# Why Bookmakers Didn’t Find a Brexit More Likely – and why everyone thought they did

Bookies made a lot of money on the Brexit

As anyone knows by now, the British people voted for a Brexit, meaning that the United Kingdom will leave the European Union. The stock market didn’t particularly like this news, as indicated by the fact that the German DAX index opened 1.000 points, or nearly 10%, lower on the day the results became known.

It appears the majority of people expected the UK to stay in the EU. This expectation was likely fuelled by the fact that news agencies worldwide said that bookmakers (companies making their money by accepting bets) found it highly likely that Britain would stay in the EU. They pointed at the odds, or pay-offs, the bookies gave. The day before the referendum, the odds Betfair (a big bookmaker) gave were as follows: 1.16 for Bremain, 8 for Brexit. Meaning: if you would bet 1\$ on a Brexit, and it happened, you would get 8\$. For a Bremain you would get only 1.16\$.

Such a big difference in pay-off would only occur if Betfair was very sure that Britain would stay in the EU, right? Otherwise they would lose a lot of money, right?

Wrong. This is nonsense. Betfair didn’t find it more likely that Britain would stay in the EU. It probably didn’t even care, because they would profit regardless of the outcome. Let me explain this via some easy calculations.

First I show the reasoning used by the public and news agencies, such as CNBC (which said that bookies found a Bremain at least twice as likely as a Brexit, and that this was because “voting for the unknown takes higher conviction than voting for the status quo”). Suppose odds of 1.16:8 as given by Betfair. Now suppose a person bets 1\$ on Bremain. In case Bremain happens, Betfair has to pay him 1.16\$. If not, they earn his 1\$ bet. The same reasoning goes for a Brexit: the person earn 8\$ in case of Brexit, Betfair earns 1\$ in case of Bremain.

Now, what can Betfair expect to earn from this 1\$ bet? Either way, it will get the 1\$ bet. Now take p to be probability of Bremain. Then Betfair will have expected earnings of 1\$ – 1.16\$p in case of Bremain, and 1 – 8\$(1-p) in case of Brexit. The bookie of course doesn’t want to lose money. Now the only value of p at which it doesn’t expect to lose money, regardless of a Bremain or Brexit occurring, is 0.87 (calculate this if you don’t believe me). For any other probability, the person betting the 1\$ can expect to make money by betting on either Bremain or Brexit. In case of p = 0.6, for example, Betfair expects to lose 1 – 8\$(0.6) = 3.8\$ in case of a Brexit. Given that Betfair is not stupid, and doesn’t want to risk losing a lot of money, they must be damn sure of this 0.87 probability of a Bremain. Or so it would appear…

### But this is not how it works.

You can also use the expected value calculation in another way, the way used by bookies. Contrary to my example, there is more than 1 person making a bet. You can you use this information. Let’s say that 100 people make a bet of 1\$ each. Let’s say the bookie sets a pair of random odds of 4 to 9. Now assume 87 people bet for Bremain, and 13 for Brexit.

Suppose there is a Bremain. Then the bookie will earn 100\$ (100 times the 1\$ bets he receives) – 87 * 4\$(pay-out per person) = -248\$. In case of a Brexit they will earn 100\$ – 13 * 9\$ = -17\$. Something is going wrong here: the bookie will lose money in case of either a Bremain or Brexit. Apparently the odds don’t match the proportion of people voting for Bremain and Brexit.  In case the bookie changes the odds to 4:6, he will make money only in case of a Brexit, but not in case of a Bremain. Now, the only odds that will make sure the bookie never loses or earns any money, given the 87 people betting Bremain and 13 Brexit, is 1.16 to 8. This is the break-even set of odds.

Proof: in case of Bremain, the bookie will earn 100\$ – 1.16\$*87 = + – 0\$, and in case of Brexit 100\$ – 13*8\$ = +- 0\$. So irrespective of what will happen, the bookie will never lose money.  Now, by only charging a fee for using its service, or a percentage of the amount bet, the bookie will always make money. The bookie can also change the odds slightly, so that – given the same 87 people voting for Bremain and 13 for Brexit – he can make money without charging fees: if he would change the odds to 1.12:8, for example, he is still sure not to lose money in case of a Brexit, but he will actually make money in case of a Bremain.

You might think: these odds work only in case 87 of 100 people vote for Bremain, and 13 for Brexit. In case the ratio changes, so will the bookie’s earnings. That’s true. Maybe more people will be lured into betting Brexit by the 8\$ pay-off. You might get 20 of the next 100 people betting on Brexit, giving the bookie a negative pay-off of 100\$ – 20*8\$ = -60\$ in case of Brexit. What to do then? Well, you just lower the pay-off: in this case a pay-off of 5\$ for Brexit will do the trick. You can even leave the pay-off of Bremain at 1.16\$, implying that you will make money in case of Bremain and not lose anything in case of Brexit. The point being: the odds are constantly adjusted, reflecting the ratio of bets at the time, so that the bookie is sure never to lose money. He is likely to use some margin of error in the odds so that, until a more accurate set of odds is reached, he will still not lose any money.

