Building the Thing I Wish I’d Had Before I Bought My First Rental

5 minute read

It’s 11:40pm. Do you know where your polygons are?

It’s 11:40pm on a Friday and I’m staring at a ZIP code boundary that won’t render correctly on a map for the 20th time. The polygon is trying to wrap itself around the entire Eastern seaboard because somewhere in a coordinate system I don’t fully understand, a projection did something a projection should not do. My wife went to bed an hour ago. I am debugging a map.

This is, apparently, how I relax now.

I own two rental properties. I underwrote both of them the old-fashioned way: a spreadsheet, a lot of Zillow tabs, some gut feel, and a healthy dose of “well, it seemed fine.” It worked out. But “it worked out” is not a strategy, and I’ve always wanted something more rigorous — something that forces me to ask the boring, unglamorous questions before I fall in love with a listing photo of a nice kitchen.

So I’m building one. It’s called, very unpoetically, the REW platform (real estate underwriting — I never claimed to be a marketer). And I want to talk about it now, while it’s unfinished, rather than waiting until it’s polished enough to be impressive. Partly because I think the process is more interesting than the finished product. Mostly because I suspect I’m going to get a bunch of this wrong, and I’d rather be honest about that from the start than pretend I built a flawless machine on the first pass.

The Actual Problem I’m Trying to Solve

Here’s the question that matters: out of every possible place I could buy a rental property, how do I quickly rule out the bad ones and spend my real time and energy only on the good ones?

Most people do this backwards. They fall for a specific house, then start justifying the numbers to themselves. I’ve done this. It’s a great way to talk yourself into a mediocre deal because you already mentally moved in.

So I’m trying to build a pipeline that works in the opposite order: start broad, get skeptical fast, and only let a deal survive if it earns its way through several rounds of me actively trying to kill it.

Right now, that pipeline has three stages.

Stage One: Is This ZIP Code Even Worth Looking At?

Before I care about any specific house, I want to know something more fundamental: is this area one where owning a rental makes sense at all?

I built a scoring engine that pulls data from a handful of sources — Census, HUD, FRED — and boils a ZIP code down to six metrics I actually care about as a landlord:

Population growth (are people moving here, or leaving?)
Unemployment (is the local job base healthy?)
Price-to-rent ratio (are prices in line with what rent can support, or wildly detached from it?)
Median income (can the local population actually afford the rents I’d need to charge?)
Vacancy rate (is there a glut of empty units I’d be competing against?)
Supply pipeline (how much new housing is already under construction or permitted nearby?)

That last one took me the longest to get right, mostly because “how much is being built near here” turns out to be a genuinely annoying question to answer with public data. I ended up pulling county-level building permit data from the Census Bureau and matching it up as best I can to individual ZIP codes. It’s not perfect. I know it’s not perfect. But it’s a meaningfully better signal than “I have a feeling about this neighborhood,” which was more or less my prior methodology.

The output of stage one is just a score and a rough read on the market. It’s not a green light to buy anything. It’s closer to deciding whether a neighborhood deserves five more minutes of my attention.

Stage Two: Now Let’s Try to Kill It

This is my favorite part, mostly because it’s the part I was worst at doing manually.

Once a ZIP code clears the first screen, I don’t move straight to a full underwriting model. Instead, I run a quick, deliberately unforgiving pass on the specific property: rough rent estimate, rough expenses, rough financing assumptions, and a gut-check cash flow number. Nothing fancy. The whole point of this stage is speed and skepticism, not precision.

I’m explicitly trying to find a reason to say no. If a property can’t survive a lazy, surface-level version of the math, it has no business surviving the detailed version. This saves me from the trap I fell into with my own properties: spending three hours building a beautiful, detailed model for a deal that a five-minute sanity check would have thrown out immediately.

Think of it as triage. A property that fails here doesn’t get a eulogy. It just doesn’t move to the next room.

