The first issue when seeking to examine the correlation between two variables is determining the optimal dataset to examine. This is highly contentious since it is quite likely that spurious correlations can appear in datasets that have been excessively manipulated either by cherry picking the date range or by eliminating outliers. For that reason, I will select the largest reasonable dataset and do nothing to it.
I think the earliest reasonable starting point is somewhere around 1950. Much before then, and one is looking at periods where the economy is so different to that of the current day, that it would be inappropriate to try to draw any conclusions. In addition, it is not that helpful to produce a model going further back and have to say, when asked about a prediction, that “this is what happens when Hitler invades Poland…”
Here is a plot showing US GDP since 1950
This immediately looks like some kind of power law growth with a kink for the global financial crisis. (We don’t really have enough data to look at COVID properly yet, but I expect it will produce another kink and not really disturb the trend line.)
This second plot is the S&P 500 index over the same timescale.
This also shows some sort of power law rise, though it is clearly much noisier than the GDP curve. This does not however obscure the direction of travel.
Here’s a brief aside about polynomials. This is skippable if you don’t care what curves I am going to fit to the above two lines. Polynomials are curves of the form y = ax^3 + bx^2 + cx + d. The order of the polynomial is how many of the a, b, c, d coefficients are non-zero. So a first order polynomial is just a straight line of the usual form y = mx +c. The reason this matters is that we do not want to overfit or underfit. If we underfit, we fail to capture information in the curve we are modelling. If we overfit, we get all the information in the curve, but we may add some features that are not really there. The best way to check for that is to see what happens if you extrapolate the curves beyond your training data. If you have overfitted, it will often be the case that your predictions go insane as soon as you are off-piste — i.e. outside the training dataset.
Here is an illustration of what under and overfitting might look like.
The blue circles are some arbitrary test data we want to fit. The other curves are the various orders of polynomial returned by a fitting package. As you can see, the first order polynomial — just a straight line as mentioned above –is totally inadequate and is a radical underfit of the data. The second order is not bad, but the third order is very good. I have run checks like this plus the original test of asking what happens off-piste. I found that third order was fine to use.
Fitting a third order polynomial to US GDP gives me the following plot.
I have slightly adjusted the data to make it fittable. The x-axis is now the number of days since 03-Jan-1950. I also zeroed out the US GDP for 1950 which I don’t think matters too much. You can see that the curve is a good fit to the data apart from a rogue rise at low day counts which again I don’t think matters because we aren’t going to try to predict GDP in 1950 — we already know it.
If you want to know the equation of that curve, it is :-5.265e-11 x + 4.351e-05 x – 0.2643 x + 414.1
If you think that the very small cubic coefficient means I don’t need third order, you are basically right but again I don’t think it matters as long as the curve extrapolates reasonably.
Performing similar manipulations on the S&P500 (recalibrating to days since the start of 1950 and setting the initial value to zero) gives me a different fitted curve, as below.
Note that in both cases, there are around 25000 days between the start of 1950 and today. (70 * 365 = 25,550).
Here, the equation of the fitted line is: 2.726e-10 x – 3.87e-06 x + 0.02366 x – 10.68
Again, the cubic coefficient is very small. The notable point about this curve is that it is very noisy. But it still follows a clear trend line.
Now we get to the dangerous part. We need to see if these curves behave once we extrapolate them. Let’s look at what they do if we double the day count to 50,000. (This is equivalent to making the date range double — so we are currently 70 years on from 1950; 70 further years added on takes us to 2090.)
There are two reasons this is dangerous. As I said, if the curves blow up, we have achieved nothing. The other issue is that you can’t extrapolate power laws forever. I will now discuss a brief example of that not working.
You will recall that in the early stages of COVID, people were plotting case counts and fitting exponentials to them. That looked like it was panning out to begin with. But the plot below shows what happens if you fit an exponential to the Florida case count as of yesterday.
It can be seen that the case count profile is in no way fitted by the exponential. So is it the case that the US economy can continue growing on an exponential basis indefinitely? Probably not. When will it stop doing so? No-one knows, but it might be beyond your investing lifetime. Also, bear in mind that it will have looked like it couldn’t continue growing exponentially at most points since 1950. We don’t know what technology or quantum computing or unimaginable developments are going to do.
So what happens if we extrapolate the curves we fitted? This is shown in the plot below.
This shows firstly and importantly that the curves continue to behave out to 50,000 days.
We can conclude that if the S&P500 and US GDP continue to develop as they have done, then by the year 2090, US GDP will have reached USD $90tn and the S&P 500 will have reached 26,000.
There are various conclusions that I have not argued for. I have said nothing about other countries. The above analysis would definitely not work for the FTSE-100 because that does not grow exponentially. It seems rather to exhibit a large saw tooth oscillation between 4000 and 7000 with a period of about a decade. That won’t correlate with anything. Similar points apply in Japan.
Secondly, I have not shown what happens if you try to fit curves to only more recent data. They are very noisy and that explains why a lot of analysis does not show any correlation.
Thirdly, this does not really backup Portnoy when he says “stocks always go up.” Partly that is the case because of the huge noise in the S&P 500 curve. Partly it is the case because you might have to wait a long time. Partly it is the case because the curve only shows that the S&P 500 always goes up. But the trend is your friend here if you wait long enough.
