The Model Thinker #4 : Modelling Human Actors

The first serious chapter on modelling covers human actors.

There are two general approaches to modelling a human actor.

a) The Rational Actor Model

Modelling human actors as being rational has come under a lot of criticism but no other model has the kind of consistency and elegance offered by this approach. By making an assumption that a person will act rationally, you can also come up with behaviour that approximates that of a highly intelligent player.

In the Rational Actor model, individuals choose the action that maximises their payoff. This pre-supposes that a payoff function is defined over a set of possible actions. If an investor is rational, between an investment that generates 10% and 12% but with the same semi-variance, the investor will choose the latter strategy.

Upon further inspection, you will realise that most human beings are hardly rational. One component of rationality is that ability to consider all options. All alternatives must have a preference ordering. Another aspect of rationality is transitiveness. If you like A over B, and B over C. You must like A over C. ( I am hardly rational when it comes to movies )

If you come into the financial markets assuming that all market actors are rational, you will be in serious trouble. Even I have serious quirk which I am not really willing to show the world even though Dr Wealth colleagues have asked me to give more details on my portfolio - one of the quirks I am less proud off is that I like to invest in denominations of eight... For example, I have 8800 shares of UMS.

To blunt the lofty assumptions of Rational Actor theory, economists now add theories of loss aversion and hyperbolic discounting into whatever models they have. We take larger risks when faced with losses, and we apply a stronger discount rate of our immediate future.

b) Rule-based model

Rule based models do not use a payoff function but assumes that people will behave based on specific behaviours. One possible way to model the behaviour of an average Singaporean is that, based on government  data, he is likely to set aside 20% of his take home pay.

The rules-based model may be fixed, but common sense tells us that people adapt to policy changes and changes. When the salary of a person goes up, he might be able to save a larger proportion of his income. He may have to forego savings when he gets retrenched.

The spirit of modelling is to adopt the approach that all models are wrong one way or another. One criticism of modelling the behaviour of human beings is that changes in policy or the environment will produces behavioural responses by those affected. This renders past behaviour inaccurate.

But we know this problem well in quantitative investing.

This is the problem of non-stationarity.

When financial bloggers take a break

This is a pretty rough week.

First 15WW has expressed a desire to take a break. You can read about it here. Then yesterday I received news that Cheerful Egg would also be taking a 90 day break to reassess his priorities.

These are good bloggers to follow because their material is quite candid and original.

The work of a financial blogger is a thankless job. A few years ago, a lot of us came in with the idea of monetisation of our blog material. That turned out to be much harder than we thought. Even if we can cultivate a legion of fans, unless we conduct courses, give talks or make physical appearances, the profits from writing articles can only float to maybe a few top blogs in Singapore. If you think about a successful local blogs, maybe only Investment Moats and AK71 come into mind.

Once you cannot monetise a blog, the disadvantages kick in. Unless your blog is completely informational, any amount of candour can potentially affect your day job and employment chances. I constantly find that everything I write can offend potential employers. Luckily, I can do it because I don't really need an employer these days. Imagine how hard is it for someone trying to FIRE at the same time.

Here are some for the consideration of other financial bloggers :

a) Read a lot. 

The crucial point about sustainability is to read a lot and reflect your reads on your blog. Your articles are novel because you adapt what you read into living in Singapore. You would also have a constant stream of articles that will eventually broaden your fan base.

For me, thought leadership matters a lot so when a new book comes online, I pay more to get it into my hands so that I can incorporate it into my training materials or blog.

If you reason that reading should be factor into the time I spend being a trainer, then I actually work harder than most office workers in my current life. I don't include this tine in my life-energy calculations because I enjoy reading and would do it even if I don't have classes to teach.

b) Don't parrot mainstream ideas unless you have a novel interpretation of materials at hand.

I thank SMU for this idea. When grading presentations, an A grade is only reserved for a "novel" interpretation of legal ideas.

The relative popularity of Marie Kondo has led me to clear about 40% of my clothes and surrender it to H&M for a few vouchers. The problem is that in becoming mainstream, this form of minimalism is less interesting to write about.

