Cotton on Ret-Fin 2018

I love this recent post ( Lessons from 2018 ) from Dirk Cotton. It reminds me that I spoke to him recently and that in addition to discovering that to some minor degree we have led parallel lives, he is also as gracious and intelligent in person as he come across as in his blog posts.  His points in this particular post resonate, probably due to the parallel lives thing. Here are some thoughts.

1. Retirement Finance v Relationships

At first glance, this might seem like an odd opposition. But when I saw Dirk tease his wife in his post for only having an interest in retirement finance as his hobby when engraved knives are at stake (steak?) I realized that it was not the first time I had encountered this concept. When I met Prof. Milevsky in person, he told me that his wife teased him about his odd choice of interest in something so quantishly obscure...and this is probably the top retirement-quant on the planet.  Me? Well, a small part of me kinda sorta maybe thinks that my perseveration on retirement finance is at least a teeny tiny part of the ending of a relationship. That idea is odd from a couple directions. I mean, which is weirder here? My perseveration on ret-fin as a “hobby?” or that someone would be so put off by it.  I have to give some serious consideration to #1 when contemplating weirdness before I start to think about #2.

2. The Power and Glory of Sequence Risk

Dimitry Mindlin scoffs at sequence risk as a dominating issue (The pitfalls of sequence risk, 2016) but I might hazard a guess that Mr. Mindlin is not yet retired and does not feel the full force of no W2 income and almost certainly depleted human capital.  As Dirk points out, earlyretirementnow.com does a nice cover of the impact of sequence risk.  I am familiar with the math that ern uses which is basically the same root as the perfect withdrawal rates articulated by Suarez and Suarez in “The Perfect Withdrawal Amount: A Methodology for Creating Retirement Account Distribution Strategies” (2015).  In one of my recent posts I deconstructed their math to show that the intuition on sequence risk can be apprehended directly from just looking at the math itself.  If one were to have an initial endowment of $1 and an ending one of zero, it looks like this below which is also the “perfect withdrawal rate” or what one could spend if one were to know with perfect foresight the sequence of returns that will be realized over a planning interval. I call it the capacity to spend because that is what it is, given full hindsight at the end of life. 

Merry Christmas from RH

A little self-promotion just for fun

Re: Process 1 - Return Generation [draft]

fattailedandhappy on FIRE and 4%

Here is a site I haven't seen before (fattailedandhappy.com) and a post I just read ($1 Million Isn’t Enough).  I may have the world's smallest quibbles or extensions to this post, perhaps, but this dude is totally right-enough for me. The chart of "probability of being broke" is probably a bigger deal than even he is making out. Also note that: me? I got supper lucky and, in his framework in the conclusions, did conclusion #3.  Watch out for #4, though. earlyretirementnow.com has a good piece (not linked) on how spending retrenchment may not save you at all but I think that's what fattailed got at in sentence 2 of conclusion 4.  I have expended 1000 times as much digital ink to make the same points he makes in one short post. 

Process 1 - Return Generation [draft]

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Note: as in the previous essays, this is a draft as I hone some of this content. Also, since I view these essays as consolidating and integrating what I've learned about ret-fin so far, I will continue to add to and update this provisional latticework over time in response to new findings or errors.
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This is a continuation of a previous essay on “Five Retirement Process” which can be found here or a blog page summary here..

Process 1 – Multi-period return generation.

It was a little bit of a revelation to me when I started to realize how little I knew about financial processes at the age of 50.  I thought my MBA(finance) had taught me something and I had naively leaned on that credential confidently for decades or at least I did in a cocktail party conversation sense.  And what I knew about what I didn’t know (or didn’t know I didn’t know) wasn’t even the worst part. It’s that what I did (think I) know, I have started to now realize, can mislead.  This section of my look at retirement processes is about how I have misled myself when it comes to “return generation” over multi-period time. It is very much not about portfolio design or optimization which is another topic altogether and something I assume as a precursor or even prerequisite to this topic.  The discussion here is: what happens after you turn on an optimized “return machine.”

Five Retirement Processes - an Introduction

"Theories and models are attempts to eliminate time and its consequences, to make the world invariant, so that present and future become one. We need models and theories because of time…You can only be disappointed if you had hoped and desired. To have hoped means to have had preconceptions – models, in short – for how the world should evolve. To have had preconceptions means to have expected a particular future. To be disappointed therefore requires time, desire and a model…You can count yourself lucky if your model of yourself survives its collision with time."

– Emmanuel Derman, Models. Behaving. Badly. [2011] 

Everything changes and nothing stands still…You could not step twice into the same river.

– Heraclitus 

What little I’ve learned about retirement finance so far since 2015, the year I started my blog, tells me that there seems to be no real, perfect spending rule that will save me, except maybe with hindsight, and no such thing (serious academic papers notwithstanding) as a fixed optimal retirement solution, at least not a permanent one anyway. There is only, in the end, what I’ll call “flow.” By flow I mean that retirement is not an object or a thing or a solution or a "number." It is a process, a continuous unfolding-in-the-present of new and unstable circumstances, challenges and changes to which we need to respond anew in each one of those present moments.

Another look at the effects of time on terminal wealth in presence of volatility

I did this before a few weeks ago here.  This is the same thing with a different view. Most of the text is the same but with a different, integrated chart.

The following are mass functions from simulated, empirical frequency distributions (3000 iterations) of terminal wealth after 10 periods under two scenarios:

1. Normally distributed returns with mean = .09 and standard dev = .25 (high risk)

2. Normally distributed returns: (50%) r=.08, sd=.18, (50%) r=.035, sd=.04 (diversified)

This is a little apples and oranges, and the "normal" assumption for returns is for ease of analysis, but I wanted to see the breadth of the distributions vs the modes and try to get a general intuitive sense of likelihood related to "positive" outcomes, however that may be defined. The risk free rate of 3% (arbitrary) is the grey area. Y axis is mass, X is the terminal wealth bins. Note that there is no consumption and there are no fees, taxes, inflation, etc.  I'm just running this out for fun.

Conclusion? Multiplicative, non-ergodic, high vol processes can create vast wealth but otherwise looks like a killer if one were to happen to desire to focus on one's specific goals rather than max wealth.  Note that median terminal wealth is a fair representation of expected geometric returns over time. The mode is instructive, too, though. Take a look at where the mode goes under the two regimes. If I am going to take risk and I have a specific goal at or near t=10+, my attitude towards risk will likely be tempered a bit.

Models, Theories and Time

"Theories and models are attempts to eliminate time and its consequences, to make the world invariant, so that present and future become one. We need models and theories because of time…You can only be disappointed if you had hoped and desired. To have hoped means to have had preconceptions – models, in short – for how the world should evolve. To have had preconceptions means to have expected a particular future. To be disappointed therefore requires time, desire and a model…You can count yourself lucky if your model of yourself survives its collision with time."

– Emmanuel Derman, Models. Behaving. Badly.  [2011]

Nat Gas - part 2

The outfit Optionsellers.com got blown out of the water this month and closed due to unhedged Nat Gas futures positions via naked short calls. That happens to be almost the same trade I had on.  I had a trivial wound from that trade but it certainly was not fatal.  This type of trade is so upside down in risk-return that risk control is the only thing between the seller and Armageddon.  Those guys found Armageddon. They not only lost all the client's money but left them with a 25% debit balance owed to FC stone re the margin calls. Ouch.  I'd put the leaders on suicide watch at this point. I talked to them once a few years ago and didn't like the sound of the offer and didn't trust the principals.  Here is my trade:

I sold calls around 3.20 and exited at about 3.60 based on rules; the horizontal line was the strike and the vertical was the tenure (I thought there was no way (ha) that I'd be anywhere the strike in that timeframe). Optionsellers, on the other hand, got taken all the way and, as I understand it, could not find counterparties to close trades when vol hit 90. Man that has got to hurt.  My strategy is still intact  -- and now warier than it was before -- but at least I didn't die.  On the other hand, my guess is that the probability that over a long enough time frame that I'll get hurt is closer to 1 than it is zero so I'll probably wind down this kind of trading shortly even though the annualized returns are still hovering around 15% even after my wound.  Fanatical risk control saved me on this one, something I have been practicing for over 10 years, but even that won't be enough if I take a really hard hit at the wrong time some day.