Lebanon; no GI; vineyards are at some distance from the winery for historical reasons (founder was unsure of the future borders of Lebanon and so the winery is in Beirut while the grapes are grown more than 60km away)
This has the disadvantage that the grapes must be transported a considerable distance under conditions of some heat; however, there are good supplies of inexpensive labour available and it is possible to harvest in the early morning
Against that, the location of the winery in a major city means there is good availability of skilled labour where it is required
Red grapes are grown in the Bekaa valley
White grapes are grown in the foothills of the Anti-Lebanon mountains and on the seaward side of Mount Lebanon
Cabernet Sauvignon, Carignan and Cinsault (red); Obaideh and Merwah (white)
Styles of wines and price point
Premium: the house has a very strong historical reputation built up since its foundation in the 1930s. The reds may be seen as competing with Bordeaux which means that they can be quite expensive when compared to the median bottle sold and yet relatively inexpensive when compared to classified growths. The house has been carefully expanding its range while aiming to maintain brand identity which would suffer from any decline in quality. The white and rosé production of the house is much less well-known than the flagship red blend, but wine critics have described this as an unfortunate situation. There is therefore an opportunity here.
Notable viticultural/vinification practices, climactic factors or location details that may be used in the marketing of wines.
Vinification practices: there are no specific vilification practices which are unique to the house but the marketing will nevertheless note that care is taken throughout as one would expect from a premium product. All wines are made “naturally” on a minimum interventionist basis. Grape growing achieved organic certification in 2006. The wines ferment in concrete with some time in French oak (nevers) and are released after a generous seven years of maturation.
Climatic factors: The vineyards are located at 34N which would normally be too warm for viniculture; the altitude of the vineyards is 1000m which offsets this. The marketing can note this as an unusual though not unique quality factor/differentiator.
Location: The house is not the sole wine producer in Lebanon, but it is clearly the most well-known and has by far the best reputation. This forms the underpinning of the marketing. Many consumers at high and moderate levels of expertise are interested in trying wines from new locations and new grapes. The reds are without doubt the highest quality wines made in Lebanon or indeed the middle east region while the fact that they are basically made from a Bordeaux blend means that they can combine quality and a new experience without being too radical a departure from established premium benchmarks. The whites benefit from the novel location details and are made from two grapes both of which are likely to be unfamiliar to even quite experienced consumers. The “brand story” of the wine is extremely strong, being unusual and interesting. For example, the cellars of the house were used as air raid shelters during the civil war in Lebanon between 1975 and 1990 and there was no interruption in wine making during hostilities. The general location has an extraordinary long history of winemaking which may potentially be traced back to the Phoenicians in ca. 4500 BCE.
Specific social, economic, political or legislative factors that would impede/assist the sale of wine
As a general remark, it should be noted that the wine will be primarily sold overseas. While Lebanon has been up until very recently a relatively wealthy country, it has experienced a sovereign debt default in 2020 for the first time in its history. It has also been a relatively liberal country given its location, but it should still be noted that Muslims make up more than 2/3 of its population and that group consumes less alcohol than other groups. Given these factors, the social, economic, political and legislative factors obtaining in the international arena are of more significance to the fortunes of the house.
No current discussion of social factors can omit the effects of COVID19. While there is no very stringent lockdown in place in Lebanon at present, this could occur at any moment if infection rates become elevated. Such a lockdown would present a significant threat if it took place around the harvest; while agricultural workers in general would be exempt, it is quite conceivably that harvesting of grapes for wine production would be deemed non-essential in the unique circumstances of Lebanon. Similarly, the house relies on transportation via sea from Beirut port. Loading ships is a labour intensive operation but also is highly computerised and containerised. The house is therefore relatively optimistic that there are reasonably chances of being able to maintain shipments. Failing that, it would be appropriate to develop financial buffers to weather any income interruptions; the increased average maturity of wine that would be available post-crisis would be valuable and can be used as a negotiating point in seeking interim credit facilities from banks.
Similarly, the international economic situation in all key markets is dominated by the COVID19 shutdown, which is predicted to cause GDP declines of 30% or more in Q22020 and which count potentially continue into Q3 and beyond. The position of wine as a product which is extremely important to many consumers but nevertheless not actually essential is a difficult one. There are no ways for the house to mitigate this; it can only be observed as above that the markets will return and the house will be ready with product when they return. Given the global nature of the crisis, there are no clear new markets to explore. However, since the crisis appears to be closest to resolution in China, and there is a burgeoning middle class there which is anxious to display its status and wealth, this could be an opportune moment to focus marketing efforts in China. This could further benefit from the 2012 prohibition on “lavish gifting” promulgated by Xi Jinping. That severely affected sales of super-premium wines such as premier cru classé Bordeaux; there could be an opportunity for the house to benefit given its niche as a premium wine in a similar style which is nevertheless perhaps more “under the radar” as far as official perceptions of excessive luxury are concerned. Such an effort would need to be conducted with a high level of discretion and local expertise. Away from COVID19, the international economy has been under strain in any case for some time. The aftermath of the global financial crisis had in some ways not ceased: interest rates were historically very low prior to the onset of the virus crisis and the US expansion was becoming very long. Economic conditions could therefore have been expected to turn negative in the next couple of years in any case. The house will rely on its strong reputation built up since 1930 to see it though this crisis and note that there could be further opportunities later since some producers will not survive this downturn.