Stage Three: Full Underwriting, For the Survivors Only

Only the properties that make it through both filters get the full treatment: a detailed cash flow model, sensitivity around rent and expense assumptions, and eventually — this part isn’t built yet — Monte Carlo simulation across a range of market conditions, so I can see not just “what’s the expected return” but “how bad could this realistically get, and how bad could it get in an unlucky sequence of years.” Longtime readers know I have a soft spot for that kind of analysis; I wrote about the same idea applied to a stock/bond portfolio a while back, and I think the same logic applies just as well to a single rental property.

That full underwriting step is the expensive one, in terms of both my time and the computer’s. Which is exactly why I don’t want to run it on every listing I glance at. The first two stages exist entirely to protect the third one.

Where This Actually Stands Right Now

I want to be honest about the state of things, because I think “in progress” is a more useful thing to model publicly than “finished.”

The ZIP scoring engine works, mostly, though I’m still finding edge cases — ZIP codes that straddle county lines are a special kind of headache I did not anticipate when I started this. The quick-kill screen exists but needs more real-world deals run through it before I trust its instincts. And the full underwriting stage is still mostly aspirational; right now it’s a folder full of half-finished code and a Monte Carlo module I keep meaning to properly hook up.

I’m also in the middle of moving the whole thing off my laptop and onto a little Linux box that lives in my house, partly because I like understanding my own tools end to end, and partly because I’d rather not depend on someone else’s server for something I’m going to trust with real buying decisions. That’s its own rabbit hole, and probably its own post.

None of this is a product yet. It might never be, in the sense of something anyone else uses. But it’s already changing how I think about the two properties I own, and it’s forcing me to write down assumptions I used to just carry around in my head, which is worth something on its own.

Why Bother

I could just keep doing this in a spreadsheet. Plenty of successful investors do exactly that, forever, and do fine.

But I like building things, and I like being forced to be explicit about my reasoning instead of trusting a gut feeling I can’t fully explain even to myself. If I’m going to make real decisions with real money — and eventually, real decisions on behalf of anyone else who ever looks over my shoulder — I want a process I can actually defend, one metric at a time, rather than a vibe.

I’ll keep sharing this as it develops, including the parts that don’t work, the ZIP codes that break my map projections at midnight, and whatever the quick-kill screen gets embarrassingly wrong the first few times I trust it. That feels more honest than waiting until it’s shiny.

A reminder that we’re not licensed financial or investment professionals — just sharing what we’ve learned and how we think about it as we build it. Talk to a qualified advisor before making decisions with real money on the line.

Are Millennials Really Behind?

2 minute read

I saw a great graph on vital capitalist the other day. It looks a bit like this.

Here’s a link to the original.

A main take-away offered by the creator is that Baby Boomers control a whopping 50% of the total wealth in the US while other generations lag far behind. And, it’s true. As a generation, Boomers are extremely wealthy at this point in their journey.

The other implication is that those much maligned Millennials are so busy staring at their iPhones and buying avocado toast that they’re missing opportunities to build real wealth. Look at how pitifully small their generational net worth line is compared to the Boomers.

But, are they really so far behind? It turns out that age matters quite a lot in the race to build wealth. The youngest Boomers are 60. The oldest are 78. If you are a Millennial born in 1981, you’re turning 43 this year. If you were born in 1996, you turn 28 this year. We shouldn’t compare the assets of a 65 year old to the assets of a 25 year old.

So what if we took the exact same data but started all the generations at the same time and looked to see how well they did accumulating net worth during their lifetimes. The plot would look something like this.

Remember, this is the same data, but it’s put onto the same axis such that each generation starts the race at the same time. Now, it doesn’t look like the Boomers are the clear winners of the race. Both the Gen X’ers and the Millennials have appear to have accumulated higher net worths by the same “generational age.”

I admit, the data set is incomplete. The Distribution of Financial Assets data set only goes back so far. So, we’re doing a bit of mental extrapolation during both the Baby Boomers and Silent Generations’ respective youth.