RH Links - 11/15/2018

QUOTE OF THE DAY

Mathematics, like medieval Latin, is a medium of disputation in economics wherein those skillful in its use can subdue those who are not, independent of any substantive economic meaning. Elton McGoun

RETIREMENT FINANCE AND PLANNING

So what, we retired at the peak of the bull market? Here are seven reasons why we’re not yet worried… ERN

…it looks like I might become my very own poster child of Sequence Risk. https://earlyretirementnow.com/2018/11/05/retired-at-the-market-peak-still-not-worried/

The New Three-Legged Retirement Stool: You, You, And You, FinancialSamurai

The new three-legged retirement stool now consists of: 1) Personal pre-tax savings (You) 2) Personal after-tax savings (You) 3) Personal hustle (You)  https://www.financialsamurai.com/new-three-legged-stool-for-retirement/

Change is Coming to the Retirement Landscape, Franklin Templeton Investments

This past year we’ve seen heightened buzz in Washington DC about retirement. Issues and proposals have included debate over the definition of “fiduciary,” treatment of multiple employer retirement plans (MEPs), and how to help more Americans better save for retirement, including those saddled with student debt. We think the big takeaway is “Change is coming.” It’s no longer a question of if, but when. https://www.advisorperspectives.com/commentaries/2018/11/02/change-is-coming-to-the-retirement-landscape

How to Determine How Long Your Portfolio Could Last in Retirement, M Milevsky

Heyday contributor, author and professor of finance at York University, Dr. Moshe Milevsky, explains the mathematical equation retirees can use to calculate their portfolio longevity.  https://www.heydayretirement.com/heyday-blogs/how-to-determine-how-long-your-portfolio-could-last-in-retirement

Budgeting for Real-World Situations, Ken Steiner

Because SWPs don’t coordinate with other sources of income and are simply drawdown algorithms, their use is frequently inconsistent with a couple’s (or single individual’s) retirement goals in these real-world situations.  Since SSPs focus on spending and not withdrawals from accumulated savings, they can be tailored to address these real-world situations to better meet retirement objectives. http://howmuchcaniaffordtospendinretirement.blogspot.com/2018/11/budgeting-for-real-world-situations.html

Dirk Cotton on Mean Reversion

In Dirk's recent post Mean Reversion of Equity Returns and Retirement Planning, he addresses some of the issues related to mean reversion in markets and the impact on retirement planning. I think he hit this one on the head from my personal experience.  He says here what I've been thinking and tried unsuccessfully to explain to others:

I've read postings from other researchers who played around with mean reversion in their retirement models until they realized that any risk-reducing effects were swamped by the huge remaining retirement risks. That's one of the reasons I don't bother modeling long-term mean reversion — along with the fact that I don't know if it exists or how powerful it might be, so I'm not sure what I would model.

I believe retirement planners have little to gain by betting that mean reversion exists unless and until research resolves the issue. (The issue has been around for a long time and it could be a thousand years before we have enough data.) There is significantly more downside to incorrectly guessing there is less risk than there is to incorrectly guessing there is more risk.

This saves me a post...

Thucydides on Retirement

Actually, I cribbed these quotes from the WSJ Saturday edition but I feel justified because not so long ago I slogged for over a year through all of the History of the Peloponnesian War. And a slog it was from first page to last. But I was glad when I was done to have had the slog. The voice, by way of the translator no doubt, sounds modern and parts of of the history were more affecting than I had expected, in particular the pathos of the Sicilian campaign and the image of the defeated, captive, abandoned soldiers sweltering in pits. 

This is a stretch on making a retirement connection but what the heck:

On Planning: “Hope is an expensive commodity”

On Spending Retrenchment: “…the usual thing among men is that when they want something they will, without any reflection, leave that to hope, while they will employ the full force of reason in rejecting what they find unpalatable.”

A visualization of multiplicative return generation, terminal wealth and risk over 10 periods

I was doing this exercise for something personal but thought I'd share, assuming I have it right.  The following are frequency distributions (3000 iterations) of terminal wealth after 10 periods under two regimes:

1. Normally distributed returns (sorry) with mean = .09 and standard dev = .25 (high risk)

2. Normally distributed returns: (50%) r=.08, sd=.18, (50%) r=.035, sd=.04 (diversified)

This is a little apples and oranges but I wanted to see the breadth of the distributions vs the modes and try to get a general intuitive sense of likelihood related to "positive" outcomes, however that may be defined. The risk free rate of 3% (arbitrary) is the red dashed line. Y axis is frequency, X is the terminal wealth bins. The overflow bins on top chart are designed to put the X on the same scale in both (otherwise chart 1 is a log-normalish distribution). Note that there is no consumption and there are no fees, taxes, inflation, etc.  Just running it out. 

Conclusion? Chart 1 looks like an expensive exercise in lottery-like thinking if you happen to have any goals you want to achieve at year 10...despite it's higher mean expected return. Multiplicative, non-ergodic processes can create vast wealth but otherwise look like a killer for an otherwise modest retiree.

NG

Being short calls on natural gas futures was not my favorite thing to be this morning. Still unharmed tho.

Courage and the Annuity Boundary

The recent sell-off hasn't rattled me...yet...but it got me to thinking about something I wrote about a while back.  Managing a retirement is, to me, a "process methodology" rather than a one-time fixed event. That "process" involves management and monitoring concepts such as, among other things, keeping track of an "annuity boundary" above which (in balance-sheet wealth terms) we might not annuitize quite yet -- because the option value of not doing so might still be such that we can potentially ratchet up lifestyle more than we might have had we annuitized all wealth earlier -- and below which we might be at risk of permanently foregoing the lifestyle we might have maintained forever, given Methuselah-like DNA, had we just annuitized our consumption when we could have done so with the wealth we had when we had it.

That boundary idea above is a pretty neat concept.  But the sell off reminded me that, like other wealth management concepts, pulling the trigger on a strategy like the annuity boundary is not as simple in real life as it is on paper.  In this case, I was reminded that the speed of change in the environment we live in might be such that there could be psychological barriers to executing what we need to execute when push comes to shove in extreme circumstances.  Me? I seriously doubt that I could quickly and decisively and efficiently sell a large percentage of my net worth on short notice -- if the speed of the movement of my balance sheet towards the boundary is high -- to fund an insurance product that might or might not be the right thing to do at that exact moment.  What if I balked, paralyzed by fear and over-thinking?  Am I screwed or might I still be ok?

Purpose Of The Post 

My main goal here is not really rigorous analysis, it is to take a simple look at what would happen if my net worth were to sail through and below the annuity boundary and I then took my sweet time to make a decision ... and in the end I were to annuitize only some of my wealth with what I had left rather than me fully immunizing consumption -- with perfect timing and anticipation -- at the exact boundary when I might have looked like a genius if I had done so.  This will be a deterministic and shoot-from-the-hip analysis without full comprehensiveness because it's too much work to do otherwise and anyway I just wanted to see what the basic shape of what I am asking about looks like.