So we cannot say that the bookies thought a Bremain more likely than Brexit. Looking at the odds, we can only infer that much more money was bet on a Bremain than a Brexit, as shown by the implied probability of 0.87.

But what was the real probability that British people would vote for a Brexit? Until two days before the Brexit, polls were published, which showed the referendum to become a very close call. Some polls showed Leave to be in front with 52% to 48%, others (such as the Financial Times poll) showed Stay to be in front. Either way you look at it, judging by the polls, there was no reason to assume that a Bremain was much more likely than a Brexit. Given an expected value calculation, and assuming probabilities of 55% for Stay and 45% for Leave, betting for a Brexit would give you an expected: -1 + 0.45*8 = 3.60\$ while betting on a Bremain would lose you an expected: -1 + 0.55*1.16 = 0.36\$. Hence you should have always bet for a Brexit. Not only in retrospect (I didn’t do this; read the sidenote).

This is one of the clearest examples of a positive expected value calculation I have ever seen in practice. There is pretty much a 50-50 probability of something happening, and choice A provides you with a pay-off of 1.16, while choice B gives you 8. Then what do you choose?

Sidenote:
I must admit that I expected the British people to stay in the EU. I didn’t think it likely that the average British person would vote for an option that, to me so, obviously seems to decrease their wealth, and therefore their well-being. Leaving the EU forces the UK to start a lengthy process of negotiating new trade contracts with the EU. While the EU has many parties it can trade with, since it already has many contracts in place, the same will not hold for the UK once it is out of the EU. This implies that it has a bad bargaining position, since the need for the UK to trade with the EU is much larger than the other way around. This will likely lead to suboptimal trade contracts for the UK. Furthermore, given the slowdown in economic growth and downturn in the financial markets that were to be expected, the average Brit could have expected a decrease in his material well-being, either through a decrease in job certainty or a decrease of his pension money. Not to speak of the 15% more expensive holidays and imported computers. It was a valuable lesson to me: do not fare on possibly wrong assumptions while the data is so clear.

# Why Trading Is Not a Game Of Chance

I recently had a discussion with a friend of mine. He said to me: ‘Be honest now. Trading is no different from playing roulette, right? You either win or you lose. It is just a matter of chance’.

What he really meant to say was that investing is a game of chance in a way similar to poker, rolling a dice or roulette. But although I agree with my friend that uncertainty is an intrinsic part of trading (or investing for that matter), it doesn’t follow that trading is a game of chance in the same way that poker, rolling a dice and roulette is. Not because trading requires certain skills that might allow you to beat the odds – for the same could be said of poker. It has to do with mathematics, and probability theory in particular.

I want to show this through the notion of expected value. The expected value of a random variable is its long-term average, or the value the variable takes on average per execution of the respective random process. Very briefly: in the case of rolling a dice, the expected value is 3.5 ((1 +2 + 3+ 4 + 5 + 6)/6), because in the long run you will get an average of 3.5 eyes per throw.

Certain requirements have to be met in order to to be able to calculate the expected value of a random variable. First of all, one should be able to fix the sample space of the process, or ‘the set of all possible results’ of the random process. In case of roulette, this set is unambiguous: number 1, 2,….., 38, because the ball can fall on one (and only one) of these numbers. Now, knowing this sample space plus the probability of the ball falling on any of these numbers plus the pay-offs of the ball falling on any of these numbers, you can determine whether you should take a bet or not. For example: let’s say you get 100\$ per every 1\$ you bet on the ball falling on number x. Then the expected value of betting 1\$ on number x is (1/38 times 100\$) + (38/38 times -1) = 1.63, meaning that in the long run you will make an average of 1.63\$ per round per 1\$ you bet when following this strategy. Since you will make money on average, you should pursue this strategy.

All well and good, but what happens when we take the market, instead of a roulette wheel, to be the random process we focus at? Let’s help ourselves a bit, and focus on a very restricted part of the market: the Brexit-debate. We can take the relevant possible results of the Brexit-debate as our sample space, the value of the DAX-index to be our pay-off, and the probability simply the probability of each possible result happening.

Now we come to face a couple of great difficulties.

Problem 1: sample space and the unknown unknowns
There appear to be only two possible results of the debate – Brexit, Bremain. Now we can define a random variable X such that any outcome of the random process is mapped to a real value. We choose the DAX-index to be our real value. You can for example say that in case of a Brexit, the value of the DAX-index will be 9000, and in case of a Bremain 10.400. Assuming that you can define a probability function on this variable, you can calculate the expected value of a trade.