Given the many international markets in which the house sells wine, there are not really any specific factors to note. However, Lebanese politics is a source of major instability and this could easily give rise to problems for the house. The political structure is unique — some might say uniquely unstable — with a sectarian basis for political appointments. There are three major religious groups in Lebanon (Shia, Sunni and Christian) and the top three political positions are divided accordingly. However, population numbers have changed significantly since the epoch when this arrangement was made. Young people who are highly educated had been protesting the poor economic performance of Lebanon, the concomitant unemployment and the widespread corruption. The recent debt default is likely to result in what is known as a “doom loop” between the sovereign and local banks. This places the house in an exposed position in terms of being a highly visible generator of cashflow which is not in a position to relocate. Any threat to the stability of the local banking sector can be generally mitigated by placing funds overseas, but this presents problems in funding the ongoing operations of the house. All of these factors could present the house with difficulties sever enough to prevent or impede production or sale of wine.
Lebanon has historically had good relations with most countries and has accordingly not suffered a great deal from trade embargoes or tariffs. There appear to be fair prospects of this continuing. There are slightly strained relations with Saudi Arabia but this country is not a customer for the house in any case. A resolution of the conflict in Syria appears to be in prospect and this would eliminate a major local source of instability.
There have been no local legislative threats, but in the context described above, it is clear that the government is desperate for funds. Its very survival was threatened by an ill-judged attempt to place a tax on WhatsApp messaging; the house could present a much easier target for taxation and other informal methods by which officials seek funding.
The house has historically sold a great deal of wine into France, partly because of the long shared history between the two nations. This has somewhat been impeded by the advent of the Lot Evin, which in 1991 greatly reduced the allowed advertising of alcohol. Nevertheless, the house has a strong enough reputation which continues to spread by word of mouth and expert opinion and so has suffered less than it might have done as a result of this factor.
Restrictions on social media are less in evidence currently so this represents an important opportunity to address new consumers. It would be valuable to explore engaging an appropriate celebrity/online influencer. Such an individual must fit with the high quality brand image and add brand awareness in a way which reaches likely new customers. These will need to be relatively affluent groups so some research on where high-earning Millennials are allocating their social media attention will be useful.
Costs associated with getting wine to the specific market: packaging, transportation, importation, sales and marketing
In general, costs within Lebanon are relatively modest since inexpensive labour is widely available.
Packaging: costs are relatively high since the house is a premium brand. Sales actually generated in Lebanon at the cellar door are important and require premium packaging. This consists of branded padded boxes and other branded accoutrements. These high costs are more than offset by the sales revenue however, since the premium nature of the house allows it to command high prices especially for older vintages.
Transportation: the winery is actually located adjacent to the major seaport of Beirut and so wine can be despatched there by road with no difficulty or expense. The house is fortunate in that its location in the eastern Mediterranean allows the easy transport by ship to many significant markets such as France, Italy and the UK. The US is more of a challenge, but again since the house is producing premium high priced product, air freight is an option.
The major issue is that the 60km from the vineyard to the winery is time-consuming given the quality of local infrastructure, but this is a fact of life rather than an addressable cost issue.
Importation: costs are in-line with market conditions generally. It must be observed that the climate globally has moved in a protectionist direction, partly as a result of the advent of the Trump admininstration and the subsequent US-China trade war. The election due in Nov-20 may ease this situation if the incumbent is not reelected. Brexit continues to be an event with extremely unclear outcomes; however the signature of a continuity trade deal between Lebanon and the UK in Sep-19 offers some reassurance that no new tariffs will be imposed in what is a major market for the house.
Sales: costs are in-line with market conditions generally. The cellar door operation is relatively expensive in that there are no charges currently made and free samples of vintages going back to 1974 are made available. However, in a group of 12-15 attendees, on average 3-5 will make purchases. Since these can be in the range of $1,000 to $2,000 — bearing in mind that most attendees will have travelled from Europe to attend the cellar door — this activity is highly viable economically.
Marketing: costs have been historically relatively modest because the house has been able to rely on its reputation. However, given the extremely challenging environment described above, this is likely to change. The engagement of a celebrity/influencer will be extremely expensive because of the requirements of the role. The house continues to incur expenditure on items such as branded corkscrews but it is unclear how rewarding this is.
Is selling wine in the assigned market a valuable business proposition?
Overall, despite the extreme challenges presented by the current environment, there are good prospects that the house will be in a position to continue to thrive. It is even conceivable that the difficulties of the situation will be offset by some positive factors. These include the possibility that houses in lockdown will consume more wine. The affordability will increase because restaurants are closed. This means that consumers will be buying the wine with a typical retail mark-up (ca. 20%) rather than a typical HoReCa mark-up (ca. 66%). It can also be expected that the end of lockdown will be greeted with enthusiasm by customers; wine can be expected to play a major part in the celebrations that will doubtless follow. The house can consider now how it can position itself to take advantage of this factor alongside champagne producers, who can be expected to take the lion’s share of such post-crisis celebratory revenues.
Plan Continuation Bias is a major factor driving investor losses in stock and other financial markets. For example, many investors tend to hold on to losers for too long when they should cut their losses. In this article, I will outline how this bias permeates our psychology by looking at how it works in air crashes, and then go on to examine its effects in financial markets. Investors will learn how to address this bias and improve trading performance.
Plan Continuation Bias, simply put, is the tendency we all have to continue on the path we have already chosen or fallen into without rigorously checking whether that is still the best idea or even advisable at all. Operating with this bias, as with the other 180+ biases that are an unavoidable feature of our psychology, is generally a good idea. We simply don’t have the time to constantly re-analyse our decisions.