What is more interesting is the question of which investments "spark joy". If I can come out with a thesis of why Asia Pay TV sparks joy if it is below 13cts, I have a nice article that can pick up a larger share of the attention. 

c) A blog is only one piece of your personal brand management.

As more sophisticated blogs come online and some of us start to align with very powerful groups like Seedly, the question is what kind of room does a blog simpliciter have in the grander scheme of things.

Seedly has become a behemoth in the industry. I think a blogger ignores them to their own detriment. This year, I realised that it's way better to cooperate and see if there are win-win initiatives with them.

This is going to be hard for introverts but bloggers need to put themselves out there to change the game. This means giving talks, making physical appearances and conducting courses.

I have been thinking about the question of using podcasts and vlogs to extend my reach myself.

d) A financial blogger needs to be a little selfish too.

Of course bloggers have to address what they can do for an audience, but a more important question is what can the audience do for you. Many readers just scour blogs for stock tips.

The surest path to burn-out is to keep giving but not getting anything out of your blogging activities. Your blog should be about self-improvement and even some degree of self-aggrandisement.

I can keep doing this because I don't really care about the audience -  I know folks want a brutal take on polytechnic students, why they need to be careful when signing up for a private degree, and definitely how our CPF program is like schizophrenic prostitute. These postings give me 1000 views within a day. It took me only 25 minutes to write the CPF Prostitute article.

But I also write for myself to chronicle key ideas to make me a better investor, Articles on Aristotelian categories would be lucky to land 200 hits in one day. These articles are harder to write because all these ideas need to be shoe-horned to practical life. In the future, these are my hidden real options to publish a full thesis on investing.

I think more bloggers will quit  or at least take a break in 2019.

But even if a lot more bloggers will take their place, I always feel a little sad when this happens.

An Earnest Conversation - Dealing with posts by commissioned sales professionals that you may disagree with

Money Maverick wrote a really sweet post which showed his human side.

I would like to invite everyone to read it here.

While you don't have to agree with Money Maverick (I certainly don't), you will probably accept that he should be treated like a fellow human being and did not deserve this level of abuse online.

Not everyone in the community likes the style used by Money Maverick, some folks say that he's too slick and basically would share details on the securities he pitches only to his clients. As a trainer who does uses my blog to promote my personal brand, I can understand that Money Maverick has to keep doing what he does because one successful case conversion can net him a reasonable amount of commissions and allow him to attain his life's aspirations.

So today, I just want to showcase a better way to deal with such articles.

A lot of unhappiness was directed at his claim that he has a fund that can provide passive income of over 7.8% but at a volatility below REITs.

a) Instead of attacking him for being secretive, why not try to make an intelligent guess as to what it is ?

If I may guess what he's referring to, it may be some kind of fund that specialises in junk bonds. As 7.8% yield is rather high, it may be focused on specific region like Asia. The low volatility probably comes from the fact that these bonds are thinly traded anyway and you might be taking on a larger share of credit risk. There is also forex risk as high yielding bonds come from countries experiencing high inflation. So while traditional measures of volatility would be rather low, you might not like it when one of these junk bonds default.

But why not challenge yourself to take a higher road ?

b) Another approach is to see if you can beat his fund at his own game using DIY components. 

We can find REITs that yield over 7.5% from the REITDATA.COM, simply picking out these REITs will give us about 10+ counters. I did an average of these yields and I got 8.61% which is already higher than 7.8%.

[ In November 2018, I backtested a dividends strategy with REITs and it returned about 19.8% a year with a semivariance of only 11.17%.  Volatility of REITs is already pretty low. ]

The next question is how do we get volatility that is below that of REITs ?

Simple. Just add retail bonds.

If we can add Astrea IV Bonds into the mix at a proportion of about 18%, you will end up with a portfolio that gives out about 7.8% dividend yields but have, generally speaking, lower volatility than REITs.

( A craftier investor can add a commodity ETF because of the lower correlations )

So if I have $100,000, the appropriate response is to structure a portfolio of equal weighted REITs that yield at least 7.5%. In such a case, $82,000 should be invested in this portfolio. $18,000 should be used to buy Astrea IV bonds.

