Browse Month

January 2018

Reading List: ‘Misbehaving’ (Richard Thaler)

I spent a good amount of time thinking about whether I should register in the UK Registered Traveller Scheme (costs £70). In total, I easily spent more than seven hours thinking through this, modelling a few scenarios, and trying to estimate the value of my time relative to data about airport immigration queue timings. I earn more than £10 an hour.

In hindsight, I tried to make a good decision above, but the decision to try (at least as hard as I did) was probably a bad one. I’ve generally always been interested in making better decisions, and these decisions often involve managing resources that are finite. I’m not sure exactly when I first came across the field of behavioural economics, though. The notion of an Econ (a fully rational agent that maximises self-interest) is certainly something I’d come across in high school economics classes. I remember also familiarising myself with quite a number of these cognitive biases when attending talks on personal finance during various past internships – and certainly when reading up on personal finance online.

Misbehaving describes a wide variety of historical research events concerning behavioural economics. This covers its growth from infancy to becoming relatively widely accepted in the mainstream. While some rudimentary knowledge of mathematics is needed to follow the text, I wouldn’t say much background is required. I was fairly familiar with quite a large number of the experiments described, so I would imagine that there might not be that much new content for readers already interested in the field. Nonetheless, there were quite a few new things I came across; I hadn’t heard of the mug experiment [1] used to demonstrate the endowment effect. The analyses of closed-end mutual funds [2] and NFL draft picks were also interesting to read – it was nice to be able to relate knowledge to concrete application.

The book begins with an introduction to how the field came about, describing the author’s observations about human behaviour in practice that contradicted the true behaviour of a rational Econ. These include considering supposedly irrelevant factors (SIFs) like one’s current feelings as relevant; valuing things that one owns (one’s endowment) higher than things one could own, and an imbalance between preference for gains and losses. There was also a relatively more anecdotal list of observations the author made too. I’ve made my own list for things I’ve done in the past, and clearly do suffer from a number of these inconsistencies as well:

  • The introductory example. (What’s the value of an hour?)
  • The returns from my mutual funds come from both capital gains and dividends. So far at least, I’ve always been reinvesting all dividends. Yet, I feel happy when a dividend comes in. (Dividends are taxed more harshly than capital gains.)
  • I’m much happier receiving a gift that someone has picked out for me than if the person gave me the cash and suggested that I might be interested in buying the gift with the cash. (I can replicate the first scenario in the second, and I also have more choices.)

From there, a variety of topics are presented in a largely topical and somewhat vaguely chronological idea. I think my complaint that I found a substantial portion of the material to already be familiar was largely in sections II (“Mental Accounting”) and III (“Self-Control”), perhaps because these are the relatively common examples people with some interest in the field are likely to come across first. The later sections get more interesting. Section VI (“Finance”) played well with my own interest in personal finance; Section VII (“Helping Out”) discusses practical applications of using insights from behavioural finance to ‘nudge’ people to make better decisions regarding their own finances… or complying with tax law.

The book ends with the author outlining hopes for how behavioural economics could continue to grow in relevance, discussing fledgling work in education. There is also an interesting section where the author dispenses some advice for life in general, based on his work in behavioural economics (specifically: make observations, collect data, and be willing to speak up).

While models should indeed account for important variables, I’m not sure I necessarily agree that these factors should be consistent over time, mainly because I think individuals can learn and within certain bounds optimise their own behaviour, though not to the point of being a hyper-rational Econ. Although in chapter 6 (“The Gauntlet”) it is claimed that learning how to make many high-stakes decisions is difficult because we don’t get many attempts at them, I think some of the decision-making skills are transferable. I might not get to make many decisions buying houses, and there certainly are aspects about buying a house that are peculiar to the task itself – yet, learning to learn about relevant considerations for the domain (as I already do with consumer electronics), plan how one’s cash flow is going to work (as I already do with regular investment into mutual funds) and being more aware of possible cognitive biases (relevant in almost all decisions) all seem to be helpful.

I enjoyed the book as a whole; it was a pretty engrossing read on my flight from Singapore to London. It held my attention for at least a good three or four continuous hours on that plane, and I was eager to finish reading the book when I landed in London. I’d recommend it as a good read, though as this is written to a fairly general audience readers who already have substantial knowledge of the field might find there not to be as much fresh content.

Retirement by 40?

I overheard a conversation a few days ago on the near-impossibility of retiring by forty. It is understandable (consider 40 in relation to standard benchmarks for retirement – a private pension can be withdrawn at 55 and the state pension is given at 65, and these numbers are trending upwards). I’m not sure I agree, though; there exist quite a number of examples of people that have done this [1, 2]. Meta-analyses disagree (against: [3], in favour: [4]). It’s true that internet and media sources may perhaps not be reliable, but in any case one can perform the relevant analysis.

Even given the option, I’m not certain I would take it. It’s arguable that I had a taste of retirement for the two-odd months in between submitting my Masters thesis at Imperial and starting full-time at Palantir, and I didn’t find it that easy to fill my time after a while. I’d probably stand a better chance now, having reignited a couple of interests in things apart from computer science.