Another criticism could be that based on my (admittedly quick) read through of the DFA description, there is not an inflation adjustment applied to this dataset. 1986 dollars are not the same as 2024 dollars.

If you want to make an inference about how much or when Gen X or the Millennials will achieve a certain wealth level, it would require a lot of extrapolation using exponential growth. For now, I’ll leave that as an exercise for the reader. But, I like the idea of the footrace being less clear cut in favor of the Boomers.

Go Fast to Go Slow

2 minute read

“Life moves pretty fast. If you don’t stop and look around once in a while, you could miss it.”
-Ferris Bueller

I haven’t posted in a while.

I have a bunch of excuses:

Bought a house
Moved
Rented the old townhouse
Started a Master’s degree
Worked
Tried to be a good Dad/partner along the way

A few of my excuses might become blog posts in the future.

We’re finishing up a road trip to Florida, and I have actual time to write. (yes, we drove from Maryland…see why I like $5/gal gas). One daughter is sound asleep. The other recently learned how to braid and is braiding everything in sight. At least it’s a quiet activity….

I’m reflecting on our whirlwind trip. Ok, I was scrolling through Mint and seeing just how much our whirlwind trip cost us. Instead of sweating the dollars, I realized this is exactly why we have worked hard, saved, and invested for years! And that’s what prompted me to put quill to parchment again.

For the record, we rented a ~~mini~~ mansion with two other families and filled it with laughter and joyfully squealing kiddos, lazed away a couple of afternoons bobbing around the resort river, completely throttled two Orlando area theme parks, and visited with family.

If this were Instagram, that would be the only perfectly coiffed image you would get.

But we weren’t quite so polished when our over-tired two year old raced off, red shoes a blur, through the packed theme park restaurant dodging patrons better then Rogue 5. Our first warning that something was amiss came from a staff member yelling, “we got a runner!”

Nor was I ecstatic when my little ones both turned up their noses at the tepid, slightly sulphury Florida tap water I had filled their reusable bottles with. I gritted my teeth and shelled out $8(!) for two nicely chilled plastic bottles of filtered water. But I totally poured the purchased water into their reusable bottles first…

So much of the personal finance space is full of tactics for how to get a certain number of dollars in some accounts. And, we’re not going to neglect our financial journey either. But sometimes, we miss out on the real purpose behind all that working, saving, and investing.

Yes, we’re exhausted from the trip. Yes, our wallets are lighter. Yes, we had plenty of aggravating moments. But our hearts are full.

I Happily Filled My Tank With $5.49/Gallon Gas

5 minute read

I’m currently driving across a chunk of the United States with my family in our minivan. The van has a 20+ gallon tank. I put ~14 gallons into it. At $5.49/gal, I dropped just under $70 to fill it.

Ouch.

There has to be a better option than spending a day and a half stuck in a tin can. Then again maybe some perspective is in order.

We needed to be back home with family for about 10 days. We had about 3-4 weeks to plan our trip. The nature of our visit wasn’t something that could be done virtually or simply forgone. Typically, we default to piling into our minivan and hauling across the country. This time, I thought it would be interesting to look at some alternatives to see what the time vs. money tradeoff looks like.

Our Baseline

Our trip is about 900 miles one way. Our van gets about 25 miles per gallon on the trip. A little more in the flat states. A little less in the hilly ones. 1800 miles / 25 miles per gallon means round trip we’re buying about 72 gallons of gas.

All of our fill ups have been less than $5.49/gallon, but let’s use that as our worst case. For gas alone, we’re talking about $400 of gas.

We’re pretty good about taking care of our vehicles. Therefore, I’m comfortable saying we’ll get 100,000 miles of life out of this car. 1,800 /100,000 is just under 2%. Let’s pretend it’s straight depreciation of the vehicle purchase price (~$20,000) relative to mileage. That works out to about $360 of depreciation for this trip.

