACROGENICS INC, VIR BIOTECHNOLOGY INC. Those names of companies are hyperlinked to their respective ‘Investor relations’ sites.  As for IT, I have one investment position, namely CYFROWY Polsat. They are not exactly the type of innovative IT company. It is more of a generalist in telecommunications. Why have I bought their stock? Because I have studied their case with my students, in the class of management. The same applies to a TV production company:  ATM Grupa. Lesson #5: I tend to invest in companies, which either I have an intellectual interest in, or I have discussed their cases in class.

As for renewable energies, I have one position open: FIRST SOLAR INC, a photovoltaic business. I have one more energy business, a Polish one – PGE – yet, in all honesty, you wouldn’t really call them a renewable energy-based business. It is mostly your (well, our) basic coal, with some timid glimpses of RES here and there. As for the First Solar case, I am somehow familiar with them: they were one of the first topics I discussed on my blog, back in 2017. As for PGE, kill me (figuratively), I don’t know why I opened that position. I think I was intuitively looking for something big sort of next door.

There is one position which I opened like a real dumb f**k, i.e. after having read a piece of news. I am talking about ASTON MARTIN WI, ISIN GB00BFXZC448. I read that a new big investor decided to acquire a significant portion of their stock, and I made quite stupid a move of following the grizzly bear all the way into its feeding grounds. Now, you are going to have fun. There is one company, which I haven’t the faintest idea why I opened an investment position on: BLACK DIAMOND GROUP LTD. They are in industrial real estate. WTF? Why did I do it? Go figure.  

The last investment position I took is a so-called ‘tracker’: an investment fund supposed to reflect, as closely as possible, the structure of a big stock market index. I chose Amundi Epra DR ISIN LU1437018838 . As I am deconstructing my way of thinking about it, I a pretty sure I wanted some kind of stabilizer, sort of independent from my own judgement.

As I have a look at those investments of mine, I re-ask myself the question: namely ‘How will other people know I am successful in my investment decisions?’. Two assumed factors of recognition seem to emerge from my decisions: coherence, and sort of a general alertness. I want to feel that I am following some sort of coherent strategy, and, intuitively, I want to save some of my money to investments outside that strategy, as if I wasn’t entirely trusting my own judgement.

That’s all in this update. I hope to keep a nice pace in the months to come. Thank you for your attention.