Anyway, let’s get to analysis. One simple way of decomposing this problem can involve

  1. Figuring out the amount required before retirement is feasible, and
  2. Figuring out the required savings rate to reach the result obtained in step 1.

For the first point, there is a well-known 4% rule. Suppose you withdraw 4% of your portfolio in the year when you retire, and then adjust your withdrawals for inflation every year. Then, your portfolio will last for at least 30 years in 96% of historical scenarios. I have some issues with this, biasing in both directions.

I think 4% seems lower than is reasonable, for several reasons:

  • The idea that one blindly draws the stipulated salary even when the market is down seems absurd. Really, one should factor in market returns when making one’s decisions about income, as in [5 – note, technical!].
  • The study assumes that the portfolio alone supports the retiree; yet, a side hustle of some kind may be relevant, and at least in the UK the state pension could kick in once the retiree reaches 65 (or whatever the age is at that time).

Yet, there are certain reasons to adjust the figure upwards too:

  • The life expectancy of someone who’s 40 is probably higher than 30 more years (especially one who’s considering retirement at 40!), hence that’s not enough as a baseline.
  • The study used the US markets, which have been performing very well. Of course, one can decide to use exclusively the US markets, but that tends to introduce currency risks too.
  • The study in question does not account for fund and platform fees. These can be kept quite low (I estimate my own portfolio operates at about 0.22%, and some of this is by choice because I hold some active and smart-beta funds, along with indices that are a bit more exotic) but invariably chew into returns.

It seems like it’s a reasonable rule of thumb, though I wouldn’t treat the figure as authoritative.

One needs to estimate asset returns and inflation for both parts 1 and 2; this can be partially simplified by working everything in real terms, though there is a risk that owing to high inflation increasing one’s savings in line with inflation can prove untenable. Typically, one relies on historical data; for instance, UK stocks have returned about a CAGR of 5.2% from 1900 to 2011 [6]. Post-retirement sequence of returns risk can prove troublesome, although the variance might indeed be smoothed out over a longer period.

Notice that assuming one starts from zero and using the 4% or any constant-percentage model, the only factor after the asset returns and inflation rate have been factored in would be your savings rate – the level of expenditure needed is a function of this. I guess one could introduce another factor for decreased spending upon retirement! An example of a concrete calculation (inclusive of a link to a spreadsheet) can be found in [7]. Using the examples there (5% real returns, 4% withdrawal rate) and bearing in mind that I have 14 years till I’m 40, that clocks in at a smidge above 55 percent.

For an individual, though, there’s probably a somewhat easier method to determine if a retirement by 40 or early retirement is feasible:

  1. As above – figure out the amount required.
  2. Given one’s past saving and investment patterns, estimate the amount one is likely to have at 40 if one continues to behave in the same way.

Of course, we need to make the same assumptions involved in figuring out the value computed in step 1. We also still can’t get away from estimating inflation or market returns in step 2. However, the previous calculation for step 2 assumes a constant savings rate; with this method it is a lot simpler to adjust the model to account for events peculiar to one’s own situation (such as long CDs maturing, stock options, vesting of bonuses, known large expenses etc.).

We then compare the figures in steps 1 and 2; there is of course some wiggle room. I think there’s a distinction to be drawn between deciding that one is financially independent and pulling the retirement trigger, though that’s perhaps a separate discussion topic. [8] I certainly would be interested in the first, but not the second at this time (and, hopefully, even at 40).

One can even switch the method up a bit further:

  1. Figure out the amount one is likely to have at 40 (step 2 above)
  2. Figure out the withdrawal amount one can derive from that. Decide if that’s feasible.

Again, we don’t get away from assumptions concerning inflation or market returns. Deriving values in step 2 gets tricky; one can always use the 4% rule or assume some other constant factor. It’s worth saying (for all of the methods) that building in fudge factors to leave some leeway for underwhelming market returns is probably a good idea, since getting back into the workforce after a long spell of early retirement might prove difficult.

Personally I’m very fortunate that this should be possible if I decide to push hard on it. It’s difficult to say though – past performance is not an indicator of future performance, and I’m at a point where I’d say my past spending is also not an indicator of future spending. I think I’m pretty frugal, but don’t entirely fancy maintaining the same degree of strictness I’ve been running with in my university years throughout. It’s certainly possible, but also definitely not easy, and I’m not sure it’s what I’d want to do.

This Side of Town (Goals for 2018)

I’m back in London, though I still think I’m on holiday. While that’s not a bad thing in and of itself, it doesn’t quite feel like 2018 has fully started yet. I have an annual exercise in goal-setting after the year-end reviews, to help me figure out what I should be focusing on in the year ahead.

Software Development

A1. Grow rapidly as a software engineer.

In 2017 I’d say progress was certainly made here. I see this as measurable by considering the change in range, scope and depth of issues and questions I receive and am able to answer/fix/address. Nonetheless, setting a benchmark is pretty difficult. In previous years I’ve written this as “be a strong engineer”, but for me at least I know that’s going to end in failure. I won’t be surprised if I end up complaining at the end of the year that I didn’t grow rapidly enough; while understandable, I think that’s something I’m less likely to berate myself for.