With 900 miles of road to cover, we either leave in the middle of the night and do 16 grueling hours all at once or we split the trip into two days. During the early parts of the COVID-19 pandemic, we did the former. We didn’t stop for anything except to fill the gas tank and empty our bladders. It was not fun. Now, we’re a bit more willing to make a stop midway, so we’ll say 16 hours of driving + 8 hours at a motel for a total of 24 hours one way. Adding the hotel costs $140 to the round trip price.

Total cost: $900

Total time: 48 hours

Intangibles: we travel with our dog, a cooler full of healthier snacks and have little contact with others (especially important for a 2 yr old still ineligible for COVID-19 vaccination).

Flying Commercial

Instead of 13 hours of road time (it’s actually closer to 15 with young kids), we could have taken a short flight. If we catch a nonstop flight, our door to door travel is 30 mins to the airport, 1.5 hours at the airport to clear security, a 2 hour flight, 30 mins to get bags and rental car, and then 2 hours to drive to our destination. 6.5 hours total (assuming everything goes smoothly) one way. Not bad relative to the drive time in the van.

Given that we had a relatively short time to book airfare, the cheapest flights I c0uld find are about $215 per person one way. With four humans, our flight cost is 4 x $430 = $1720.

Of course, we have to do something with the dog. No, we’re not going to ship her in the cargo bay. So, it’s either boarding at a kennel for something like $55/day or at home care for closer to $80/day. Our trip was 10 days. Yikes, we’re at somewhere between $550 and $800 just for the dog. Let’s go with $550 to be conservative.

Next, we need a rental car and two car seats when we get where we are going. That’ll be $850 for a full-size car for 10 days.

Total cost: $3120

Total time: 12 hours round trip

Intangibles: way less travel time with a potentially cranky toddler, more COVID-19 exposure, more people to annoy inside of an airplane with a cranky toddler.

Train

We’ve been on plenty of trains in Japan and Europe. Before kids and COVID, we took the train into and around Washington DC. But, as much as the notion of a train excites me, I don’t usually think about it as a serious method of transportation in the United States. For this exercise, here’s the numbers:

Amtrak quoted me $227 one way and $159 return. At $386 per person round trip, taking a train is actually cheaper than the prices I saw for flights. Total travel fare would be $1,544.

We still need to take care of the dog and rent a car upon arrival. $1,544 + $550 + $850 = a total cost of $2,944.

We need 30 mins to get from home to the train station. The train ride is slated to be about 24 hours with 2 train transfers. Again, we need 30 mins for getting from the train and into a rental car. Then, it’s 2 hours to get to where we are going. Total time is about 27 hours one way or 54 hours total.

Intangibles: less rigamarole to get to/from the train than an airport, someone else drives the train, moving sleepy kids between trains at odd hours.

Private Flight

I’ve never looked into this before, but why not? We’re almost A-list! It turns out that anyone can rent a private jet. For around $15,000 (give or take a few thousand bucks), we could get our own private plane to whisk us across the country. By the way pets are allowed on domestic private planes…guess we can bring our dog with us (and save big bucks on that costly kennel fee)!

Because the private flights leave from the General Aviation part of an airport, there is far less time required to go from the car to the airplane. And let’s be honest, if we could throw down $15,000 for a plane ride, we can afford a driver to get us to the General Aviation terminal. No $8/day long term parking for us! So the time works out to 30 mins to the airplane, a 2 hour flight, 30 mins to get bags and rental car, and then 2 hours to drive to our destination. 5 hours total (assuming everything goes smoothly) one way.

Total cost: $30,000

Total time: 10 hours

Wrap Up

Here’s a scatter plot showing each of these different options to visually represent the trade off between dollars and hours.

The gist is this: we all make trade-offs about how to spend our time and/or our money. If I absolutely needed to be with my family that same day, spending $15,000 for a private flight is truly an option. Fortunately, I’ve never been forced into that position. Instead, I’m optimistic about how much time I have left on this Earth, so we traded time for dollars. $900 (even with crazy high gas prices) is way cheaper than the nearest alternative.