Berman and Dismukes wrote a NASA report on this problem, which they describe in a brief article. They define Plan Continuation Bias as follows:
a deep-rooted tendency of individuals to continue their original plan of action even when changing circumstances require a new plan
Berman and Dismukes “Pressing the Approach” Aviation Safety World, December 2006, pp. 28–33
The authors describe two air crashes which were in their view caused by the operation of Plan Continuation Bias. Flight 1420 into Little Rock, Arkansas crashed in June 1999 because the pilots ignored alarms and persisted with an approach in difficult weather conditions. Similarly, Flight 1455 crashed in March 2000 in Burbank, California because the pilots continued with an approach even though they knew that they were flying at 182 knots which they knew was 40 knots above the target touchdown speed.
It is very easy for us to sit here on the ground and do armchair flying. We would not have made these errors we say to ourselves, wrongly. If we saw that we were flying too fast or that there were multiple alarms sounding, we would abort the landing and go around. This is not difficult to do. This quick and wrong simulation of the pilots misses out many germane factors. The pilots are under some pressure to land planes quickly and efficiently for cost reasons. There are no guarantees that going around will improve weather conditions. But ultimately, the major factor in these crashes in human cognitive bias.
Plan Continuation Bias has significant effects on the psychology of all of us. As the authors observe,
Our analysis suggests that almost all experienced pilots operating in the same environment in which the accident crews were operating, and knowing only what the accident crews knew at each moment of the flight, would be vulnerable to making similar decisions and errors
Berman and Dismukes “Pressing the Approach” Aviation Safety World, December 2006, pp. 28–33
Plan Continuation Bias is just as relevant a factor in making decisions in financial markets. We can be just as liable as the pilots described above to sticking to the plan. We bought a stock, it was a good idea at the time, and we continue to hold it even though the original reasons for it being a buy have dissipated or not transpired.
In trading, while no one is going to be killed, it is still an environment in which decisions need to be made on an inadequate data set and sometimes under time pressure. It is also going to be a highly charged situation emotionally. The inadequate data set could result from factors such as the impossibility of predicting the future or the sheer scale of the operations of a listed company. Time pressure is particularly prevalent in day trading, but even more long-term investors are susceptible to effects such as feeling that “money is burning a hole in their pocket” and they need to put a trade on right now. The emotional charge comes from losing money. We are all highly averse to losses — in fact, we seem to be 2.5x more averse to losing money than we favour gaining the same amount. It hurts to lose. It challenges our self-perception.
These observations lead to immediate suggestions as to how one can prevent Plan Continuation Bias from impairing one’s trading psychology.
Try to minimise the effects of an inadequate data set by either doing more research or not trading unless you are certain or can set downside limits. Don’t take trades where it looks like you need to know everything about a company or where you think other market participants can easily know more than you. Don’t trade things you don’t understand like Bitcoin.
Don’t do anything under time pressure. You will need to get used to FOMO because “just getting one more trade on” will kill you quite quickly. It’s fine to miss things. It is much more important to get a small number of decisions right than to try to catch every opportunity
Don’t trade when feeling strong emotions and try to trade emotionlessly. This is hard to do. It is particularly hard to learn this from practice/dummy accounts. It simply doesn’t hurt very much to lose play money. You should still start here, but be prepared for real life to be much harder. Get more Zen about it. It doesn’t matter if a trade loses as long as you are up over the year.
Why women are better traders and investors than men — a psychological explanation
Warwick University Business School (“WUBS”) have conducted a fascinating study on the investment performance of men and women. They show that women perform significantly better with a good sample size and temporal range. They make some interesting remarks on why this might be. I think I can add some extra psychological depth to this — so we can see that female traders appear to have some quite deep natural advantages and they should feel encouraged about managing their own investments.
What WUBS did was collaborate with the share dealing service offered by Barclays Bank. They looked at 2800 investors over three years. There are various ways of measuring stock market performance, but one of the most common is to compare the performance of a portfolio with a relevant stock market index. (I explain what a stock market index is here: What Is A #Bear #Market?)
It is quite hard to outperform an index consistently. This fact is what lies behind the recent strong growth of tracker funds. You may as well buy the index if you can’t beat it. The results from the WUBS study showed that women consistently outperformed the FTSE-100 index and men did not. The male investors returned 0.14% above the index which is basically statistically consistent with having performed equivalently to it. However, I suspect that these investors would have been better off just buying the index rather than paying a lot of trading fees to obtain the same performance.
The female investors outperformed the FTSE-100 by a massive 1.80%. This may not sound much, but it is actually huge. Done over a lengthy period, it would lead to significantly improved results. Let us assume that the FTSE-100 returns 5% a year. If you started with £10,000 and performed as the male investors do, you would end up with £45,000 after 30 years. (It is always important to think long term in the stock market; to prefigure part of the answers I will discuss below, the women seem to understand this.) The female investors would turn £10,000 into £72,000 over the same 30 year period. That is a huge improvement over £45,000 and bear in mind that the female investors have taken the same risk, making it even more impressive. (One caveat is in order here: no one performs this consistently over the long-term–if they say they do, it is a huge red flag. Remember Madoff? But the point stands.)
How are female investors outperforming?