When I was in Singapore, I met up with a close friend, and for both of us it turned out that 2017 was a year largely centered around the pursuit of technical and career development – to the point that we struggled to think of other things to remember the year by. While growing technically is definitely something I want to do (it is target A1, after all), it shouldn’t be at the expense of all else.

A2. Present a paper on computational logic.

We had two papers in 2017 based on the work done as part of my Masters’ thesis. Things are getting a little trickier here now, as writing more will require some original extension of the work that was already done (as opposed to merely tightening up existing work). Nonetheless, I

A3. Get at least two patents in the pipeline.

I enjoy the creative parts of my job – while some of it is indeed cobbling together glue code to ensure that other pieces of code interface correctly, there are many more interesting bits involving designing and building new systems, whether as part of normal work or otherwise. These more… creative projects can be filed as patents, and setting this targets serves as encouragement to look beyond the day-to-day on my team and think more carefully about what can be improved.

Skill Development and Experiences

B1. Write 52 full-length blog-posts on this blog.

I failed this last year; in the end I wrote just 37. I have a few ideas for how I can do things differently this year to give myself a greater probability of success at this one, such as having a series of book or paper reviews, which should also get me to read more widely.

Of course a once-per-week cadence is the target here, though I’ll consider this successful regardless of the actual temporal distribution of the posts. I define full-length as requiring at least an hour of thinking and writing. I won’t assign a word limit (in case I write a poem, or some kind of “Explain Like I’m 5”) though for standard non-fiction prose I’d say it tends to be somewhere between 700 and 1500.

B2. Visit 12 distinct countries this year.

The point of this is that I’d like to spend a bit more time travelling while I still can*. Trips as part of work do certainly count. In terms of edge cases, I’ll allow Scotland, Wales and NI to each count as one (I probably wouldn’t allow it if I’d been before); trips for work count, but airside transits do not. If I ever do a mileage run (i.e. fly purely to preserve airline elite status), that doesn’t count either. There is no requirement for novelty (so Singapore does count, as would a likely trip to the US at some point).

*for health / work / other commitment reasons, not because of Brexit! Since the UK isn’t a part of Schengen I don’t think I really benefit that much from residing in the UK for this, other than proximity and less fettered imports.

B3. Walk 3,650,000 steps this year.

This is 10,000 per day and I wouldn’t have managed it last year (I hardly ever broke 10,000 – let alone an average of 10,000). Walking to work helps, but by itself that’s not enough.

This target can be accomplished by walking in circles around my room, though I hope it also encourages me to get out more and try out more different routes.

B4. Be able to sing a B4 consistently, and complete three studio recordings.

This looks like two targets, but I’m pairing them up because they are both related to singing and the alternative of giving music its own section seems a bit excessive.

B4 is a pretty high note (think the high notes in verse 2 of Journey’s Don’t Stop Believin’ – “find” in “living just to find emotion” and “night” in “hiding, somewhere in the night” are both B4s). I’m somewhat more confident of my A4s and Bb4s. I’m able to hit B4s sometimes, but I really wouldn’t go above Bb4 if I had to perform (in fact, I’d prefer to stick with A4s, even).

Obviously, there is no requirement for the B4s to be as bright or sustained as the ones in the Journey song. I’m looking more for reliability here.

The studio recording target is because I have been practicing to maintain my vocal range and to some extent accuracy, but I don’t remember when the last time I actually tried to learn a song was.

Financial Responsibility

C1. Maintain a savings rate of 50 percent or higher. This is computed by

SR = \dfrac{\text{savings} + \text{investments} + \text{pre-tax pension contribs.}}{\text{net salary} + \text{pre-tax pension contribs.} + \text{dividends} + \text{other income}}

I’ve been thinking about maxing out my pension contributions, but I’m not so keen to do that because of the Lifetime Allowance and also the lack of flexibility in that the money is tied up till I’m 55. This could make sense if I wanted to pursue an early-retirement path, but I’m not currently thinking about that.

This is a pretty ‘vanilla’ target and existed last year. It’s certainly not easy, though I wouldn’t say it’s that unreasonable either. I’m quite a fair bit above this mark in 2017. However, one thing I’m tracking for 2018 is that super-hard saving and investing can also be irresponsible; see this post on Monevator…

C2. Live at at least the UK Minimum Income Standard in 2018.

Without considering rent, for a single person that clocks in at £207.13 per week (so about £10,800 per year). That’s still a substantial bump from my expenditure last year.

It’s very easy for me to be very strict with spending, but sometimes this becomes counterproductive. I’ve spent hours agonising over a £20 decision; even if I made the right choice (which is likely to have value less than £20; assuming that paying more yields a better product/service), that’s still way below minimum (or my) wage. I’m rather well taken care of, and sometimes my monthly budgets can be eye-wateringly tight as a result.

Relationships

D1. Maintain clear and regular communications.

In 2017 I did reasonably well here, so there’s not much to say here other than to keep on keeping on. In practice this goal could probably be split into several sub-goals corresponding to people or groups of people, though that information is a little less public.