Besides, who says that two days jammed into a car with your family can’t be memorable and maybe even fun? One of my favorite moments from this road trip: I read about a quarter of Little House On The Prairie to my daughters while my partner drove. At the end, our 6-year old was still entranced. Our 2-year old just looked up at me with a big toothy grin and said, “More cookies, please!”

How to Manage Your Emotions While Investing in a Downturn

3 minute read

“This too shall come to pass” –ancient Persian parable

The S &P 500 closed down 20% from its peak of 4800+ over the past 5 months. Financial headlines trumpet words like “crash” “bear market”, “extreme fear”, and “volatility“. Red is the predominant color on financial news service websites. Is it time to panic sell all your equities? Should you go all in on the US Stock market?

First: Don’t Panic

OK, take a deep breath. Don’t panic. 20% drops actually happen rather regularly. The current drop happened over a period of about six months. `Here’s an image showing the distribution of S & P 500 price changes for 6 month intervals.

The light red dashed line is at -10% or “correction” territory. The dark red dotted line represents -20% or the threshold for a “bear market.” Look how much of the distribution remains to the left of both of these lines. Neither event is uncommon. In the histogram, I also highlighted the 0% line in solid blue. Take heart doom and gloom fans: most of the distribution is to the right of that solid blue line. That means that most of the time, the market has a positive return.

Let’s look at the same data differently so we can more easily quantify how often to expect a -10% correction and a -20% bear to occur within a 6 month window. Corrections happen about 10% of the time. That 20% bear market line happens about 3% of the time. There’s a reason why people smarter than me have said that over time, “it always goes up .”

Cumulative distribution of 6 month market returns

Second: The Market Isn’t That Cheap Yet

Believe it or not, we’re not at bargain basement prices yet either based on two widely accepted measures of aggregate market value.

1) the “Buffet indicator“, which looks at a country’s total stock market’s price relative to the economic output of that country. Economic output is usually measured as Gross Domestic Product. Here’s a detailed discussion if you want some real gory stuff. While the current market conditions have improved from late 2021/ early 2022, valuations are still relatively high.

2) the Cyclically Adjusted Price to Earnings ratio (CAPE) or Shiller PE is another measure of long term value. It too is still high by historical standards despite recent sell-off. As of this writing, the Shiller PE is above 30 against a long term average of about 17.

Of course, I don’t have a crystal ball that sees into the future. However, based on measurements like these that show some good predictive power with long term stock market returns, it might make sense to make a measured response.

How to Respond to a Market Downturn

With a 20% drop, your asset allocation is likely out of balance. you can think of the market on sale and consider this an opportunity to re-balance. Sell some bonds and buy some stocks to bring your asset allocation ratio back to your goal.

Continue investing regularly or dollar cost averaging. Stay the course and try to avoid any drastic action. You’re investing for the long haul. As we’ve seen above, dips happen regularly.

If you have low enough expenses, consider investing some extra funds while prices have reduced. I would be cautious of going all in at this time though.

Stay diversified. It’s tempting to think we’re able to pick individual winners. For most investors who aren’t spending their free time reading prospectuses our scouring the headlines for information about a company, buy the entire market (or at least a big chunk of it) and ride the tide.

Disclaimer: While we have a passion for providing entertaining, informational, and possibly useful articles about personal finance, we’re just random people on the internet with no formal credentials or expertise. Talk to a licensed professional advisor if you need advice.

The Portfolio Series – Part 1: Monte Carlo Simulation

5 minute read

We’re kicking off a new, multi-part series here. We’re going to be looking at several different investment strategies using Monte Carlo Simulation techniques. Our goals with this series are to:

Demystify the Monte Carlo simulation technique.
Objectively evaluate the performance of different strategies against each other.
Learn.

I’m going to drop in our disclaimer right here just to make sure there is no confusion:

What Is A Monte Carlo Simulation?