WUBS and Barclays set out a few reasons which could explain the outperformance. One of them is the one we already know about. Women are less over-confident than men. I explain how that works here: Women Are Better Traders Than Men. In summary, women tend less often to think that their new idea is brilliant and then abandon their previous idea before it has had time to work. Men on the other hand just get extremely convinced about their new sure-fire idea and go with it. Interestingly, women’s lack of over-confidence is not manifested in what they say about their beliefs. They just don’t act on them as often. We could discuss philosophically what that means about our account of belief — but the key point is that women are less likely to trade in deleterious ways!
But there are new reasons suggested. There are three that I think are especially interesting.
Women stay away from terrible ideas like #Bitcoin (this explanation is proposed by a Guardian commentary from Patrick Collinson; see links below)
I have not seen any data on how many women bought into Bitcoin, but is is certainly consistent with my claim in the second post above that female investors have stayed away — we know that women did not vote for Trump very often and much less so if they had college degrees. In addition all of the online hysteria (!) from Bitcoin boosters appeared to be from deluded male market participants.
Women avoid “lottery style” trading
It has always struck me as insanity to own a lot of penny stocks which are supposed to return ten times the amount you invest in a year because this almost never happens. As I discuss in my book, The Psychology of Successful Trading, traders can get seduced by vivid stories, incorrectly over-estimating massively their likelihood of coming about. A far better approach is just to sit still in major stocks for a long time, with maybe some spicy options for fun in a minor section of the portfolio. The problem with picking the next Amazon (or Bitcoin, for that matter) is that you can’t. You would have to own a million penny stocks for each Amazon or Apple. So this strategy is exciting but completely unsuccessful.
Men hold on to their losers
It seems that women are better at getting out of something which hasn’t worked. This came very close to home for me. Infamously, I am still holding Deutsche Bank stock, partly because I recommended it in my book as a contrarian trade. Banks are supposed to trade at at least book value (in fact, 2.0x before the crisis). So if you buy a bank at 0.25x book value, you can’t lose right? Because it is buying something for a quarter of its value. That hasn’t worked for me yet — maybe a female trader would have got out of this position a long time ago.
In conclusion, we have seen some deep-seated psychological advantages which female traders will have over male ones. This should encourage women in their investing.
Understandingbasic psychology is one of the most important but alsomost neglected tasks for investors.Of course, everyone realises that they need to analyse the investments they are considering buying.But many traders do not realise that winning in investment is also about successfully predicting what other market players will do.And that is a psychological task.
Most of the advice on the internet is not really psychology.It is quasi-psychology.You might get famous traders telling you things like “I always played tennis in the morning before my best trades to make sure I felt good.”This is useless.By all means, study what these guys do to get insights into how they analyse opportunities and maybe any tricks they have for bouncing back from a loss.But famous traders don’t have any specific training in psychology so if you are specifically wanting to improve your own trading psychology, adopting their tips (such as the tennis one above)won’t really help you in achieving that goal.
Alternatively, there are some actual psychologists who write on the topic and are experts in the field of psychology.But be careful about their specialisms.Someone who is a clinical psychologist may be an expertin schizophrenia but not necessarily other aspects of human psychology. And of course the main thing is that these expertsdo not have any serious trading experience, so they also can’t help you improve your trading psychology.
To identify the right sort of person, you need to ask two questions: does this person have significant trading experience and are they qualified in a related field?I am one of these people.
To try to convince you of this, I will outline my ideas on how to optimise your trading psychology.The first thing to know about is that we have a lot of cognitive biases —mental shortcuts that are often useful when we want a quick and dirty answer and often very unhelpful when we are trying to get something right.One example is Confirmation Bias, where people look only for evidence that supports what they already believe.There have been manyrobust psychology experiments published,that show time and time again that we do this often and consistently.
The first thing to note here is that if you use this bias when making your own trading decisions, you will make bad decisions.Every time!So you will definitely not be optimising your trading psychology.But here’s the key point: everyone else in the markets will be doing it too.
So what does that mean?It means you need to know about Confirmation Bias and think about it in a market context.Look out for it in yourself and be careful.Expect it in other market players and trade accordingly.
That’s how you stand the best chance of optimising your trading psychology.
People often ask what the common stock market terminology of bullish or bearish means.While these have standard meanings in normal speech — bullish being positive or optimistic, and bearish being the opposite — at least the term “bear market” has a precise technical definition in the arena of stocks.I will explain this here.
The formal definition of a bear market is a market that has declined 20%.
The first item to clear up on the way to understanding the definition is “what do we mean by a market?”Normally people will be talking about a particular stock market index, such as for example the Dow Jones Industrial Average (“DJIA”), the S&P 500 or the Nikkei-225 (“N-225”).So now we want to know what a stock market index is.
Individual shares go up and down all the time.One cannot say what is happening in more broad terms to “the market” by looking at single shares because of this volatility.So instead, one looks at a basket of shares.That is what an index is: a basket of shares listed in a specific location.There are thousand of these, and they can be selected in many different ways.
To illustrate this, the DJIA is a basket of 30 major US shares that are selected so that they represent a good spread of major US stocks in different sectors such as computers, aircraft manufacture and banking.The S&P 500 is a broader basket of shares issued by the 500 largest public companies listed in the US.The N-225 is somewhat different as it is made up of the 225 largest stocks listed in Tokyo.It is price weighted, meaning that more expensive stocks will be more heavily influential in the movement of the index.
