True Link (YC S13) is launching an investment division | Hacker News Reader

True Link (YC S13) is launching an investment division

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38 pointshowsilly14 comments

The glide path shown here [1] seems to advise being ~90% in cash at age 61 and then ramping up risk until you're ~90% in equities by age 86. What's the logic behind that?

[1] https://cdn-images-1.medium.com/max/600/1*TnBmuHLdCi1VGwBMS7...

I don't know this particular company's methodology but, in a nutshell, usually they consider a number of glide paths and then run Monte Carlo simulations for each, then choose the best performing one. The goal is to minimize the probability of running out of money before dying, assuming the retiree withdraws a constant amount every year. Some studies concluded that a rising-equity path performs better.

Of course it's more complicated than that. There's a lot of assumptions embedded in those simulations: life expectancy, bonds and stocks returns, etc. See below for more info.

The Case for Increasing Stock Exposure in Retirement https://www.aier.org/research/case-increasing-stock-exposure...

Reducing Retirement Risk with a Rising Equity Glide Path https://www.onefpa.org/journal/Pages/Reducing%20Retirement%2...

That's interesting, because increasing the percentage of equities over time is literally the opposite of what most other investment advice sources preach. Thanks for the links. :)

Hi! Kai here from True Link. #1 lesson from the launch so far is that graph is totally incomprehensible! We love it here in the office but it's going to be totally re-done in the next release.

That graph is how your money is invested today – we divide your money up based on what age you need it and invest it differently, so what the graph is saying is that "money you need for age 61" is 90% in cash, and "money you need for age 86" is 85% in equities.

People are so used to seeing the glide path graph that like half of people see our graph and are like, wow that's incredibly smart, and half are like, your glide path is upside down.

Also, probably didn't help that I cropped out the axis labels so it would fit nicer on Medium. Thanks for noticing! I'm going to fix that right now.

As it happens, our glide path in aggregate ends up within conventional bounds – we have a screen in the tool that compares the equity percentages to what you'd have in a Vanguard or T Rowe Price target date fund and usually it's in the same ballpark.

I've long been interested in an investment company that had a variable cut that was directly based on the customers' preferences. Ultimately you'd want the managers incentives based on the fees to be exactly aligned with the customers' needs, which means that different fee structures are needed for different kinds of customers.

Basically the hedge fund fee structure extended. So someone who wanted more risk would give a higher cut of fees for higher gains and a lower cut of fees for lower gains, and vice versa. The average expected value to the manager should be a constant percentage of assets, but the distribution changes for each customer.

One cool thing that naturally falls out of this idea is negative fees: if someone is risk averse enough, then the incentives require the manager to lose money if the customer loses, which causes the manager to be risk averse as well for those funds.

(I have more detailed thoughts on this that this margin is too small to contain; feel free to email me for some disorganized elaboration on the above.)

The place this ends up sticky is that a manager with multiple clients can jointly maximize fees – e.g. instead of properly hedging a bet within each client's portfolio, you can put the bet in one client's portfolio and the hedge in another's. If risk preferences are divergent enough the manager can basically be making one-way bets – and frankly the point of this is it could be socially efficient for two of your clients to bet against each other, that's the point, but for almost any nonlinear compensation structure you dream up (even just sharing a little bit in upside, like venture) you can figure out that the manager maximizes his/her own risk adjusted return by playing clients off against each other or creating scenarios that sometimes throw a client under the bus.

To be clear, a flat fee is the ULTIMATE one-way bet… but making the one-way bet simple rather than complex means that it doesn't incentivize one type of behavior over another, you get the one-way bet even without throwing a client under the bus. And maybe at the end of the day your broker or advisor is a good human and, barring any incentive to the contrary, will do his/her best for the client. Kind of a crazy bet, but…

>frankly the point of this is it could be socially efficient for two of your clients to bet against each other

So I did think of your scenario, and actually one worse (directly moving money from clients who don't value the next marginal dollar as much as clients who do). A couple of points I thought of in response:

1. Require clients funds to be transparent, so no moving money around after the allocation decisions have been made (this protects more against my problem than yours)

2. Assume the manager's utility is linear in money, in which case hedging their own fees doesn't make sense. If it's not linear in money, then this all becomes more complicated. I got to the point of saying something like "get a model for client utility and for manager utility of various amounts of money, then set the fee to align incentives". If the manager's utility is linear, then fees should be proportional to utility the client gained. If not, it becomes more complicated and perhaps gaming like you describe is inevitable, this is ultimately a math question for which I haven't modelled everything out and so don't know. You may be able to still define a fee structure that gives a proportional increase of utility to the manager for an increase of utility to the client, but I don't know for sure how that would work for multiple clients.