So with a simple exercise, I can confidently build a portfolio that has a decent probability of beating Money Maverick's proposed fund.

If you are willing to go DIY, you have a huge edge over solutions offered by sales professionals - You pay lower commissions, management expenses and there might even be tax advantages as we're talking about S-REITS here.

Let's try to make the financial blogosphere a nicer place for folks like Money Maverick. There is no need to condemn him for his choice of profession.

When he proposes an investment idea, challenge yourself to guess what it is.

Then take the high road and engineer a DIY solution to the best of your ability.

This why I always take the position that blogs like Money Maverick can potentially teach us a lot about investing.

The Model Thinker #3 : Aristotle's categories

I can argue that Aristotle is the philosopher who inspired all of quantitative investing. Even before the establishment of modern financial markets.

Aristotle created a framework of inquiry that is relevant even today, his ten categories being : Substance, Quantity, Qualification, Relative, Where, When, Being-in-position, Having, Doing and Affection. By inventing these categories, it is possible to classify everything under the sun. Once a set of objects can be categorised, we can start hypothesising about the relationship between these objects.

Naturally, in this modern world driven by data, a good working theory can result in extraordinary profits.

To bring this discussion down to earth, I have been experimenting with folks who show up for my previews. As my quantitative models have been working pretty as of late, I want to see whether the same quantitative discipline can be used to learn more about folks who are passionate about learning about investment. This is an example of one-to-many thinking : can I use the same models I learnt in my investing work in my new job as a trainer ?

The following slide represents my maiden attempts to understand my preview participants better :

I tried to distill the MBTI personality tests into one Mentimeter slide and attempted to figure out what "personality" do preview participants have.

After some crowdsourcing, I have at least one data-point that folks who show up for previews have the ISTJ personality. Introverted, data-driven, and decisive thinkers who otherwise would make great administrators and accountants.

So I can now imagine my course preview as some kind of equity screen that returns participants who belong to the ISTJ personality category.

Of course, just because you have an equity screen with a selected stock does not mean that you can you can profit from it.

Being an ESTJ-turn-ENTJ, communicating with ISTJs needs to be picked up as a skill.

My next step is to subtly change my materials to reflect the needs of my audience. Every assertion should be backed by some data. Every major outcome should come with a series of steps on how to achieve that.

What does the Finance Industry and the Social Development Unit have in common ?

Until the Millenials developed Tinder, dating was not a straight-forward process for guys in my generation. An entire generation of men were emotionally scarred by the Social Development Unit or SDU.

I was, fortunately, not a victim of this government initiative. Instead, after being burnt by a match-making attempt by my parents, I developed my own quantitative approach towards meeting women.

( This is why I have a family today in spite of being D&D otaku and troll. That story is something I will tell another day. )

Some of my friends were not so lucky as to escape the clutches of SDU.

Seduced by cheap government-sponsored dating activities, many of my friends fell into the trap of attending SDU events, some retained their sanity long enough to tell me their tales of woe. Through the horrors experienced by my friends, I have heard tales of people so unattractive, boring or so disagreeable, they could have been tales to scare naughty children being putting them to bed.

It took me and my friends ages to realise what the ultimate objective of SDU was.

In my opinion, it was clearly not an attempt to match-make singles.

The aim of SDU is to hurt your self-esteem and lower your standards so drastically that you would eventually settle for anything that comes by in your life. Imagine if you are fed army rations everyday. One day you are given a slice of kaya bread - that would be the best meal you ever had in recent memory.

Thanks to Tinder and Coffee Meets Bagels, the SDU is now a relic of the past.

But very recently, I have noticed that the finance industry is now using the same tactics to increase their profits.

Just the other day I went a new eatery in Selegie Road and I was lucky enough to overhear a conversation between the proprietor and his old NS pals. The proprietor worked in insurance and was able to raise enough capital to start the food establishment with another insurance buddy of his.

He shared a few interesting snippets about the industry. Namely (a) closing one case nets him about $1,600. (b) He can make about $6,000 - $7,000 a month (c) Even without closing cases, his previous wins can give him about $3,000 - $5,000 a month. Payments seem to stretch years (d) He does this by pure cold calling and he does not sell to friends or relatives.