Lear and Retirement

From today's WSJ (Shakespeare’s Uncomfortable Message for Baby Boomers):

If “King Lear” is a lesson in the unexpected results of child-rearing, it also dramatizes the vicissitudes of retirement. It captures the existential abyss that can open when a once-solid identity begins to melt, and purpose gives way to purposelessness. Lear is deprived of his retinue and thrown out into a storm, reduced to his most elemental self—a “poor bare, forked animal.” We baby boomers, aging amid a technological landscape that changes at dizzying speed, must sympathize. We, too, face a storm that can make even the most successful among us feel lost and diminished.  

Lear rages at the ingratitude of his daughters and the crumbling of his regal identity, but these are ultimately stand-ins for a greater antagonist. Now on the downward curve of life, Lear faces the reality of death. Viewers and readers of the play can grasp this only when we reach the age when death, formerly hidden by the clutter of ambition and child-rearing, reveals itself.  

At that point “King Lear” counsels us to moderate our expectations and sense of entitlement with regard to our children, to accept a diminished professional identity as we age, and to be philosophical in the face of our inevitable mortality. These are profound messages but not cheerful ones, which is why “Lear” is both a great work and an unpopular one.

Vol premium looks fat today

If I had courage I would sell vol today.  Here is a (custom hack) chart I use to look at the futures options market, this time for ES mini -- something I don't usually trade -- for Nov expiration or 21 days. 

The red line is a normal distribution (density) using price, vol and tenure. The blue line is a self-rolled function of premium that approximates what I call option price "intensity" that shows me skew and opportunity to sell volatility.  Green is delta. Blue columns are the current premium at the avg of bid/ask. The vertical dotted lines are the 1 and 2 standard deviation markers of the red line. This shows me that I could get $550 for something that is at a 10 delta and more than 2 standard deviations outside a normal distribution. I think that is a good deal. Takes courage though.

Someone talk me into it. Not sure I have the courage. This should be a no-brainer but isn't.

RH Links - 10/24/2018

QUOTE OF THE DAY

"The idea that one can trace the causal connections of any events without employing a theory, or that such a theory will emerge automatically from the accumulation of a sufficient amount of facts, is sheer illusion."   -- Friedrich Hayek

RETIREMENT FINANCE AND PLANNING

Why Winging Your Retirement is a Really Bad Idea, Cordant

But here I want to highlight, in addition to the non-financial reasons, a very important financial reason to stop winging your retirement: the sequence of returns risk.  http://blog.cordantwealth.com/why-winging-your-retirement-is-a-really-bad-idea

How to Stress Test Your Financial Plan: A Look at the Key Variables, Cordant

As any engineer can tell you, sensitivity and stress testing are important tools in determining how a system can fail and therefore, determining the safe usage for that system. When it comes to your financial life, it should be no different. Stress testing your financial plan is an important exercise in determining the health of your wealth. While this a natural inclination for engineers, it can be unclear where to start. 

http://blog.cordantwealth.com/how-to-stress-test-your-financial-plan-a-look-at-the-key-variables

Contradicting Warren Buffett: When Volatility is Risk, Cordant

Most people have neither the discipline nor the timeframe of Warren Buffett. As a result, most people cannot ignore volatility as a type of risk to manage when building their investment portfolio. On this Buffett is wrong—volatility is risky for you even if it isn’t for him. [Cordant is correct but does not go far enough. Buffet (icon, yes, but let’s ignore for now his pandering on tax policy and recent history of underperformance) has nothing to do with retiree portfolio management in the sense that (a) he has infinite horizons (a point made here) and sources capital via a corporation’s access to capital markets, (b) has no consumption constraint, and (c) he effectively manages to single period (makes one myopic on volatility and sequence risk). Give him a $1M portfolio, a 5% spend rate, an age of 50, and his own skin in the retirement game and he would no doubt succeed but his rhetoric would be very different. Oh, and remember that volatility->sequence risk->permanent loss of capital in a way.  Vol is risk for retirees ]  http://blog.cordantwealth.com/contradicting-warren-buffet-when-volatility-is-risk

What is the correct benchmark for trend following?

"What is the correct benchmark for trend following?" [1]

This is the question asked by Alpha Architect here today. I've seen this kind of thing before. I love their post and their asking of the question but I find, for myself, that the answer to this question is really really easy.   For me the answer, not to drag it out, is that the proper benchmark is one's own current portfolio design and the expectations that come from that.  I know this because I have been invested in as well as rolling my own trend following systematic alt risk program for close to 10 years and that is what I do. 

I have looked at a million ways to evaluate the choice and its marginal impact. I always come back to the: (1) do nothing or keep doing the same thing (current portfolio) vs. (2) do something different (add trend following) framework.  And in that framework it's easy.  It is always do something different (add trend following) because it is additive to the do nothing scenario.   

I say that because, as a retiree, I am not an infinite-life single-period no-consumption portfolio manager. I am a many-period short-lived consuming retiree.  With kids. And goals.  Trend following, with a similar-return lower-vol vibe, provides benefits to me that I cannot get elsewhere.  I won't prove it in this post. Just google some work by Andrew Clare on trend following and perfect withdrawal rates, or a ton of work by NewFound Research on trend following*. You can even search this blog. It (trend following) is clearly additive for people like me when we use our experience from the past data (standard disclaimer on past not predicting future...).  

So, if one were to have the wherewithal to track the month over month performance of one's own portfolio in a time-weighted fashion (to account for in and outflows) and net of any trend following positions, then I think that is the proper measure. An easier way is maybe a proxy for a portfolio similar to one's own base. If that is 60/40, for example, or close, then some index/fund based on 60/40 might work, say an ETF like AOM or maybe Vanguard VSMGX or something. Maybe there are others. But you'd have to be careful to make sure things like dividend flows and issues like advisory fees are factored in.  Bon chance!


*
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Risk Ignition with Trend Following, Newfound Research 4/23/18

Can Sustainable Withdrawal Rates Be Enhanced by Trend Following? Andrew Clare 2017

Using Trend-Following Managed Futures to Increase Expected Withdrawal Rates, A Miller 2017


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[1] I didn't realize Tadas was going to pick this up in abnormalreturns.  This was pretty a pretty casual post.  There are more formal and complex ways to express this that I have not bothered with.  The base portfolio is probably assumed to be single-period mean-variance efficient on a frontier using expected forthcoming arithmetic returns.  In addition, since we are actually multi-period retirees we also probably contemplate a geometric mean frontier that anticipates the volatility effects on returns which may create inflection points in the geo frontier at higher vol so we are somewhere between min-var and inflection on that geo frontier.  Then we also probably think about the covariance and vol-reduction considerations of adding/reallocating an nth asset such as trend following and whether it nudges the frontier out, which it often does in multi-period mode.  That's why I am looking at the baseline as a benchmark and then incrementally I'm not really looking at trend following in isolation but more likely the incremental portfolio changes after the reallocation. My guess is that it is more often than not a constructive move, a point I was being casual about above.  The question is does it help my portfolio by making the change, hence the baseline as benchmark.  I can be coached on this if I am way off...

On the The Annuity Puzzle by Elm Partners

This recent article (The Annuity Puzzle: How Big is the Free Lunch Being Left on the Table? Victor Haghani and James White, Elm Partners 10/15/2018) is a pretty good, succinct (short) cover of the annuity puzzle concept. It also introduces a little bit of the consumption utility idea, something covered here quite a bit recently.  There are a lot of ways of looking at this kind of thing but I like how they cover it here and also how they keep it simple, short and readable.  I also like the fact that they make the underappreciated point "bearing one’s own longevity risk does not offer compensation in the form of a risk-premium" along with the related, obvious but also underappreciated point that access to the longevity risk pool via annuities is something that one can't roll on one's own with any type of financial engineering.