But are these really the only two relevant results when it comes down to the Brexit-debate? No, it appears. There could be an explosion in a chemical factory in Germany that coincides with the Brexit or Bremain, but that significantly alters the course of the DAX-index. Maybe a politician will be murdered in case of a Bremain, and the DAX-index will collapse, even though the UK stays in the EU. There is an infinite list of possible events, not all of which can even be conceived: the black swan events, or the unknown unknowns. Since these results are by definition unknown, but nevertheless possible to happen and relevant for the DAX-index, your calculation will necessarily lack all relevant information, thereby giving an incomplete sample space. Such a thing can never be the case in roulette.

Problem 2: pay-offs
Furthermore, it is unclear what the DAX-index will do in case of either a Brexit or Bremain.This can be seen from the many different predictions made by various analysts. No-one knows exactly what the result of a Brexit or Bremain will be. Hence it is impossible to put a value on each of these results. So the second component of expected value, the pay-offs, is doubt-worthy too. This too can never be the case in roulette.

Problem 3: probability
But there is another, at least as stressing, issue. For expected value to be calculated, every event in the sample space must be assigned a probability.  While this is relatively non-controversial in the case of roulette (probability of either 1,2,…, 38 is 1/38), how do you come to know the probability of an event such as a Brexit, an interest rate hike, or any event that has never happened before?

It seems impossible to apply the so-called frequentist interpretation of probability, in which you conduct experiments and measure how often an event occurs relative to the total number of experiments. First of all because it is impossible to conduct experiments of this sort in the market. And second of all: even if you somehow manage to calculate how often an event occurred in the past and divide that by the total number of experiments done, you will necessarily get a 0% probability for events such as a Brexit, which have never occurred before. This seems absurd.

Using a subjectivist interpretation of probability will not help you much further. You can of course assign a probability to Brexit or Bremain by judging the available evidence, but the question is: how should you judge the available evidence given that you have no information about what happened in the past given the same set of available evidence, for this set of available evidence is surely to differ from any set in the past (Bayesian probability). One thing is for sure: certainly no Brexit has ever happened, under no set of available evidence, so again, the probability of a Brexit should be 0% (in light of any set of available evidence, in case you apply the rules of Bayesian statistics rightfully), which seems absurd.

This shows why probability theory and trading are no happy marriage, and why trading is not a game of chance like poker, rolling a dice or roulette.

# How Apple Can Cause Any Stock to Go Down

On April 28th of this year, Carl Icahn (a billionaire hedge fund manager) announced that he sold his entire stake in Apple. He said, among other things, that he was worried about China and cautious on the U.S. stock market.  No big deal you would say. Sure: it might be bad for investors’ confidence in Apple, knowing that a man with a history of successfully anticipating the stock market shows not to have confidence in their company. But it would certainly not affect an apparently totally unrelated European company, such a BMW, right?

Wrong. Via a complex set of relations, it does. Stocks worldwide are closely interconnected; even though the rationale behind these relations might at best be hard to find. Let’s for example track the chain of events that caused BMW to decline on the 29th of April.

Icahn announced him selling his Apple shares on the 28th of April, after European trading hours (i.e., when the European markets were closed). Following his statement, Apple’s stock fell from \$97.5 to \$94.5 – around 3%. Apple, being the biggest company worldwide and the largest component of the S&P 500 index, to a large extent determines the S&P 500 index. So if Apple goes down, the S&P 500 goes down. Hence, after the announcement, the S&P 500 index declined from 2095 to 2075.

Now we arrive in Europe. European algorithms detect the decline in the S&P 500, and – being programmed to arbitrage around a positive correlation between the S&P 500 and the German DAX index – sell the DAX index future (possibly while going long the S&P 500, so called ‘statistical arbitrage‘). The result of the selling? The DAX index future plunges from 10321 to 10038, or +- 2.7%, an extraordinary big intra-day decline for the DAX.

Other algorithms, detecting the DAX index future to fall, and arbitraging around a relatively stable premium between the future and the index, sell-off the funds making up the DAX index, thereby causing the DAX index (which is just a collection of stocks of big German companies) to plunge accordingly. Since BMW is part of the DAX index, algorithms sell the BMW share. This causes BMW to decline from 83.94 to 80.5, more than 4%, a significant decline.

Hence Apple causes BMW to decline. See figure 1 for a graphical depiction of this chain of events.

Figure 1: how Apple going down causes BMW to go down

You might think this chain of events is too far-fetched. That it is some kind of conspiracy made up in a desperate attempt to explain what is in fact impossible to explain. But I doubt it. On the 28th and 29th of April, nothing exceptional occurred (besides the Apple event), or at least nothing that would justify a 2.7% fall in the DAX index. Usually, given a decline of this sort, there must at least be one relatively big event to which the decline can be ascribed. Hence in this case we have no better explanation for the plunge than Apple’s stock falling. Furthermore, assuming that algorithms do the tasks I described above, which are strategies known to be followed by algorithms, this chain of events is nothing but an utterly logical consequence.