3. If fees represent utility, and utility is maximized, then wouldn't it be good anyway? (Kind of the point you made in the part I quoted.)

4. Another point to keep in mind is how various kinds of returns are expected to attract or repel customers, which factors into manager utility in a sort of "side-channel". If that's significant enough, it might make the whole incentives not work.

There are a lot of interesting math questions that go into this. I don't have too many answers, but I feel like I have a good grasp of the questions.

Some other points I see in my notes on this:

1. it could be that various kinds of existing funds already cover most of what investors really want, and this won't be enough of an improvement to justify the overhead. Investors who want a small chance of a large win go to hedge funds, investors who want the whole market buy index funds, etc, could be there's no room for innovation there

2. incentive structures need to be very specified, won't just be a fee for various amounts but need to take time dimension into account

3. For that matter, utility is time-sensitive, so we need a complex model just to determine utility, and maybe quizzing investors on utility won't actually get the "truth"

I like to think of this as a combination of the insights behind insurance and hedge funds, basically skewed utility curves.

I'd love to talk further if you're interested. I ended up starting a retail startup instead of working on this idea because it's easier to break into, but I'd be thrilled if someone turned it into a real company or incorporated it into an existing one, and you guys seem to be capable of doing something like that.

Love to help you out on this if I can. The other thing to note is that because of the fear of double dealing there's a lot of stuff on the regulatory side about what kind of fees you can charge – my sense is, even saying, "any quarter in which you lose money, I'll just waive my fee" is illegal (perhaps because it would push the advisor to focus on preventing loss rather than tracking the market). But it's something that to a typical retail investor seems incredibly obvious – why do you get paid for losing me money?? – and I'm kind of sympathetic to, like I'm happy to share the pain in a down market (and to retain the customer). And saying "I actually have to charge a fee in a down market because it's in your best interest for me not to try too hard to avoid bad quarters…" well… there's only so much game theory your typical retail client wants to be doing sitting there in your office.

My gmail address is the same as my HN name. :)

There's a big challenge for RIAs trying to do right by their clients and offer appropriate glide path investment portfolios:

The products and potential returns that honest legit RIAs discuss with potential clients will always be unappealing compared what competitor, dishonest RIAs (who are willing to exaggerate) will be offering.

One lesson from the election: it's hard to convince people of a reality they don't want to hear and warn them of others who are promising wildly optimistic scenarios are not being totally honest with them. Potential investors want to believe exaggerated talk of huge returns by dishonest RIAS and honest RIAs lose clients because of this.

RRG YES

RRG?

How is this better than a Vanguard Target Retirement fund?

Great question. It's a lot like a target date fund, but you actually want your fund a lot more personalized. E.g. a man or a woman both 70 years old today would be in the same 2015 target date fund, but she's going to live longer and so has a longer time horizon and should be one or two percent more in equities maybe. But this also varies based on whether you have equity in your home as a cushion, have long term care insurance (which pushes financial needs sooner), are married (especially to someone older or younger), have a separate tax-advantaged account (that should be spent later, typically, meaning you actually have a very short horizon on your non-tax-advantaged account), etc.

The point is, you'd be surprised how different two people are in terms of investment needs even if they retired the same year.

As an aside, we model our investment model most closely after target date funds and annuities. Annuities offer a guarantee (subject to to the insurance company's solvency) but high fees and low flexibility, while target date funds offer good market participation and low fees but don't have the guarantee component. We include a similar blend of securities as a target date fund might, but also include an annuity component for the guarantee.

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