For a little more depth on the type of model that might be used to evaluate consumption utility of different strategies over a forthcoming lifetime and the impact of annuitization on lifetime utility, one might look at two things I've done this year:

1. my Wealth Depletion Time EDULC (expected discounted utility of lifetime consumption) model

2. my post on partial annuitization, consumption utility and bequest

There are a bunch of other related posts but you'll find them listed in item 1. 

A gift from a new friend...

RiversHedge just got this this weekend from a new, awesome friend. This needs to be acknowledged in an embarrassing and public way since it is so rare and appreciated. Thanks J! I'm hoping this is only the first of many...

Last week's sell off...

Ok, so we had a big sell of last week, maybe 4% depending on what you are looking at. 4% doesn't phase me when looking at the long term and considering the future dynamism of the American economy which is not going out of business any time soon.  Even looking backwards, we are still way above trend.  I mean, look at a monthly chart!  I even had the temerity last week to sell near-dated puts on the long end of treasury futures.  In a rising rate environment that's a trade by someone with a screw loose, or maybe someone complacent, or maybe more likely: confident that it'll all work out. Basically the message is, for today, "move along there is nothing to see here."

But that is not the end of the story.  The above paragraph is written by an over-confident investor.  A retiree, on the other hand, sometimes looks at it a little differently. For that person, the week was not denominated in dollars or percentages, it was denominated in time.  For me personally, for example, the move down represented something like two years of consumption.  Divided into my remaining lifespan (a totally meaningless statistic, by the way) that's about eight percent. That did get my attention.  It's been a while but every move down makes me think about portfolio longevity in the presence of consumption and the probabilities related to remaining lifespan. This is why retirement is less a single period optimal solution kind of thing and more of a process management and monitoring endeavor.

Some random comments on random longevity in modeling

I recently read a new submission to ssrn on safe withdrawal rates (Joint Effect of Random Years of Longevity and Mean Reversion in Equity Returns on the Safe Withdrawal Rate in Retirement By Donald H. Rosenthal , Ph.D.).  The author had some worthy points on nudging the modeling approach when doing Monte Carlo simulation of retirement. The main points were that adding random longevity and a mean reversion process (a) probably mirror reality a little more closely than when they are absent, and (b) when added, they hint that slightly higher spend rates might be possible.  

Losing one's mind in retirement

I knew I was losing my mind. Here is a paper from Texas Tech (The Mental Health Effects of Asset Depletion in Retirement) Colin Slabach Texas Tech University September 30, 2018

"...few have analyzed the mental health effects of running out of money during retirement. This study examines the likelihood of having mental health issues in retirement when an individual runs out of money...The result suggests that individuals who are going to run out of money two years from now have an increase in the probability of having mental health issues. However, there is an even further increase in the likelihood of mental health issues when the individual actually has actually run out of money. The larger the drop in asset level (ex. $25,000 down to below $1,000 vs $5,000 down to below $1,000) the large[r the] probability of having mental health issues." 

My new favorite paper...

Here is another paper where, having now read it, I could probably hang up the blog and take off for a while (Sustainable Retirement Income for the Socialite, the Gardener and the Uninsured, Chris Robinson and Nabil Tahani 2007).  This is the first and only (ok "only" is a little dramatic, I have seen some of this before but it sure doesn't feel like it sometimes) paper that has directly addressed the following things I find to be essential points in playing the retirement finance game:

I shoulda quit a couple years ago

I probably could have wrapped up the blog a couple years ago if I had read and posted a quote like this since it packs in a lot of my current understanding of the retirement problem. This is from "An Age-Based, Three Dimensional, Universal Distribution Model Incorporating Sequence Risk," Larry R. Frank Sr., John B. Mitchell, David M. Blanchett (2011):

Researchers have sought a single withdrawal rate that would last the retiree's entire lifetime from initial retirement to death. The authors suggest a more dynamic model should be used where the author’s prior work demonstrates that a retiree's transient state is in constant flux due primarily to market sequences. The model in this, and the authors’ prior paper, develops a methodology to monitor, evaluate and react as necessary to those transient states as well as base the model on age specific expected longevity rather than generic, ageless or unanchored, distribution periods. [emphasis added]

and, while I'm at it, this next link is an exceptionally wise and fresh post from Darrow Kirkpatrick (How Accurate Should Your Retirement Calculation Be?) with all the common sense that I should have conjured myself a long time ago.

Another possible small future tweak to the lifetime consumption utility calc

In a recent post How I might tweak my consumption utility simulator in the future, I was casually ruminating on how I might adapt my lifetime consumption utility simulation in the future to factor in some additional considerations like bequest, spend shocks and foregone optionality. I ran across another one I might want to try when reading Davidoff et al. "Annuities and Individual Welfare" (2003) They replace the period consumption term c(t) with c(t)/s(t) where s(t) allows the modeler to shape an "internal habit" to the consumption path. To quote in order to help with the definition of this idea: 

What differentiates our more general setup from prior work is that we can vary s(t) in equation (1) so that the utility function exhibits an “internal habit,” which we can then adjust to create optimal consumption trajectories that differ markedly from the usual CRRA case. The intuition behind our utility function, taken from Diamond and Mirrlees (2000), is that it is not the level of present consumption, but rather the level relative to past consumption, that matters for utility. For example, life in a studio apartment is surely more tolerable for someone used to living in such circumstances than for someone who was forced by a negative income shock to abandon a four-bedroom house. In choosing how to allocate resources across periods, “habit consumers” trade off immediate gratification from consumption not only against a lifetime budget constraint, but also against the effects of consumption early in life on the standard of living later in life. Following Diamond and Mirrlees (2000), we model the evolution of the habit as follows:

[alpha] is the parameter that governs the speed of adjustment of the habit level. When [alpha] is zero, the habit is constant and we are back in the additively separable case. As [alpha] approaches infinity, present habit approaches last period’s consumption. 

A RiversHedge Reading List

I have a bad habit of buying the same book twice or printing the same article three times. Wasteful. So I decided to catalog what I have on hand. Then I thought this might be of some plausible use to others so I added the list here.  This excludes what I have lost or thrown away and items read before I kept what I printed. Obviously it ignores what I've read online but have not printed. This is only related to RH work (retirement, annuities, asset allocation, pensions, options math, econ, systematic trading, etc) so it excludes things like casual reading and literature.

* is an "editor's choice" selection

How I might tweak my consumption utility simulator in the future

I wanted to look, in this post, at what might be missing in my lifetime consumption utility simulator. Specifically I wanted to anticipate how I might adjust it if I were to think more carefully about the presence of things like annuities, bequest motives, spend shocks such as long term care, the need to inter-temporally shift consumption in the future, support a desire for optionality on future consumption increases and so forth. None of that is "answered" here in this post. I just wanted to think about how I might deal with it at some point. The goal is not to educate a reader, by the way, it is rather to commit to "paper" what I think I'm trying to do for myself. I find that writing something down makes me think more carefully which I can then use in the future.