Algorithms of course don’t care about Icahn’s opinion of the Apple stock, or the stock market in general. But what they do care about is relations between financial products, since this is where they make their profits. And it is by profiting from any significant deviation from historical relations between financial products that they keep intact such relations, and form the intricate web that is the stock market.

The machines have taken control

A lot has been written about high-frequency trading (HFT), especially since the 2010 flash crash, for which HFT is at least partially held responsible. HFT even caught Hilary Clinton’s eye, proposing a plan to tax cancelled trades, thereby hindering HFT’s business.

In my experience as a stock trader, who watches order books all day and follows the workings of HFT’s closely, you see many signs of the subtle workings of HFT’s. We, human traders, often complain about these ‘machines’; especially the more senior traders, who grew up in a time in which trading was something that happened between humans, sometimes get frustrated by the seemingly random price movements caused by the machines.

I want to give you some clues about how HFT has changed the job of a human trader. This might also shed some light on why today there are fewer and fewer human traders. Today, if you buy quite a large sum of stocks, let’s say 50.000 stocks ArcelorMittal or 10.000 stocks Shell, 9 in 10 times you will experience a sudden drop in the stock’s price (+- 1%). That’s right:  a drop, not an increase. This didn’t use to happen a couple of years ago, but from a HFT perspective, the price drop is easily explained.

For suppose you aggressively buy 50.000 stocks, meaning that you buy 50.000 stocks on offer. This implies that a certain HFT is short 50.000 stocks. Assuming the HFT wants to have a net position of zero, this means that it has to buy back 50.000 shares. But it doesn’t want to make a loss: it wants to buy back the shares at a lower price than they were sold for. Being a market maker, hence controlling the order book and therefore the share’s price, the HFT removes successive levels of best bid. Now it waits for other HFT’s to fill up the order book, until it detects an offer of 50.000 stocks at a price lower than the price the HFT sold the stocks for. Now the HFT buys back the shares, hence making a profit. For the human trader, who is on the other side of the trade, this means that he starts his trade with a loss.

Another way in which trading has changed, is in the extremity of price movements. A couple of years ago, human traders would prevent certain extreme price movements from happening – by buying when they deemed a stock oversold, and selling when it was overbought. Machines don’t follow this logic. They go with the flow, and if the flow is selling, they are selling too. Hence you see price movements that either go up or down continuously, without any correction. Furthermore, price movements get accelerated due to the high speed of HFT. This explains the increased volatility; another side effect of HFT.

Adding up all such changes, you can imagine why the traditional way of trading has become increasingly difficult for humans, possibly explaining why relatively fewer and fewer humans trade.

# Why 30 Years of History Shows the US Stock Market is Going Down

I hate preachers of doom and destruction. I think most of them just want some attention, and instilling fear into people’s minds works better in doing so than painting a rosy future. But something quite concerning recently caught my attention, and – even though you might have already noticed it – I want to point it out.

Governments worldwide decreased interest rates in response to the 2007-2008 financial crisis. The idea was that by decreasing the interest rate, it becomes cheaper for banks (hence people) to borrow, hence increasing the amount of money available to spend, thereby increasing the spending power of the economy.

As a matter of fact, the USA has had such a ‘stimulating’ economic policy for over 30 years to date. If you look at the United States Fed Funds rate, the main determinant of interest rates in the USA, you can clearly detect a down-trend since 1980:

This policy has shown to be effective, at least in recent years. The unemployment rate in the USA has decreased from 10% in 2010 to around 5% in 2016.   This might be a case of post hoc ergo procter hoc, but it seems hard to believe that the US stimulating policy has had zero positive impact on the economy. Furthermore, if you take the S&P 500 index to be the benchmark of the US stock market, you see that it has tripled since the bottom of the financial crisis in 2009; from 700 to 2100. In fact: the S&P 500 index has been in a clear up-trend over the course of the last 30 years:

You see the relationship? What we see here is a clear negative correlation between the Fed Funds rate and the S&P 500 index. The first question you should of course ask yourself when talking about correlations is: are the increasing stock prices a result of the decreasing interest rate, or is the deceasing interest rate a result of the increasing stock prices? The last relation seems to make no sense, for if anything, a higher stock market might be a symptom of a market overheating, hence encouraging restrictive instead of stimulating economic policy. So the relation seems to hold the other way: a lower Fed Funds rate causes the market to increase, which from a perspective of common sense, seems to make sense: lower interest rates means more money to spend, means more money to spend on stocks, means higher stock prices.

But the question that nowadays is very relevant is: what will happen to the stock market when the US government decreases its stimulatory policy? That is: what if the down-trend in the Fed funds rate stops? Currently the Fed has an overnight interest rate between 0.25%-0.50%, which is already higher than the 0.00% it has had for over 6 years. Now it is considering to increase it.  It seems fair to say that we can not go lower than 0.00% (although this has been done in Europe, but following up on this policy will lead to all sorts problem for the banking sector, not to mention a slippery slope). Hence the Fed funds rate can only go up. Given the negative correlation with the S&P 500 index, which is based on 30 years of economic data, there seems only one way for the US market to go, and it is not up.