So, put simply, if all of the component stocks in the DJIA go down 20% in a period, the whole index will also go down 20% over that time.Since this index and the others are a broader measure of market sentiment than any single stock, if the DJIA goes down 20% in a period, we can say that it was a bearish episode for the market.Since that is an approximate measure of the health of blue chip US equities, one would also be justified in saying that that period was a bearish period more generally for major US companies.
The DJIA has been published since 1896.The graph looks like a long uptrend punctuated by occasional bear markets.You can see this below.
People tend to talk less about the technical definition of a bull market — they will often use it more colloquially to just mean “stocks are going up.”But if one wanted to be precise, it would just be the opposite of a bear market.It would mean that a particular index had increased by 20% from a trough.
I recently discussed (in Investment Styles) the two major different styles of investing: value and momentum. One difficulty with following a value approach is the difficulty in measuring value, since much of it these days is tied up in intangible assets. I will suggest here that, counter-intuitively, buying bank stocks is the solution to this problem.
The value approach to investing is simple to understand, though perhaps a little harder to implement. The basic idea is that you buy things when they are cheap. Finding cheap assets would classically rely on looking at concepts like “book value,” which is just the accounting value of everything owned by the firm in which you are thinking of investing.
In previous decades, book value would have been simple to calculate: you could just look at the published accounts and examine how much the accountants said each asset was worth. A company making cars, say, would own a lot of items like factories, car parts, machinery and land. You could look at all of those items that you could walk up to and touch, and add up all the values, and that’s it: you have calculated book value. If you can buy the stock for less than book value per stock, you have made a good investment. If the company sold all of its assets, and turned that book value into actual cash, each shareholder would get more than book value. That’s why value investing is a good idea, and why you should try to buy stocks at less than book value.
This simple approach is more difficult in modern times, because IP — Intellectual Property — is much more important than it used to be. IP is anything the company owns which is valuable but that you can’t touch. It could be a suite of software, the value of a brand, or
simply the know-how involved in producing the products or services that the company produces. To illustrate the scale of this IP problem for value investors, consider the following estimate. Ocean Tomo, an investment bank, reckoned that the proportion of the value of S&P500 companies which was tied up in IP increased from 17% in 1975 to a huge 84% in 2015. So it is clear that there is a very serious problem in adopting a value investment approach these days, and that’s unfortunate because in my opinion, it is the only approach that works.
So what should investors do about this? I think they should look at bank stocks. This will seem dramatically strange at first sight, because banks own hardly anything at all that is tangible. However, we already saw above that this is true for all companies now, so it can’t be avoided. The key point though is this: there is a well-determined market value for everything owned by a bank.
If you look at the balance sheet for Deutsche Bank, for example, you will see a very large number of items. They will all have market values though. That will be true of shares, bonds, interest rate swaps, credit default swaps, loans to corporates, futures and options, office buildings, warrants, cash in various currencies and any of the other myriad financial assets. There will also be a certain amount of brand value but I think that will be fairly low in the mix. So basically everything owned by Deutsche Bank could be turned into cash, and a known amount of cash, quite quickly.
Banks typically traded at 2.0x book value before the crisis. The rule of thumb for value investors in the sector was “buy at 1.0x book value, sell at 2.0.” Something like this is still true: you can buy Deutsche Bank at 0.3x book value and I think you should. That’s the right approach for value investors today.
There are two major investment styles which take completely different approaches.They are value investing and momentum investing.The former, also known as contrarianism, seeks to find cheap assets to buy.It is called contrarianism because often it involves looking for assets which are cheap because no one likes them.Momentum investing is simpler.This simply observes that often, assets that have been performing well continue to do so.So investors adopting this style just look for assets which have gone up and hope that they will continue to do so.
I favour value investing.One reason for this is because the problem with momentum investing is that assets which have done well continue to so until they don’t.There is no way to tell when something which has gone up will stop doing so.And we definitely know that nothing will appreciate forever!
The difficulty with value investing is knowing when an asset is cheap.In the early days of investing, the concept of book value was very useful.This is simply the accounting value.If a company owns a factory and some machinery, the book value will be close to the value for which the factory and the machines could be sold. If you can buy a share, or a slice of the company, for less than the book value per share, you should.
Book value is still very useful on many occasions.But modern companies are very complicated, and often much of what they do cannot be valued simply.A lot of their worth might be tied up in software, for example, which is harder to value than a building.Or they might own a lot of IPR — intellectual property which again, is intangible and hard to value.But the effort is worth it.Finding a cheap company to buy is one of the best ways to trade successfully.
I have written a lot about the importance of psychological factors in investing.It is absolutely crucial that you understand these, for two reasons.Knowing about your own psychology will help you understand and improve your decision-making processes. It will be especially valuable to know when cognitive biases are likely to cause you to make errors in evaluating investments.But just as important is knowing how other investors will think — after all, they have the same psychology as you do!And knowing what other investors are likely to think of an asset is the key.Because you want to find an asset which is not just cheap — but unjustifiably so.Then you can expect it to go up sustainably.
Yesterday, the Shadow Chancellor gave a speech outside the Bank Of England on the tenth anniversary of the Lehman collapse. I will argue that his remarks do not display a good understanding of how The City works. All quotations below are from his speech.
“The key lesson is this: never let the finance sector become the masters of the economy when they should be the servants of the economy” *
This is a misconception. Finance is never either the master or the servant of the economy so it would be impossible to change it’s status in this regard. The way corporate finance works is not that different to getting a mortgage to buy a house. This is true in several ways. Firstly, if you never buy a house, you never need the finance and you never talk to a bank. That’s up to you. So that doesn’t look like a master or servant relationship.