The Basic Consumption Utility Function

In my attempt to wing a consumption utility simulator earlier this year, I tailored the core value function, coded in R, to be like Case A in Yaari's 1965 paper. That was the case with what he called Fisher style utility (with constraints) without insurance (annuity) markets.  His Case A function -- without much explanation of terms except that Tbar is random life, V is an expected discounted utility of lifetime consumption, c is consumption, g is utility of consumption and alpha is a subjective discount -- looked like this:

Yaari case A (eq 13)

My amateur value function, the one I try to simulate, looks like this below which is more or less the same thing as above, given my non-economist efforts, except it's discrete and simulated...if I understood things right...which is a big if because it's hard for me to read calculus and impossible for me to read the related differential equations. Let's just say I made a good faith effort:

RH EDULC value function

This does a journeyman's job for what I am trying to do personally and works well enough for evaluating basic consumption utility. The terms and sim structure can be understood here.

In a parallel universe...

In a parallel universe this moment has always existed and will continue to exist into an infinite future. That idea pleases me.

maybe 10-11 years ago

Also, in case any reader is wondering, this is why I "retired" early. There was absolutely nothing related to the FIRE movement whatsoever about my choice. I had been taking full time (24 hours a day solo, 5 days a week) care of these children of mine for many years before 2008.  When I (we) went through a move and a divorce in '08, given the presence of a constructively involved co-parent who also either traveled or worked intensely, I felt compelled to to maintain continuity of care for them (i.e., retire) for a while to keep young minds sane and focused.  That I was 50 at the time was irrelevant (except that I now know the risk...hence, the blog). One of the most beautiful sentences I've ever heard in life was a now-adult child say to me: "I know what you did for us..."

Some of my influences...for now

Being neither academic nor practitioner, this blog has never been a "teacher" blog. My goal has never really been to explain or educate as such since I know so little and I feel like I know even less as I learn what I don't know.  Rather, I am a student and the purpose of the blog is to report from class on what I am imperfectly learning...didactic, perhaps, only in the reporting. But learn I do, so...

The following is an adaptation of an email I sent to someone in response to a question on "which retirement researcher/practitioner do you think influenced your thinking most?" In real life, the question and answer are more process than snapshot but I took at shot at answering the question as a snapshot.  I've made some edits and additions to the email in this post as well as some likely and accidental omissions.  This is not in rank order, just an impressionistic melange:

Perfect Withdrawal Rates with normal and fat-tailed return distributions

Point of the Post

In this post I am taking a non-rigorous, non-exhaustive peek at what  happens to a perfect withdrawal rate (PWR) distribution when generated with either a normal or a fat-tailed return distribution where I have coerced the first and second moments to match.  The goal is mostly just to do it as a placeholder for something I want to try later...but also to see what happens visually to the PWR distribution as well as to get a first pass look at the scale of the effect on the 5th or 10th percentile PWR for quasi-reasonable but fake assumptions.

Picerno (and RH) on High Yield

James Picerno has a blog post out on Is It Time To Start Taking Profits In Junk Bonds? and I think his conclusions are correct, conclusions which can be summed up by his final comment:

...the good times may roll on for the high-yield market. But for anyone who respects probabilities, the odds don’t look especially favorable. After all, the problem with holding assets that are priced for perfection is that we live (and invest) in an imperfect world.

On the other hand the discussion of high yield reminded me of two things:

Revisiting Perfect Withdrawal Rates But with Variable Duration

Perfect Withdrawal rates

Over the last 3 or 4 years a number of different sources[1] have discussed a way of viewing retirement consumption analysis by way of "perfect" or "maximum" withdrawal rates (PWR).  Quoting Suarez 2015: PWRs are the "constant amount that will draw the account down to the desired final balance if the investment account provides...any...particular sequence of annual returns." i.e., it is the rate in any of some number of parallel simulated universes that draws an account down to zero (or a bequest level) at the end of the duration of the analysis.  If one were to simulate 10000 parallel universes, one would thus have a distribution of 10000 constant "perfect" withdrawal rates for each parallel world.  Constant is a debatable proposition but for first pass examination of retirement processes (not last mile real planning) it is ok enough.

The distribution, then, can be examined by retirees and planners for making a joint "allocation and spending" choice.  It is, in effect, no more and no less than inside-out monte carlo simulation except that the fail rate is set to zero over the interval of interest and spend rates are allowed to vary to make it work.  Looking at the left side of the distribution (the lower spend rates, at or below which were the rates that worked in really bad situations) is interesting. Looking at the right is not or rather is an elegant problem to have.   The cumulative percentile (say 5% or 10%) of spend rates that worked in the worst of situations is roughly equivalent to a fail rate analysis except that it is, in my opinion, a wee bit more transparent and conversation-worthy.

Optimal Spend Rates and Casual, Borrowed Backward Induction

The Point of the Post

I was contemplating, the other day, a project that would use backward induction and stochastic dynamic programming in order to visualize approximate optimal spend rates at different ages.  I wanted to try something like this because the form of analysis is powerful and efficient, the method is economically rigorous, consumption is a big deal in a multi-period retirement decumulation setting, and I had done it once before, on asset allocation at that time, in a post from January 2017, though that now seems like a million years ago.  I paused a long while on this idea for several reasons:

1. This, surprisingly to me, is becoming less and less trivial but my aging, decaying eyes are starting to limit what I can and want to do in terms of chasing down the financial economics of retirement.  My ability to sit and stare at a screen of code for hours or days or weeks -- which is what it would take for this idea -- is much more constrained than it was even 5 years ago.  These are the type of wages paid for entering late middle age.

2. I could not figure out how to make the proper focus on spend rates.  The lowest spend rate will always have the highest probability of success which will therefore always make self-denial the dominant strategy for success, something that is both common sense and ridiculous at the same time, and, not unrelatedly,

3. If using utility to evaluate spend rates or lifetime consumption -- so that they do not tend towards self denial -- makes more sense, then I have no idea how to chain things backward.  In my prior attempt it was relatively trivial (not really, technically, but conceptually) to chain probabilities backward.  Chaining utility makes no sense.

Optimized spend rates by age and allocation in a lifecycle-decumulation utility model

The Point of the Post

This post is a continuation of several past posts where I have been using (trying to shake out) a lifecycle utility model (decumulation focus only) [1] that includes a wealth depletion framework -- i.e., where there is a time interval in the late lifecycle when non-pensionized wealth runs out and consumption snaps to available income -- to evaluate "optimal spend rates." The optimization is done by evaluating a value function (expected discounted utility of lifetime consumption) that is calculated, based on a simulation process, across different spend rates, range of ages, different risk allocations and different coefficients of risk aversion. The goal is to see what happens to optimized spend rates at different ages and how it might be influenced by asset allocation.  Framed as a question it might look like this:

What kind of optimized consumption does $1M in purchasing power (age 60 baseline) buy at different ages, and for different allocations to risk, in a lifecycle/decumulation utilility model that uses a wealth depletion time framework?

As in past posts the assumptions and parameters are illustrative rather than realistic and are for self learning rather than suggesting or recommending strategies and plans of action.  Also, since this uses a utility framework, you'd have to buy into that, which I'm not sure I do even though I am here doing it.

My 2 cents on buybacks

Talk of buybacks has been in the the air lately on twitter, blogs, papers, etc.  I get the basics, Modigliani and all. Dividends, buyback, investment (projects) are what the company does with surplus.  I have no problem with this and I certainly agree with the recent pushback by the fin-twit crowd on the intellectual vacuousness, if not intellectual adolescence, of the anti-buyback crowd.

I have no real comment on dividends or buybacks as such, though I do happen to enjoy receiving dividends for my own reasons.  But let's call all three methods more or less equivalent and worthy and defensible propositions that have some variation on taxation and efficiency.  Except, I guess, sometimes for the third...