# Why Economic Growth is More Important than Gender Equality

Figure 1: Taking care of moral issues enhances the economy

I think most of would agree that issues such as gender equality, education and malnutrition are important matters. Not only morally, in the sense that anyone of us should have the right to be treated equally, to receive education or to have proper feeding, but also because of their economic consequences. Studies have shown that gender inequality, lack of education and malnutrition affect the economy of a country negatively (see Figure 1). But fewer studies, at least none I could find, look at the relation the other way: what are the effects of economic development on gender inequality, education and malnutrition? Or more broadly: what are the effects of economic development on moral issues, instead of the other way around?

Let’s take gender equality, for example. I think it is reasonable to assume that when a country develops economically, the role of women in society will improve – in the sense that they are treated more equally to men. For suppose people have more disposable income, as a result of economic development. Then this money might allow families a sense of freedom that partially breaks down the traditional role division between the working man and housewife. The money might for example allow women to pursue their interests, whether this be education, painting or something else, thereby enabling them to develop in a manner similar to men.

Furthermore, economic development might reduce the number of children per family, thereby putting less pressure on either the man or woman to stay at home to care for the children. This enables both parties to participate more equally in, for example, the workplace.

Economic development might also increase the level of education in a society. In case there is a system of private schooling in place, this is obvious. For if people have more income to spend, they can spend more on the education of their children, thereby increasing the level of education received in society. Also, more income means more taxes. In case a country has public schooling, more taxes allows for a more elaborate educational system, thereby enhancing education. Also, when families have more income, their children might not have to do labour to increase the family’s income. This provides them with the time required for education.

Malnutrition; another problem. It is obvious how malnutrition might be bad for a country’s economy. But it is just as obvious how economic development might reduce malnutrition. After all: if people have more income to spend, they can spend more money on food, thereby decreasing the level of malnutrition. Furthermore, if an economy develops, the supply of food might increase, since there might be more economic demand for food. The food might also be cheaper due to increased mass production, hence increasing the availability of food for the common people.

I am sure there are many other moral issues I didn’t deal with in this article (think about poverty, or child labour), but that affect both the economic development of a country and are affected by it. But what each of these matters appear to have in common is that they can be improved by improving the economic development of a society. Hence, in case you want to improve the well-being of a society, as many charities might want to do, you might be better of developing a society economically than to try and solve each moral issue one by one (see Figure 2). Because why choose the hard way when there might be a much simpler solution?

Figure 2: Economic development might (partially) solve moral issues

What do you think?

# Why Voting on Trump Now is Especially Bad

Today another terrorist attack hit a major city in Europe. After Paris, today Brussels was hit. Naturally people are scared, and want to feel safe. Hence it seems attractive to support a political party which implements policies that at first sight seem to increase one’s safety. Think about people such as Geert Wilders in the Netherlands, or Donald Trump in the USA.

Geert Wilders for example wants to close its country’s borders, and stop emigration from Muslim countries. Wilders’ policies are part of a much broader agenda; an agenda that is characterized by a core of anti-Islam. He condemns pretty much anything that has to do with the Islamic ideology. Donald Trump might be even worse: he wants to ban any Muslim from emigrating to the USA.

Although such measures might appear to improve the safety of the average citizen, one can legitimately doubt whether such policies will make our lives safer, instead of less safe.

For suppose more people vote on Wilders or Trump. Then Wilders/Trump will implement more anti-Muslim policies, which not only creates a more apparent difference between Muslims and not-Muslims, but might also make Muslims feel more oppressed in their own country, which in turn could cause resistance. They might start thinking: ‘If you guys won’t accept us and our ideas, then we might have to force you to respect us another way’. Or: ‘Given that you don’t respect us, we see little reason to respect you’. This feeling might not directly cause terrorism, but it could lead to an increased sense of suppression within the country’s Muslim community, which might stimulate the occurrence of a breeding ground for (violent) resistance.

But even without political anti-Muslim measures being implemented, increased support for anti-Muslim politicians might in itself make Muslims feel like they are not accepted, not even in their own country, thereby creating resistance. After all: how would you feel to live in a country (such as the Netherlands) in which 1 in every 3 people on the street votes for a party whose main message it is to suppress your kind of people. I can imagine that you won’t feel much compassion for your fellow citizens.

Especially in this time, when the tensions between Muslims and not-Muslims seems relatively large, voting for people who increase this tension even further might be particularly problematic.

What do you think?

# Why Do So Many People Want To Be in a Relationship?

Why Do People Want To Be in Relationships?