The second element of the analogy is that if you get a mortgage, there will be conditions attached. The most important ones will be around debt service and security. Debt service means that if you borrow money, you will have to pay it back and you will have to pay interest on it until you have paid it back. Security means that no one will lend you £1,000,000 to buy a house unless that debt is secured on the house. So if you default on the loan, the bank takes your house. Again, this is just contractual and reasonable and does not mean that the bank is either your servant or your master. It is a contractual counterparty.
Corporate finance is the same. If companies want to borrow, there are conditions they have to satisfy. No one forces them to borrow. If they don’t like the terms, they can just walk away. Or they can access alternative sources of funds, such as bond markets. There are conditions there as well of course. It still doesn’t seem to make much sense to say that companies are “servants” of the bond markets.
Similarly, countries are not required to borrow money in the international bond markets. Norway has a net surplus because it has wisely saved much of its oil income. The UK is currently not running a deficit — amazingly enough, although progress needs to be measure correctly, as I have observed previously https://timlshort.com/2015/01/04/uk-deficit-no-longer-a-problem — but in the past, it has borrowed heavily. The total debt will be £1,840bn as of March 2019. All of that debt also comes with conditions though in that case not very many. You have to pay interest and principal. Again, the choice is yours and, as said, currently the UK is not borrowing any further. No master/servant relationship there.
Reuters also report** that McDonnell said that “ordinary people were still paying the price for the crisis through falling living standards and cuts to public services, and a Labour government would redress the balance.”
There have definitely been falling living standard and cuts to public services. There was definitely also a global financial crisis. But there needs to be some link between the two for McDonnell’s point to stand. The collapse of Lehman cost the UK taxpayer nothing. McDonnell can only mean the bailout of RBS. This definitely cost the UK taxpayer. Arguably, a bank needing to be bailed out is the only reason to care about what they get up to. If they lose a lot of shareholders money, that is no one else’s problem. The only thing worse than bailing out RBS was not bailing it out.
The bailout of RBS amounted to £45bn. The Government spent that amount on buying shares. It still holds a lot. It has made a loss of £4bn on what it has sold so far. It will doubtless make further losses on future sales. However, these amounts are simply trifling when compared to government expenditure. Welfare spending will be £115bn in 2019 alone. So it is not the case that the RBS bailout contributed in any meaningful way to public sector spending cuts.
What did cause that was the government’s income — which is entirely sourced from taxation of the private sector — declining. And what caused that was a global recession. That was quite plausibly caused by the events of 2008 including the subsequent credit crunch.
But how will Labour “redress this balance?” Will it force banks to lend? They are private sector firms. Will it replace them with public sector banks? The record there is not good. Spain had a network of Caixas: local banks run by local worthies such as trade unionists and priests. They were massively corrupt and had to be bailed out having funded a large number of white elephant projects.
Meeting with bankers and asset managers, McDonnell said:
“You’ll get a decent rate of return but we’re not being ripped off anymore. Ripped off by speculation, privatisation, job cuts, exploitation of workers.”***
This is a claim that the government received a bad deal as a result of several activities.
Speculation is betting that an asset’s price will move in a particular way. It is not obvious what the government’s involvement would be in that or why it should care. If you suggest that RBS needed to be bailed out because it had “speculated” on subprime mortgage bonds, you need to explain why it is speculation to invest in Aaa securities.
Privatisation is a source of funds for the government. There no obvious way for it to be ripped off by doing that, unless it sells an asset for a low price. Which again, no one forces it to do. Perhaps McDonnell means PFI. That is also excellent value for money if the contracts are drafted correctly.
Job cuts: I have no idea what McDonnell means here. Obviously I understand what a job cut is, bit what is McDonnell proposing? That the government will regulate firing? That is bizarre and generally results in a lack of hiring because you don’t take people on if you have to keep them forever even if they are incompetent, corrupt or don’t turn up.
Exploitation of workers: so what is that exactly? And why is it not adequately addressed by the current regulations such as employment tribunals?
It does not appear as though any useful answers to the crisis are to be found in McDonnell’s remarks.
I will argue that Proust’s picture of how we get into the minds of other’s is simulationist, thus following the account that I favour rather than the mainstream one.
The term in psychology for the way in which we predict and explain the behaviour of others is “Theory of Mind.” This is, I suggest, something of a placeholder, because it is in fact deeply unclear how we do this. Or even if we get it right. It certainly looks like we do, but that’s just because we confirm our results using the same method. (This is sometimes known as the “dipstick problem” in philosophy. I can’t tell whether my fuel gauge is accurate if I only look at the fuel gauge.)
There are two accounts of Theory of Mind in academic psychology. One is called Theory Theory. This is the claim that we have a theory of other people that we learn when young. This is the mainstream account. The other account, which I support, is called Simulation Theory:
Simulation Theory suggests that instead of using a theory of others, what we do when we predict and explain their behaviour is to simulate them. Metaphorically, we place ourselves in what we think is their position with the information and desires we thing they have, and then work out what we would do.