I point out investment (projects) in particular because supposedly that is what is being "starved" according to the critics with ill effects due to the starvation, I suppose they'd say, on employment and income inequality. I also point it out because I have seen no small number of "projects" with my own eyes.  As a former management consultant with a global consulting firm, I have been in or near many "projects" over the years.  And here's the deal.  On all but a few, all of the people should have been fired and the project shut down given the foolishness of the plan, the incoherence, the waste, the inefficiency, the errors, the weak management... I get it. It's a portfolio concept and some have to fail. But there was a lot of fail.

Maybe this makes "their" point about employment and certainly I never wanted to get fired for being on one of these crappy projects.  But now, as an investor, the idea that a corporation, on which I have some small claim, would -- instead of paying out my surplus in a dividend or buy back some or all of my shares or put it into the very very best of growth opportunities...for me -- pour it into one of these ill advised and poorly managed projects? It's a form of thievery. Or at least it's a form of burning money in a greasy pit. I'd take a buyback any day. There are plenty of productive things I could do with the cash.

Endowments, Retirement and Spending

I was recently following a twitter thread on a question about endowment targets.  The proximal question at the top of the thread was "Is 4% real a reasonable target for an endowment?" I didn't jump in on that because (a) I am a fin-twit coward and newbie, and (b) at first I was confused about whether they were talking about returns or spend rates, but it did get me thinking.  My first thought was that it doesn't matter whether it was spending or returns because those issues are necessarily and importantly intertwined (a point often forgotten or ignored) and the second thought was that they were asking the same question about endowments that retirees do when they talk about sustainability of their retirement portfolios over time.

Of course there are differences.  Taxation is different, endowments are generally perpetual, there is often a dedicated and experienced staff, and, importantly, they have contribution inflows (that's what I need! gofundme...). In addition I guess there are some other soft issues like politics to consider. No one (yet) is asking me to divest from energy or tobacco.

Retirement as Jazz

From the Flaw of Averages by Sam Savage:

"The form of reasoning based on "subjective degrees of believe about the uncertain future" is like improvised jazz, in which the musicians commit to their own notes in advance of knowing with certainty what the others are going to play. If there were a field of statistics to deal with black swans, it would be this improvisational form."

"...but let's not forget that many jazz musicians have had classical training..." 

A 2nd attempt at viewing retirement choice as a type of real option - preliminary

Summary

This is an exploration with untested and un-reality-checked ideas on "retirement as a real option." This is just for fun and self-learning and the conclusions are going to be thin. Skepticism is warranted.

What feedback I do have from this effort looks a little similar to other work I've seen that tells me that, up to a point, holding a risky portfolio has some option value that is accretive to undefined bequest plans and maybe to an undefined and unscheduled decision on when (what age) to eliminate risk in favor of something else...like lifetime income. But that is a pretty indirect inference. And also well known already.

The Point of this Post

In a past post I tried to look at retirement as a "real option" by using an annuity boundary as a strike price. This was in order to do (via simulation, not Black Scholes) an amateur reproduction of some work by smarter ret-fin guys than me so that I could learn something new, especially about the benefits of not annuitizing "just yet."  In this post I wanted to look at the idea again but now without the annuity boundary and this time with some variation in spend rates and return assumptions. In addition I wanted to also try to discount the intrinsic-value results at expiration with a conditional survival probability.  The goal here, by the way, is "self-learning" and just to "see what it looks like."  At this point all of this is pure play and I'm not sure if my assumptions and approach are on solid enough ground yet to make any conclusions if they are even meaningfully interpretable in the first place. More on that later.

The other reason I'm here on this is that so many of my posts seem to focus on the negative: sequence risk, ruin, wealth depletion, disutility, mortality, etc. Dark stuff.  It's easy (for me) to forget that one of the many reasons to hold a risky portfolio -- and not 100% bonds or life income annuities or TIPS ladders with a side portfolio -- is that it represents a big upside option above and beyond providing what it is supposed to provide: reasonable probabilities of funding consumption. It is an option to get access to additional lifestyle growth, bequest motives, etc. that might otherwise be foregone.  That means the option has value, up to a point, in the context of finite, random life.  This is a second attempt to try to see and understand the process and "the point." My guess is that it'll take a while and more than this preliminary and flawed post for me to get there.

Spend Rates by Age, Wealth Level, and Risk Aversion in a Lifecycle Utility Model

Summary 

• Wealth looks like it matters in determining the spend rate optima in the analysis but as far as I can tell only indirectly in the sense that lower levels of wealth support lower absolute dollar spend rates and those spend rates present less of a "cliff" over available income when wealth is depleted.  There is a lower height to fall from when consumption depletes wealth and then drops to available income. That means higher spend rates in a low wealth situation are not penalized as severely (in the utility math) as they would be for larger wealth and bigger falls.  

• Optimal spend rates tend to go up with age, though this is already known.  But in this model, it appears as if the impact of the previous point is accelerated or accentuated at later ages as longevity probabilities come in a bit.   

• Risk aversion, in this model, has a significant impact on optimal spend rates as well as the rate at which spend-rates change for changes in wealth and age in the presence of pensionized income like social security or annuities. The means and methods of measuring risk aversion in real life are beyond me. Contemplating the idea of the stability of risk aversion over time makes me woozy.  

The Point of the Post

The goal of this post is to use a lifecycle utility model [1] -- one that anticipates a "wealth depletion time" i.e., a time interval in the late lifecycle when non-pensionized wealth runs out and consumption snaps to available income -- to evaluate "optimal spend rates" by optimizing a value function (expected discounted utility of lifetime consumption) that is calculated across different spend rates, wealth levels, a range of ages, and different coefficients of risk aversion.

This exploration is neither sufficiently rigorous nor exhaustive enough to make hard conclusions or recommendations about spend rates. There are too many dials to turn...and one has to accept the model as meaningful in the first place. The exploration, rather, is intended to help me see the general shape of lifetime consumption utility in terms of spend rates and in graphic form.  It also helps me shake out the software one more time. 

Wealth and spend rates in a lifecycle utility model - preliminary

This is a quick, preliminary look at how the lifecycle utility model I've been working with lately might handle changes in wealth for difference spend rates. This post uses the WDT model mentioned in the past (link explains how the value function works) and a set of generic quick-look assumptions[1].  As a quick, informal pass, there are limits to what I can conclude but let's try this:

A quick peek at consumption utility with a deferred annuity

SUMMARY 

• [note -- this is a casual and mostly non-rigorous post]  

• It's been well known before I ever came along, that risk pooling can enhance consumption utility by hedging out longevity risk and shifting it to the pool or insurer.  This post is doing a quick drive-by to see how much spending might be nudged under some narrow, artificial and simplified assumptions using my lifecycle model with a deferred annuity (DIA).  

• Last year I estimated, in another casual post, that if one were to try to keep risk the same (i.e., holding ruin risk constant in a ruin-risk-based simulator at that time) when hedging out a minimal level of age 85+ consumption with a DIA, one could increase spending ~14% (the way I did it then). This time, using the lifecycle utility model I recently built, and hedging out some of age 80+ consumption with a nominal DIA representing a "consumption floor," one can, under some generic, arbitrary, and very simplified assumptions, perhaps increase spending between 10-20% (or more) while keeping "discounted lifetime consumption utility" the same or higher. This is apples to oranges, of course, and probably optimistic, but the general magnitude still makes sense and is consistent with the results from last year.  