Sharing your life with someone else. Always being together: if not in person, then at least in mind. Sharing in the other person’s pain (but also in their happiness of course). Always having an obligation to someone. Not being fully free.

These are merely some of the consequences of being in a relationship. I wonder: what draws so many people into a relationship? Why do so many people appear to have the urge to always have that other special person in their lives?

Is it is to share your feelings and ideas with someone who truly cares about you? Who doesn’t judge you, who wishes the best for you and tries to help you? That might be true, but it seems like you don’t have to be in a relationship to have such experiences. You might just as well talk to friends – who by definition care about you, want the best for you and try to help you – and achieve pretty much the same results.

Is it for sex then? To have sexual intercourse with someone regularly without having to go through the seduction process over and over again? Maybe, but again: you don’t need to be in a relationship for that. You can have sex with pretty much anyone who wants to have sex with you; also with the same person, so that you don’t have to go through the seduction process over and over again. ‘But’, someone might object, ‘sex with someone you’re not in a relationship with is less intimate in some way, than sex with your girlfriend/boyfriend.’ But is it really? Because why would the fact that you are in relationship with someone, which appears to be nothing but a social construct, add to the intimacy of sex? It might be that being in love with each other does, but then again: you don’t need to be in a relationship to have that experience.

So why then, if not for companionship or sex?

Maybe it is to boost our own perception of ourselves. Maybe it is the idea that we mean so much to someone that that person is willing to give up a large part of their lives, time and bodies for us. And the prettier, smarter, kinder that other person is, the more special it is that that person chooses you. And it might just be that feeling of possession that we, insecure humans, crave for, and why we value being in a relationship with someone.

Or maybe it is because it is just the normal thing to do, according to the unwritten rules of society. But one could question whether this is ever a good reason to do anything.

The best reason I can think of is when you plan on having, or actually have, children with someone. For in case you have children with someone, it might only be fair towards that person to devote all your resources to him/her and your children – if only because it might be best for your children, which from an evolutionary perspective seems an important consideration in one’s actions. However, I doubt many teenagers, or people in their twenties, consciously decide to get into a relationship with someone for this reason.

None of this is of course a problem; not if both parties agree to the relationship. But it might shed light on the not-so-conscious reasons that drive people into a relationship.

# How Hedge Funds (Ab)use Human Psychology to Increase Profits

I am a professional trader. That means that I buy and sell stocks for a living. And since I am a so-called ‘day trader’, the buying and selling have to happen within one day. This means that I am extremely short term focused: I try to anticipate where a stock will be at within five minutes or an hour from now, instead of five years.

As a trader, you obviously want to buy a stock as cheaply as possible, and to sell it for as much as possible. But if you think that studying financial documents and finding out what companies appear undervalued will help you in trading, you are only very partially right. Much more important, I dare to say, is understanding and using human psychology. And when you zoom in from years to days to minutes to seconds, the more important human psychology becomes.

Let me give you an example of how big hedge funds (which I certainly do not belong to) seem to use human psychology to increase their profits. I say ‘seem’, because I cannot prove this. If only because I don’t know who is buying or selling at any moment in time (but I can see what hedge funds own what stocks, and when they bought/sold). But given my everyday experience with movements in price, and applying common sense, I am reasonably certain.

Suppose there is a stock trading a little above \$3. Last time it went to \$3, it recovered to \$10 within three years, and to \$55 within six. Last year the stock was priced at \$10, and ten years ago it was priced at \$55. Therefore it looks cheap (irrespective of the fundamentals of the company). Hedge funds assume that many people are willing to buy at this price. Assume that many people do. Now hedge funds, with practically unlimited financial resources, come in. They create a level of resistance in the price. They do so by offering a practically infinite amount of stocks at best offer (being the lowest price at which people are willing to sell the stock: \$3,21 in Table 1). By doing this, they create an upper limit in the price, since before the price can increase, all the stocks at best offer have to be bought, which is practically impossible given that the hedge funds have so much selling power compared to the rest.

Table 1: order book of stock

Now, since the price cannot go up, it will go down at a certain point. Be it because of algorithms trying to maintain certain correlations with indices, or because the hedge funds actively sell stocks at successive levels of best bid (the highest price at which people are willing to buy the stock: 3,19, 3,18 etc. in Table 1). Through doing this, the price will decrease to let’s say \$3: a ‘psychological level’ in the stock. Many of the people who bought the stock thought it would never go under \$3. Now people get anxious. Then the hedge funds give the final blow, and push through the \$3. Now people start to panic – “maybe the stock will go to \$2!”. They start selling the stock ‘at market’, meaning regardless of the price.