Anyone who has read Proust knows that he has an exceptionally deep and unusual set of insights into our psychology. His insights are not paralleled elsewhere in my view, with the possible exception of Henry James. For this reason, it is unsurprising to me that he also favours Simulation Theory. Moreover, Proust even seems to suggest the defence of Simulation Theory using cognitive biases which I have proposed.*
There are two key quotations I will use to back up this claim.** The character Swann is discussing “fellow-feeling,” and remarks to himself as below:
“he could not, in the last resort, answer for any but men whose natures were analogous to his own, as was, so far as the heart went, that of M. de Charlus. The mere thought of causing Swann so much distress would have been revolting to him. But with a man who was insensible, of another order of humanity, as was the Prince des Laumes, how was one to foresee the actions to which he might be led by the promptings of a different nature?”
This tells us that Swann has observed that it is easier for him to predict or explain the behaviour of others when those others are similar to him. In this particular case, Swann is wondering which of his friends might have sent him a distressing anonymous letter. Swann believes that Charlus is similar to Swann himself, that Swann himself would not have sent such a letter, and therefore Swann concludes that Charlus did not send the letter.
On the other hand, Swann believes that des Laumes is a very different individual, who is “insensible.” (I suspect that a more modern translation would use “insensitive” here.). Note that Swann, in a very simulationist vein, does not say “des Laumes is insensitive, so he might have sent the letter.” Instead, he says “des Laumes is insensitive, so I cannot tell what he would do.”
This is a very simulationist line. It says, in effect, that Swann is unable, he believes, to simulate des Laumes, because des Laumes is very different to Swann. Note this is not consistent with the mainstream Theory Theory view. There is no reason why Swann, an intelligent and perceptive man, could not have a good theory of insensitive behaviour. There is by contrast every reason why Swann could struggle to simulate insensitive behaviour, lacking as he does the experience “from the inside” of such behaviour.
A further simulationist view is suggested later; someone might be a genius:
“or, although a brilliant psychologist, [not believe] in the infidelity of a mistress or of a friend whose treachery persons far less gifted would have foreseen.”
This is a claim that people may be extremely intelligent and even special gifted in academic psychology but still make Theory of Mind errors in relation to other people not so gifted. Note how uncongenial this is to Theory Theory. Intelligent people who are brilliant psychologists should have an excellent theory of others and so be able to make very good predictions of their behaviour. Simulation Theory, by contrast, will predict exactly what Proust is describing here: brilliant, intelligent (highly moral?) individuals will fail to predict the behaviour of others who do not possess those characteristics. And similarly, more ordinary mortals will be able to simulate much better and thus predict much better when the person to be predicted is more like the person doing the predicting.
The major objection to Simulation Theory is that it does not account for surprising results in social psychology, such as the infamous Stanford prison experiment. Here, people behave amazingly harshly, for no apparent reason. This behaviour is not predicted by anyone. Theory Theorists claim that Simulation Theory cannot explain this, because we should just be able to simulate being a guard in a fake prison and then predict the harsh behaviour.
I provide a response to this objection on behalf of Simulation Theory. I suggest that what is missing from the simulation is a cognitive bias. In the case of the Stanford Prison Experiment, the bias in question I propose is Conformity Bias. Simply put, this is just our tendency to do what we are told. This bias is a lot stronger than we suppose, in comfortable repose.
It is gratifying to find Swann also gesturing in the direction of this Bias Mismatch Defence, as I call it. Swann further observes that he:
“knew quite well as a general truth, that human life is full of contrasts, but in the case of any one human being he imagined all that part of his or her life with which he was not familiar as being identical with the part with which he was.”
This, if Swann is accurate in his self-perception here, is a description of a systematic Theory of Mind error. It is a form of synecdoche, if you like. Swann takes the part of the person he knows and assumes that all of the rest of that person is the same.
I have suggested that one of the biases which can throw off our simulations is the Halo Effect. This means we know one thing about a person or item which has a certain positive or negative perceived value, and we then assume that all of the attributes of the person or item have the same value. For instance, someone who is a good speaker is probably also honest etc. There is of course no strong reason to think this, rationally speaking.
I have discussed the implications of the Halo Effect on predicting behaviour in financial markets previously:
In that case, I called the Bitcoin bubble just before it burst by employing the Halo Effect and positing that it was affecting the judgement of buyers. It is encouraging to see that Swann is also on the same page as me here!
Note that I do not claim to be a Proust expert or even have completed my reading yet! I do not therefore suggest that the above represents a radical new reading of the whole of Proust. I make only the modest claim that in this one paragraph, Proust describes a version of Theory of Mind which is more congenial to simulation than to theory. Since there are only these two developed candidate explanations of Theory of Mind, then that is already interesting. (There is also a hybrid account which employs both simulation and theory, but that is a mess in my view and there is no evidence of for any theory in the above quotation and therefore no evidence for a hybrid account.)
*”IN SEARCH OF LOST TIME – Complete 7 Book Collection (Modern Classics Series): The Masterpiece of 20th Century Literature (Swann’s Way, Within a Budding … The Sweet Cheat Gone & Time Regained)” by Marcel Proust, C. K. Scott Moncrieff, Stephen Hudson).
**It might be argued that this view is not that favoured by Proust himself but by Swann, who is a character created by Swann. I will not pursue this sort of Plato/Socrates point, but merely observe that it is at the very least true that Proust considers the position worth discussing. Moreover, I think it is very clear that Swann is rather to be considered an intelligent, discerning individual, if perhaps somewhat afflicted by propensities for self-deception, and so the fact that this view is at least that of Swann is sufficient to make it interesting. (I am informed by someone who knows Proust better than me that I am likely to revise my view of Swann in a negative direction as my reading progresses.)