THE POINT OF THE POST

This is a drive-by look-see to see what happens in a lifecycle utility model when some portion of wealth is allocated up front to a DIA intended to support very late age (if any) consumption.  I had done something similar last year with a standard Monte Carlos sim and this question, reposed to myself this year, was a chance for me to add some code to my WDT-utility model to be used for working with nominal streams of income in addition to what I already had. In this case I was thinking about DIAs or pensions.  In this post, I'm taking one tiny set of shoot-from-the-hip parameters and taking a quick shot to see what happens.  I realize that this kind of DIA analysis has been done before quite often. I just wanted to shake out part of my model for some new features and to do a superficial validation of the spend increase benefits of hedging longevity that I had tried to do last year.

Hindsight 12 - No Math Will Save Me or The Most Important Equation

When I first saw my retirement[1] risk a few years back I was a little shocked. I thought, shortly thereafter, that trying to understand retirement finance would help. Which it did...quite a bit.  But the real conclusion, over more than a few years, is that it is not really about the math. And this should not have been shocking.  It is about everything else, too.  Since this blog leans on retirement finance so often, let's set up "the most important equation" like this:

RS = f(W, A, Ce, U, B, H, Z, MPIF, O)

RS: Retirement success

is a function of...

RH Links - 8/14/18

QUOTE OF THE DAY

Think, when reading the following, of a constant inflation-adjusted spend rate, set at the beginning of retirement, and then never revisited...

“Life is a process of becoming, a combination of states we have to go through. Where people fail is that they wish to elect a state and remain in it. This is a kind of death.” Anais Nin 

RETIREMENT FINANCE AND PLANNING

How screwed are you when it’s time to retire? Allison Schrager @ quartz.com

Saving enough, managing investment risk, and knowing how much you can spend in retirement is hard. https://qz.com/1335391/how-screwed-are-you-when-its-time-to-retire/

Divorce Very Bad for Retirement Finances, Boston College

When a marriage ends in divorce, there are no fewer than seven ways that it could damage a person’s finances…for most people who divorce, their retirement finances will take a hit. The good news is that divorce rates, having peaked with the baby boom generation, are now in decline. http://squaredawayblog.bc.edu/squared-away/divorce-very-bad-for-retirement-finances/

New research on loss aversion is causing me to think deeper - Worth a closer look, Mark Rzepczynski

Now we have research that calls into question loss aversion as the core reason for these effects both from a theoretical and empirical point of view. There is clear evidence that contradicts loss aversion, but it has either been dismissed or ignored. Loss aversion is a description of behavior and not an explanation of behavior. This research is not offering an alternative to loss aversion but rather a commentary on its usefulness and explanatory power. https://mrzepczynski.blogspot.com/2018/08/new-research-on-loss-aversion-is.html

Why the Most Important Idea in Behavioral Decision-Making Is a Fallacy, Scientific American

as documented in a recent critical review of loss aversion by Derek Rucker of Northwestern University and myself, published in the Journal of Consumer Psychology, loss aversion is essentially a fallacy. That is, there is no general cognitive bias that leads people to avoid losses more vigorously than to pursue gains. Contrary to claims based on loss aversion, price increases (ie, losses for consumers) do not impact consumer behavior more than price decreases (ie, gains for consumers).  [wait til they retire…] https://blogs.scientificamerican.com/observations/why-the-most-important-idea-in-behavioral-decision-making-is-a-fallacy/ 

Asset Allocation and Spend Rates in a Lifecycle (WDT) Utility Model

SUMMARY

• Over some pretty broad, middle of the road asset-allocation ranges and moderate spend rates, spending control looks like it trumps asset allocation as a lever for lifetime consumption utility. This is more evident as the concept of risk aversion rises. My take-away from this is that once a consumption plan has been rationalized, asset allocation -- over a broad range from 30-40% to 80-100% to a risk asset -- is of less importance than spending control. 

• Risk aversion, if it is considered a valid analytical tool, has a significant effect on the results and suggests that spending control is an important tool in the presence of high risk aversion.  High aversion seems to command lower spend rates.

• Random lifetime, when it is modeled as "literally random life" as opposed to just a vector of conditional survival probabilities for a given age, makes the simulation unstable except at very high iterations within the sim. My naive take-away from this is that in real life, the individual path one is dealt in terms of longevity matters a lot and may trump both spending and asset allocation as a significant factor for consumption utility over the life-cycle.  In the absence of "pensionized wealth" this might be considered a vote for conservatism in spend rates given the first and second bullets. ...or maybe a vote for pensionized wealth.

• Volatility reduction, all else equal, appears to have positive effects on consumption utility and would imply support for higher (constant) spend rates.  Alternatively, looking at it from another perspective, parameter estimation uncertainty in constructing efficient portfolios (e.g., estimation of parameters such as returns, vol, covariance, etc) would imply some need to think carefully about conservatism in planned spend rates.  It is not shown here but it has been shown elsewhere (e.g., Claire 2017, Hoffstein 2018) that allocations to alternative risk premia and anomalies like trend following, given the effects on the volatility of portfolio returns, is accretive to retirement portfolios that are seeking higher consumption rates.  

• The very lowest allocations to portfolio risk, counter-intuitively to some retirees, appear to be the least productive of lifetime consumption utility and might reasonably be avoided by those with moderate to low risk aversion. The exception, of course, might be for those in the most fearful "retirement crouch" but I have not looked at extreme risk aversion yet. When the policy for how the model deals with cases of depletion before income starts is made more assertive, high spend rates with high allocations to risk are much more heavily penalized (not shown) and would be avoided as well.  That policy change may be explored in a follow-up post. 

THE POINT OF THE POST

The goal of this post is to use a lifecycle utility model -- one that anticipates a wealth depletion time i.e., a time interval in the late lifecycle when non-pensionized wealth runs out and consumption snaps to available income -- to evaluate the expected discounted utility of lifetime consumption given various choices in asset allocation and (constant) spend rates.  This exploration is not sufficiently rigorous to make hard conclusions about allocation optima or, for that matter, specific recommendations about spending. The exploration, rather, is intended to help me see the general shape of lifetime consumption utility in visual terms and to get some sense on how it "moves" in response to changes in risk aversion or volatility assumptions. 

Case for social cooperation among retirees with high vol strategies?

If:

(1) the long-horizon time-averaged geometric return for an individual investor with volatile returns is said to be something like E(g) = µ - σ²/2 (see any finance textbook; long horizon is technically infinity I think but maybe less in practice), and 

(2) the presence of consumption over "multiple periods" in retirement (in the presence of volatile returns) creates the potential for sequence risk above and beyond (or due to?) the drift term and thus the potential for whatever you want to call it: higher ruin risk and/or lower consumption utility due to higher incidence of wealth depletion, etc., and

(3) the mathematics of cooperation for “N cooperators” implies that the “spurious drift term is [- σ²/2N] so that the time-average growth approaches expectation-value growth for large N” ^[1]

Then: 

Note on my WDT model

Fwiw, I consolidated my "wealth depletion time" model and links into this page here which is now a tab at the top of the blog:

• A WDT Model

so that I would:

- not lose track of it

- consolidate multiple posts and links

- give it some extra emphasis since it is integrative of a lot of my learning

- correct some errors of content, grammar and math

I kept losing track of the various posts and related commentary. Now I have one place to go.