Figure 1: Arcelor Mittal stock

Now the hedge funds can buy the stock for less than \$3 from the people who are selling at market, either to go ‘long’ (to have stocks), or to cover their shorts. See Figure 1 for a graphical display of this chain of events. Combine this with the fact that high frequency traders (acting on behalf of hedge funds) can change the order book in less than the blink of an eye (thereby changing the quantities on bid and offer), they can very quickly change the price of a stock. The price of a stock is after all nothing more than the price paid for the stock in the last transaction: so if you very quickly pull away successive levels of best bid, the next person selling at market will do so at a (much) lower price, meaning that the hedge funds buy at a lower price than the general public.

Now the hedge funds have bought their stocks, they pull back, and let the market do the rest.

# Why ISIS Is Ignorant, But Not Wrong

It is clear that we in the West do not agree with ISIS. We think that what they think is wrong, and more importantly: we think that what they do is wrong. They decapitate Western journalists, promote violence against people who don’t agree with their religious beliefs, organize terrorist attacks, and even destroy Iraq’s cultural heritage – statues that were over 5000 years old. How can they do this? Why do they do this? Is it due to their set of (religious) beliefs? And if so, can we then judge them for doing what they think is the right thing to do?

First a rather obvious observation: people from different cultures or societies have different ideas about what is right or wrong. This view is called descriptive moral relativism, and it’s a moderate, empirical claim, that is corroborated by reality. Look only at the people of ISIS, who think that what they do is spreading the true message of Allah, and who think that anyone who disobeys this message is wrong. They believe that they should stick to a very strict interpretation of the Islam, and that people who don’t do this, should be done away with. If not by words, then through force. We in the West clearly find their ideas about what is right and wrong absurd. Hence ISIS and us, clearly, disagree about what we find right and wrong.

We could go one step further than this claim, and say that ISIS and us don’t merely have different ideas about what is right and wrong, but that neither of us is more right or wrong than the other in having these ideas. There are many cultures and equally many ideas about what is right and wrong, but there simply is no absolute, culture independent interpretation of right and wrong.

And there is something to say for this so called meta moral relativism. After all, acts can hardly be judged wrong in any absolute sense; that is, without regarding the relevant context. Killing a person might seem wrong, but if you can save one hundred people by doing so, it might actually be a sin if you wouldn’t do it. So the context appears to matter for deciding whether an action is right or wrong. So it could in principle be possible that a culture’s or society’s set of beliefs, taken as the relevant context, genuinely determines whether an action is good or bad. Applied to the ISIS case: it is not only that they have the idea that destroying Iraq’s cultural heritage is right, but given their set of beliefs, it truly is the right thing to do. An equivalent way to say this is that what is right or wrong is determined by nothing but the idea of what is right and wrong. Hence, given that ISIS thinks that what they are doing is right, which I assume they do, their deeds are truly right – for them at least.

Let’s for the sake of argument assume that this meta moral relativism is a correct description of reality: that there truly is a plurality of interpretations of right and wrong floating around, none better or worse than the others. Then, applied to the ISIS case, we have to face a difficult question. Because if ISIS truly thinks to do what is right, how then can we judge them? Okay: we might have a different interpretation of what is right than they do, but we have just established that having a different interpretation doesn’t make their views wrong regardless of the context. Our conception of morality is just different from ISIS’s: different, but not superior.

And, playing the devil’s advocate, don’t we (the West) do exactly the same? It might not be the message of Allah that we try to spread throughout the world, but the message of liberalism and freedom. And we too are willing to go to great lengths to spread this message. History shows that countless of people have been killed because their actions didn’t cohere with our ‘right’ notions of freedom and liberalism – the Nazi’s being just one example.

So it appears that we cannot declare ISIS’s ideas and actions to be more wrong than ours – not while strictly assuming meta moral relativism. That’s a pity.

But there might be a way out. A way in which we can judge ISIS’s beliefs and actions to be wrong, without falling into the pitfalls of meta moral relativism. Because even though we might not be able to say that ISIS’s ideas and actions are absolutely wrong, we can say that ISIS is ignorant. We can say that they have not tried to actively refute their basic set of principles – the principles, derived from the Islam, that make their actions right. For if they would have done so, which I am quite sure they have not (because Allah’s words seem the most basic principles guiding their thinking, and even doubting these principles is wrong), it seems hard to imagine that they would have still accepted such principles.

So we can say that ISIS is ignorant, which in itself could be found immoral. But let’s not go there…

What do you think?

# Why It Is Possible to Make Above Average Returns – Even in Efficient Markets

There is a well-known hypothesis in financial economics, called the Efficient Market Hypothesis (EMH), that spawns a lot of debate. The EMH states that financial markets are ‘informationally efficient’. In other words: a financial asset’s market price always incorporates and reflects all available relevant information. Hence no investor can consistently use such information to find stocks that earn him above average returns. After all: such information is already reflected in the asset’s price; so if there is a lot of ‘positive’ information about the company, the stock’s market price will have increased, and if there’s a lot of ‘negative’ information, the price will have decreased.

