How far?

Message in a bottle

I didn't know my father well. I was seven when he had his third and final heart attack in 1965. He was 47.  Here are some of the few things that come from my direct memory:

- bald
- had a fedora on the top closet shelf and long heavy overcoats, some with a fur collar
- liked shish-kebobs
- had some big-shot job at Prudential on highway 12
- liked his Cadillacs with fins
- loved to fish
- terrible cologne
- most of the time leave him alone but solid otherwise (like me)
- drove us all on an epic western road trip in ~1963
- turned purple some night in '65; wasn't there in the morning

Comments on the Floor Leverage Rule

I was sent a link to a paper from the Stanford Institute for Economic Policy Research by a friend the other day. 

SIEPR Discussion Paper No.13-013
The Floor-Leverage Rule for Retirement
By Jason S. Scott and John G. Watson
Stanford Institute for Economic Policy Research
2013

The abstract is thus:

The Floor-Leverage Rule is a spending and investment strategy designed for retirees that can tolerate investment risk, but insist on sustainable spending. The rule calls for purchasing a spending guarantee with 85% of wealth and investing the remaining 15% in equities with 3x leverage. Surprisingly, this leverage is a tool for managing risk. We compare our rule to some popular strategies, illustrate it for a variety of retiree preferences, and evaluate its historical performance.

The following is neither comprehensive nor exhaustive, just a riff based on some thoughts as I read my friends email.

My first kinda botched attempt at backward inducting spending via SDP

Preliminaries and Intro

The purpose for this post is to write up my attempt to try to use an "optimal control theory" technique (e.g., stochastic dynamic programming and backward induction - BI/SDP) to evaluate lifecycle  spending choice (or the decumulation half, anyway).  I had tried this BI/SDP technique once before with "asset allocation choice" when I tried a couple years ago, with a modestly successful outcome, to replicate Gordon Irlam's description of the method in his article Portfolio Size Matters [2014] article.

The goal here is not replication (I'm not sure I've actually ever seen this kind of BI thing done before for spending) nor is the goal necessarily usable functional results. No, I am mostly just trying to: 1) build new skills or stretch old ones, 2) see if I can do it at all, and 3) maybe provide another avenue of confirmation for the shape of spend rates in the mid-to-late age retirement process.   Since the method is considered to be quantitatively and intellectually robust in some circles of academic econ, it is probably therefore worthy in my mind of some examination. It can then be placed in the toolbox that I have for "triangulating" around my understanding of the retirement spending problem.

Twitter broke my pinned thread

"Todo dia um leão, vovô." from a twitter follower: "every day a lion, Grandpa"

Twitter is the new censor (and jester) of the kingdom.  I had a "pinned tweet" that put myself out there a bit and they broke the thread entirely.  I figured it was going to be there for a while but I keep forgetting that Twitter is a "gaming platform" and they own the game.

Just for fun here is the original thread to the extent that I can reconstruct it. Most of this is redundant with my page above with my fitness stuff as well as a previous post on the same topic. I just felt obligated to rebuild what Twitter broke apart. Edits added for clarity and flow.

-----

see also:

 - some late-age core work 

 - fitness post-60 page 

-----

1/  My Path

I burned myself to ash in a crucible of my own making, with 11 years of dead-walking, to find my own path mentally and physically. That’s a really long time. Now? Examples of fitness-follows I use at 61 to stay alive:

@TheForeverAlpha
@Mangan150
@_CynthiaThurlow
@jerryteixeira

2/ The Game…

Fast: consistently, not obsessively >=18:6
Eat: high protein, low other. Count calories, nix alcohol
Lift: often, progressively, with ROM. Recover
Balance: hormones, sleep, stress
Excellence: attempt it always and everywhere, with purpose

all that = hope for 60+ crowd

Results [maybe Q3 2019]:

/3 Some other follows:

@allicovington

@Mattvjohnson

@Chris_DFB 

@HynesDm

@tellquint

@DanielKellyTRT

@FitzgeraldSTA

@IngriPauline

@ClintShelton5

@SBakerMD

@FKetogenics

@ThePrimalMan

@anymanfitness

@jackdcoulson

@MasculineDesign

@Rob_NBF

@Matt_S_Stephens

@AJA_Cortes

4/  Why Those Follows?

It’s not exactly that I do what they recommend or buy their programs, it’s that they seem to be the closest confirmation of what I figured out long before I even knew what a Tweet was a year or two ago.

/5 Some Side Benefits

To round out thread, some of my follows (e.g., @_CynthiaThurlow) enabled me to open a dialogue on this stuff with three teenage girls. Try THAT in your house sometime without being murdered. Note that I am not selling any program and receive nothing for my plugs. Twitter, eh?

6/ Post script to 1-5: 

pic on left [above] was Xmas 2016 close to 200lb. Right was this week [Q32019] at ~169. Turned 61 in July[2019]. Started program casually from zero Q3 2017, seriously in early-mid 2018. BF in mid 2018 was 23%. Now approx 15, maybe less [under 15% by Dec 2019].   5’11” tho I bet I’ve shrunk. My 6-6 bro is now 6-5

7/ Chaining something else to my pinned tweet... 

I hit another fitness goal in mid-to-late 2019: For older dudes that follow: I'll assert age is not an excuse, though it may take a good long while. 61 and I *finally* hit all but 1 goal today. Down 35lb plus strength goals hit. Took me about 2.5 years with periodic caloric and alcohol suppression.  Now legs ;-)

[The reason for the two pics, other than pure vanity, was to show the difference between ~15-16% above and a punch down to ~14% below. If I hit 10% I'll do it again...]

8/ Update 02 05 2020: 

1) still at ~167. Body fat is a little lower I think but haven't checked. Using more recovery.

2) will never trust twitter again even as a small inconsequential account. They move goal posts.

9/ My fitness Page

At the top of the blog there is a tab with a cover of my fitness program. Covers the same ground with more detail on the plan.

Increasing the machine's interval of interest to age 60-->95

Reason for this Post

See the integrated cover of what I'm doing here:

• Machine Spending  

In the last post

• Adding some lifetime income to the machine learning model

I wondered what would happen if I looked at the interval not just from 60-80 but from 60-95 because I wondered if the machine could make itself converge, when presented with the beneficence of lifetime income, towards a "shape" of spending that looks more or less like optimal consumption in a formal economics LCM (life cycle model) context.  The mental frame-of-reference that I have for "the shape" -- though there are other sources for this -- is from a 2010 paper by Marie-Eve LaChance titled 

Optimal onset and exhaustion of retirement savings in a life-cycle model; Cambridge U Press. 2010 

On page 35 she sketches it out like this:

Adding some lifetime income to the machine learning model

Premise

The original set up, with the references and links to other posts, is here:

• Machine Spending

In this post I added 15k  (real) in lifetime income starting at age 70 to the other parameters. This can be viewed as exogenous income like Social Security or some other external pension or annuity.

Something to keep in mind is that:

a) This move to add income with no other changes is more or less like adding new wealth to the balance sheet since the probability weighted present value of that stream at 60 is something like 226k, money that we didn't have before. 

b) the income really isn't like a static wealth PV since it is a "flow" that, in the model, is set up to last forever. I mean except that at some age the survival probability goes to zero...which moots the forever aspect.

The game is still the same as before:  recommend to the machine that it spend 4% but also let it learn, via some randomizing and an evaluative reinforcing value function, what might be better given random returns and lifetime, now this time with life income present.