RH Links - 8/2/2018

QUOTE OF THE DAY

...beware of incoherence that passes itself off as complexity.  Dani Rodrik

RETIREMENT FINANCE AND PLANNING

Are SUVs Ruining Retirement Savings? Ben Carlson

if you’re one of the many people who are woefully unprepared for retirement or any of your other saving goals, a good place to start would be cutting back on any unnecessary spending on transportation. http://awealthofcommonsense.com/2018/07/are-suvs-ruining-retirement-savings/

Target-Date Funds Aren’t the Retirement Bull’s-Eye, Nir Kaissar

target-date funds are no cure-all. One obvious defect is fees. I counted 227 retirement share class target-date funds with $100 million or more in net assets. Their average expense ratio is 0.67 percent a year, and their asset-weighted average expense ratio — which accounts for the size of the funds — is 0.58 percent…It’s also not clear why retirement savers should own more bonds over time. People are living longer and a bond-heavy portfolio raises the risk of running out of money. And that isn’t the only risk…The combination of those factors — high fees and the potential for unlucky timing and misuse — could easily add up to 1 percent to 2 percent a year in lower returns, costing retirement savers hundreds of thousands of dollars over the course of a career.   https://www.bloomberg.com/view/articles/2018-07-18/target-date-funds-aren-t-the-retirement-bull-s-eye

The Unique Retirement Issues Facing Women, Swedroe

Women face at least 12 unique challenges from financial and life circumstances related to long-term retirement planning. … Specifically, women: 1. Earn less.  2. Live longer.  3. Have fewer years of earned income. 4. Start investing later… https://www.advisorperspectives.com/articles/2018/07/30/the-unique-retirement-issues-facing-women

Why is Retirement Harder than Saving for Retirement? (SWR Series Part 27),  ERN

ust because saving for retirement is relatively simple it doesn’t mean we can just extrapolate that simplicity to the withdrawals during retirement. And that’s what today’s post is about: I like to go through some of the fundamental factors that make withdrawing money more complicated than saving for retirement. Think of this as an introduction to the SWR Series that I would have written back then if I had known what I know now!  https://earlyretirementnow.com/2018/07/25/why-is-retirement-harder-than-saving-for-retirement-swr-series-part-27/

On sloppiness v accountability

I was reading an article on golf in the weekend version of the WSJ and ran across this quote:

"I don't see the point of hitting a golf shot in practice without being accountable, given that every shot in competition, you're accountable in a round...as a behavior, it doesn't make sense to me."

This made me think of two things.  First, I was thinking that I generally feel like I am often in practice mode here at RH. I cut corners, I estimate, I get sloppy, I hack, I fudge, I elide, I leap to conclusions. etc etc. 

Then, the other thought I have is that it doesn't matter because the one thing that I am here is "accountable." For all the sloppiness and elisions there is no point at which I am not 100% accountable to my family and my future self.  The stakes and consequences for understanding what I try to figure out here could not be higher.   The work I do here may not matter to the world at large but it matters one hell of a lot to a few real people here in south Florida.

Some thoughts on modeling complexity

First of all, I'm making this up.  Second, this seems to be true enough to at least me after three years of doing retirement modeling and simulation. Let me try to dilate on the letter-points along my fake curve.

Testing last year's naive intuition on consumption utility with a lifetime utility model

Last year in this post (My Own Private Idaho Of Utility - A Case Study In Spending Control) --before I had figured out the idea of multi-period lifetime consumption utility modeling -- I had made a naive stab at creating my own single period consumption utility formula just for fun.  It was ugly and un-informed and more or less tongue-in-cheek. It looked like this: U(Ct) = 7e-11*x^3 -6.85e-06*x^2+.1396x-565.56 ...for reasons I can't recall but could if I re-read my own post.  The basic idea was that I wanted a hump-shaped function because I figured that spending 35k has utility and spending 36k has slightly higher utility and spending 37k has even higher but diminishing utility, BUT spending 100k might ruin you and might be wasteful to boot. The implication for me at the time was that consumption utility (if perpetuated over time) would not really rise as more is spent, it would go down at some critical point.  The typical formulas for consumption utility, however, like CRRA or log utility have monotonically rising and diminishing utility behavior so I made up a new formula (above) to get the hump.   I wanted:

A Weak Defense of the Constant Spend Assumption in Retirement Modeling

THE CHART

Since I have often ripped on constant spending as an unnecessary and foolishly high risk idea[1], let me try to explain my chart to set up the post...

Book Mention -- Willful Ignorance

Just finished Willful Ignorance, the Mismeasure of Uncertainty by Herbert I Weisberg, cr 2014, 452 pages.  This is not a review, just a mention, but it was, in the end, gladly read. The book can be roughly characterized as going to school on the history, philosophy, meaning(s), lacunae, and implications of our modern conception of probability theory.  It was also written by a neighbor of one of my retirement-quant interlocutors, Francois Gadenne. From Amazon's description (I am not an affiliate, btw):

Through a series of colorful stories about great thinkers and the problems they chose to solve, the author traces the historical evolution of probability and explains how statistical methods have helped to propel scientific research. However, the past success of statistics has depended on vast, deliberate simplifications amounting to willful ignorance, and this very success now threatens future advances in medicine, the social sciences, and other fields.Limitations of existing methods result in frequent reversals of scientific findings and recommendations, to the consternation of both scientists and the lay public.

Willful Ignorance: The Mismeasure of Uncertainty exposes the fallacy of regarding probability as the full measure of our uncertainty. The book explains how statistical methodology,though enormously productive and influential over the past century,is approaching a crisis. The deep and troubling divide between qualitative and quantitative modes of research, and between research and practice, are reflections of this underlying problem.The author outlines a path toward the re-engineering of data analysis to help close these gaps and accelerate scientific discovery. 

Or maybe it is pithier and more efficient to quote Mr Weisberg himself:

"...probability is not destiny"

But you'll have to read to find out why.

Alpha Architect on Investment Factors in Bonds

In this recent post, AlphaArchitect reports on efforts to deconstruct factor influence on corp bonds. To quote: "The presence of historical prices impacting future returns, i.e., momentum, has been well researched in the equity market, which we’ve covered here. We’ve also closely looked at momentum in bond markets here, here, and here. What the Bali, Subrahmanyam, & Wen are exploring is whether momentum shows up in the corporate bond market, and if so where?"

The conclusions are broader than what I put into this post but this point was interesting:

1. Some of the most interesting conclusions of this paper came in the robustness tests finding the sources of STR, MOM, and LTR.  When digging deeper into short-term reversals in the corporate bond market the researches found that STR disappears in the most liquid bonds and was strongest in the least liquid section of the bond market.  This indicates that there is a liquidity-based explanation for short-term reversals.  The researchers also found that the momentum effect was strongest in the highest default/credit risk bonds, while the factor becomes statistically insignificant in the lowest default/ credit risk section of the market.  In addition to those findings, they also found that momentum is strongest in times of economic downturns and periods of high default risk.  In fact, the impact of the financial crisis was so strong that when the financial crisis is excluded from the data the MOM factor becomes statistically insignificant.  Much the same as momentum the long-term reversal factor was strongest in the highest credit risk and highest default risk bonds.  In fact, the researchers found that credit rating downgrades are an important source of the long-term reversal effect.

While I don't have the research chops to critique, comment, or replicate, I find the feedback from the reported research to at least be confirmatory.  I can say that because:

1. The single biggest trade profit I ever received over an entire lifetime by way of an active time-delimited trading position made with existing capital was in high yield at the depths of the financial crisis in Q1 2009, something that was held for approximately 24 months thereafter.  While the at-the-time 25 point spread seems like a no-brainer in retrospect looking from our current perch in 2018, I will admit that at the time it took some courage to un-freeze from my death-crouch and commit meaningful and steadfast capital

2. It's been a while since I have done the analysis but since I trend-trade across credit risk categories I once took a look at what works best over what timeframe.  High yield etfs over 12-18 months won.  My take away was that they had equity-like behavior and high beta so I was not all that surprised.