I want to make an argument why, even if the EMH holds, it might still be possible to consistently earn above average returns on investments. The argument is basically very simple. Let’s first recall the EMH. We know that an efficient market is a market in which the price of a financial asset (let’s say a stock) always incorporates and reflects all available information. Hence, you cannot benefit from the set of available information in such a way that you can consistently earn above average returns on investing in the asset – or any asset for that matter. But does it follow from this that you cannot consistently achieve above average returns? I don’t think so.

Because what if you are consistently better than other investors in anticipating future information? Then, even though the stock’s market price reflects all available information, you can utilize this anticipated future information to decide whether to buy or sell a stock. And if you can anticipate future information (which is information not yet incorporated and reflected in the stock’s price) better than the average investor, then you can earn above average returns, time after time.

This all sounds pretty abstract. So let’s look an example. Suppose there is a stock of a company that produces wind turbines – call it ‘stock A’. Furthermore, let’s suppose that at this point in time investors are on average not confident about wind energy’s potential. They might think that the cost of producing wind energy is too high, its profits depend solely on the current regulation, or that it will still take a long time before our fossil fuels are depleted, making the switch to wind energy not urgent yet. Given these considerations the stock trades at a price of – let’s say – 10. Let’s assume that this price indeed incorporates and reflects all available information – such as information contained in annual reports, expert analyses etc. Hence it seems reasonable to say that you cannot consistently earn above average returns on this stock by utilizing only this pool of existing information.

But what if you believe that, given the ever increasing energy consumption and ever decreasing level of fossil fuels, society has in the middle-long term no choice but to turn to alternative forms of energy – forms such as wind energy? If you think this is true, then you can anticipate that any future information about the wind-turbine producer will be positive – at least more positive than today’s information is. You can anticipate that the future information will show an increase in the firm’s revenues, or – for example, in case the firm is close to bankruptcy but you know that its managers don’t profit from a bankruptcy – a decrease in costs. Given that the market is efficient, you know that at the time this information will become public, the market price of the stock will increase to reflect this information, to a price of let’s say 20. If you can anticipate such future information consistently, then you can anticipate the future stock price consistently, allowing you to consistently earn above average returns – despite the perfectly efficient market.

An equivalent way to look at this matter is to say that you take into account more information than the average investor in calculating the stock’s fair value. Let’s say that you are doing a net present value calculation, and you have estimated the firm’s future cash flows. In case of stock A, investors used estimated cash flows that lead them to a fair value of 10. However, given your anticipation of future information, you estimate these cash flows to be higher – leading you to a higher valuation of the stock. Again: if you can consistently anticipate future information better than the average investor, you can consistently earn above average returns – even in an efficient market.

# Why You Should Always Do What You’re Afraid To Do

Ralph Waldo Emerson said: ‘Always do what you are afraid to do.’ And this rule seems a reasonably good guide for self-improvement. Because it turns out that people are often afraid to do the things they are least familiar with. Whether is approaching a girl in a club, giving a speech to 50 people, or setting up a business: things make us feel anxious because we have little experience doing it. In such cases the anxiety often pushes you away from doing the thing, hence still leaving you clueless about what you will experience, or even further increasing your anxiety.

But there is something odd here: because the things that you are least familiar with provide you with the biggest opportunities to learn. After all: if you are not familiar with something, it means that you have little knowledge of it. It means that you are still at the start of the learning curve; that the ‘marginal utility per unit of experience’ is very high. Therefore, being afraid of something might be a damn good indicator that there is a lot of potential for you to learn about the thing. Hence it might be wise to always do what you are afraid to do.

This reasoning seems cogent, doesn’t it? But there is one problem with Emerson’s rule…it is not always true. There are cases in which fear should actually push you away from doing something – not pull you into doing something. Think about the fear of jumping of a building, or the fear of approaching a tiger. Given that you want to improve yourself, it seems unwise to jump of a building, or to be ripped to pieces by an angry tiger.

So the best we can do is to say that the rule is a heuristic: a guide in life, that points you – in most cases – to the areas in life where you can learn a lot. But how do you know in what cases you should act upon the rule, and in what cases you should realize that doing so might actually put you in danger? I think we have to distinguish between two kinds of fear here: socially conditioned fears and innate fears. The first are things such as being afraid to start a business or to make a move on a girl*: we have been told, or we have experienced at first hand, that such endeavours might cause emotional pain – even though they are not inherently dangerous. Innate fears, on the other hand, are things such as being afraid of tigers, which seems like a reasonable fear. Tigers are dangerous; despite your experiences with one. In other words: it seems that innate fears try to protect us from real threats, while socially conditioned fears don’t always do so.

Taking this into account, ‘Always do what you are afraid of’ is likely to make you learn a lot.

But what do you think?

*it might be true that socially conditioned fears are grounded in biology, hence being innate. If we take evolutionary psychology seriously, for example, it might be true that the fear to approach women is in fact innate. Hence there seems to be a continuum from innate to socially conditioned fears; not a categorical difference.