I came away with the impression that making it in insurance is all about dealing with rejection, but more importantly, the commissions earned has to come from someone - the hapless insurance consumer. If closing a case nets the agent $1,600, it basically means that his client loses about $1,600 when he agrees to whatever advice was given to him.

How does the industry collaborate to lower the standards of consumers since so much money goes into paying commissions ?

Broadcasting lower returns, of course. Of recent note, I have seen a lot of insurance ads talking about the returns a consumer can expect from their products with an investing component. These numbers tend to hover around 2-3%.

Broadcasting these returns has the same effect as SDU, eventually creating a lower anchor for hapless investors to lock onto. Whoever manages these investment products have greater leeway to provide the higher commissions to insurance agents, who can, in turn, make more aggressive moves against consumers.

Here's how can reverse this anchor.

After a brutal 2018, the SPDRs STI ETF still returned about 6.5% since inception, or more than 8% if you consider its performance for the past 10 years. If you take the Nikko AM Investment Grade Bond ETF, you can expect a yield of 3.2%. A combination of these two ETFs will still net yourself more than 5%.

Another argument is that we can expect inflation to be around 1.9% every year. Even though Singapore has experienced lower inflation than other OECD countries, you are in essence locking yourself down in an instrument for real returns at around 1+% at most. One way to troll your advisor is to ask him to express his projections in real instead of nominal terms.

If the insurance agent insists that the lower returns are guaranteed, make sure you read the small print. There may be a loss of liquidity for a number of years. In any case, directly pumping into your CPF-SA will net you a risk-less 4%. The fact that some products lock you in for a number of years and yet the returns are benchmarked against SSBs which do not have a lock in period is possibly the result of very sneaky marketing.

You should also remind your agent that capital guarantees are predicated on the insurer not falling apart. (AIA was bailed out by the US government during the 2007 recession )

The financial industry is creating the same trap that has hurt an entire generation of men who have attended SDU dating events in the past. Don't let them trap you into accepting illiquid investment products for real returns of less than 2%. Instead of going SDU, why not venture overseas like Vietnam and Thailand to meet the women there ?

Similarly, separate your investment and insurance needs.

Where possible use a DIY portal for your insurance needs. Pay a small premium for pure insurance products, minimising commission payments, then invest the rest in a portfolio of standard vanilla equity and bond ETFs.

How to take a crap on quantitative backtesting.

With the efforts I have been gaining to show up some misconceptions about investing in local stocks, I would have thought that I should be become by now public enemy number 1 from value investors. Sadly, I have read some attempts to discredit quantitative backtesting and I find that they are either holding back key information, or generally lack intellectual sophistication.

As such, I will take on the burden of criticising quantitative backtesting myself. This is because, of all people, I cannot afford to drink my own Kool-aid. Not only could I stand to lose money if my methodology is flawed, it can affect the portfolios of my students too.

There are, in fact, three valid responses when faced with quantitative backtesting data.

The first, which I support, is to simply accept that is a superior approach towards investing. The second is to disagree and argue that you can get superior returns because the model inadequately capture all the risks associated with this strategy. ( For example, the strategy of small stocks is plagued with the problem of illiquidity. ) The third is to simply argue that backtest models model the past and the strategy simply will not work in the future. You need to have a better way to make money if you argue as such.

A good quantitative strategist must address three specific issues :

a) Data Mining

If you spend enough time interrogating data, you will always find a combination of factors that can result in excellent past performance. There are hundreds of factors to play with, all the quant needs to do is to set a time range and start grinding the numbers through the factors and pick out the best one of the lot. The problem is always the question of whether the strategy works in the future.

The only way I address the problem of data mining is to use only tested factors in the US and repeat the experiment in SGX. Then I do some work to ensure that I'm not crazy by testing out the strategy in Bursa Malaysia. I can safely say that dividends sustainable by free cash flow has not only passed all the tests but also receive support from value investors.

b) Non-stationarity

Imagine you have a bag of red and white balls. You draw out the balls one by one. Over time you have a certain idea of the proportion of red balls to white balls after a while. Sadly the markets do not work like this - when you invest in the markets, the markets will change the bag every now and then. So when you are having the Great Recession and lowering interest rates, you are drawing from a different bad than when you are facing the trade war between China and the US.

This is a much harder issue to address as this means that the returns and standard deviation can change as we enter a new stage of history.

This is not a easy issue to address. My only defence is that if there is a significant change in history, it should be argued as such. We had the same PAP government for 50 years. If anything, Singapore investors have a greater reason to stick to models captured in the past than, say, Turkish investors.

My only defence is to keep expanding the backtest timelines and watch other markets when strategies begin to fail. Of late, the small firm effect is not as profitable as before and value has been losing to growth for over a decade in the US.

c) Model misspecification

This is so hard, I struggle to understand how to even deal with it. When we fail to select factors when we create a model, a factor like the low-variance effect can either be interpreted as a market beating anomaly or a risk premium. So the model is incomplete.Academic researchers have found 316 different factors in quantitative investing.

 The combination of factors I employ are the obvious ones documented by texts. The sample size of Singapore markets is also very small such that using more than 2 factors at one go will result in a set of stocks that may be too small for diversification.

So I have chosen to ignore this critique of quantitative investing.

Maybe a professional quant can share some ideas on how to address these issue when you run a professional fund.

The Model Thinker #2 : Seven uses of models

In this second installation of The Model Thinker, I will talk about seven uses of models.

The author uses the REDCAPE acronym to illustrate these seven uses which I will illustrate here for folks interested in their personal finances :

a) Reason - To identify conditions and deduce logical implications

One of the best illustrations of this usage is Ray Dalio's Big Debt Crises he showcases one way to look at how accumulating foreign debt can lead to a depression later on. A detailed discussion of this model, unfortunately, cannot be done on a blog. We do know that taking on a lot of foreign debt can led to tragedy later on.

b) Explain - To provide testable explanations for empirical phenomenon

I attempted to explain the underperformance of a REIT portfolio due to an investor's preference for REITs run by 'good' sponsors using quantitative backtesting. This racked up a lot more unhappiness than I originally intended, but I will possibly do up a sequel to that article quite soon.

c) Design - To choose features of institutions, policies and rules.

The CPF Life program defaults to the Standard Plan which is drawn from the concept of choice architecture illustrated in the book Nudge by Richard Thaler. The government obviously wants more people to load up on annuities in their retirement plan so a sneaky way to do it is to make it the default. This is excellent policy design, but I fully intend to switch to the Basic Plan the moment I get to do that.

d) Communicate - To relate knowledge and understanding.

If you follow my block, you might know that I am getting rather obsessed with building a taxonomy/epistemology of financial knowledge. I was inspired by the TCP/IP stack and a writeup from a finance professor. I hope to explain the problem of financial knowledge better. If I fail, at least the IT guys and engineers will appreciate my use of this model.

e) Act - To guide policy choices and strategic actions.

A very simplistic way to locate Singapore's position in the market cycle is to look at trends of CDP growth, inflation and unemployment. Once we can guess at our market cycle positioning, we can start to determine our asset allocation. At this point of time, we might be in a contracting phase - this means buying bonds in spite of their lack lustre returns over recent years.

f) Predict - To make numerical and categorical predictions of future and unknown phenomenon

What does it mean when my strategy of buying stocks yielding more than 4% and having a P/E less than 12 returns over 20% ? A lot of folks misinterpret this as  projection of future returns of 20+%. Actually, I build quantitative models to maximise the chance of outperforming the market average. So I am predicting that this 4% yielding and PE would do better than holding a basket of Singapore stocks in equal weights - a less dramatic prediction than +20% gains every year.

g) Explore - To investigate possibilities and hypotheticals.

Over the next few days, I will be investigating whether REIT's with 'good' sponsors have a larger average volume over the past 6 months.  I hope to use these insights to see whether I can put a second nail into the "Good REIT Sponsor" idea that many investors currently have.

In summary, models are very powerful tools to assist an investor. Hopefully as I explore this book further, I will learn of new ways to structure an investment plan.