Monte Carlo simulations attempt to show how a system responds through the use of repeated, random sampling of a model of that system. In observing how the system responds to a range of inputs, we can make better decisions in real life. We would like to see if we can learn about how well different investment strategies performed so we can make decisions about what to do in the future. Check out wikipedia and investopedia for some more detail on Monte Carlo Simulations.

While this post/series is not a comprehensive overview of the topic, a brief introduction is useful. Remember the “Normal” distribution from your first statistics class? If not that’s OK. My first statistics class was traumatic too. It represents a range of values/probabilities that we’re likely to see in many systems. Here is a distribution that represents the US Stock Market’s annual returns:

1000 samples of annual US stock market returns from a distribution with mean of TBD and standard deviation of TBD.

For Monte Carlo Simulation, the distribution is at the heart of everything. It is our representation of the system. The underlying distribution tells us how often we expect to see a given result. Finally, it is also fundamentally based on assuming that the general shape of the past can give us clues to how the future will look. How?

We iteratively and randomly sample points from the distribution. In our case, this provides a hypothetical sequence of returns for that asset class. If we’re simulating a 30 year retirement, we need 30 points from each asset. We’re using a distribution rather than actual historical sequences like cFireSIM. Therefore, we can simulate an infinite number of sequences. Let me be clear: that’s not a knock against cFireSIM. It’s actually one of my favorite tools and an inspiration for a lot of our work here.

What does a Monte Carlo Simulation Look Like?

Next, let’s look deeper at the first 5 points sampled from this type of distribution. We will illustrate how we can start to build up a sequence of returns. Remember, these 5 points are randomly drawn from the same distribution. Think of them as the first 5 years of a single “run” representing one potential retirement reality. Below, each panel shows a new point being randomly generated from the underlying distribution and added to the prior sequence.

Five successively chosen points from an underlying distribution.

Next, we can extend the sequence to 30 points (or any number) to represent a single retirement “run.” The next plot shows three such runs. Remember, we drew 3 sequences of 40 points from the same underlying distribution. And, the underlying distribution represents the annual performance of the US stock market. Therefore, you can think of this as three potential retirement experiences.

Three simulated “runs” of randomly generated sequences of returns.

When you make thousands of such multi-decade “runs”, you start to see the range of potential outcomes from this portfolio over time. And, that’s the foundation of our Monte Carlo simulation. We iteratively sample from the historical return data. We then simulate thousands of 20 year, 30 year, or 40 year (or more for those in the FIRE community) return sequences. Finally, let’s put the whole thing together and illustrate our 3 runs from above against a fuller population of simulation data.

In this plot, we simulated 1000 runs and then took the 10th to 90th percentile of those runs within a given year. We’re essentially eliminating some of the less likely returns from the summary. This reduced population forms the grey band in the graph. Overlaid on top of that are the three runs from above. Notice how many individual points are well outside of the grey bands. That’s important: any individual run can have some pretty extreme values (March of 2020, anyone?), but when you look at expected values they’re frequently less extreme. Are those extremes possible? Yes! But, they’re also less likely to occur.

Three 30 year simulated runs highlighted against the 10th -90th percentiles (grey band) of a 1000 run Monte Carlo Simulation

If you had two distributions, one that represents the annual performance of the US stock market, and another that represents the annual performance of the US bond market, you could start to build a model of their respective performance over time. From there, we can start to compare how well different portfolios perform…but we’ll dig into that another time. For now, let’s look at one caveat of many simulations: the shape of the underlying distribution(s).

Pitfalls of the Normal Distribution

In many systems, the normal distribution is a good fit for the underlying data. Stock market performance is not one of them. Here’s a great discussion on the topic. The key phrase is, “fat tails”. Over time, people observed that the stock market sees big movements more frequently than the normal distribution would suggest. This results in errors: differences in the model relative to historical performance. We would like our models to be as right as possible. I need to pause for the obligatory quote from legendary statistician and 20th century Renaissance Man, George Box:

“Essentially all models are wrong, but some are useful.”
George Box

Of course, we would like the models to be as right as possible, especially if we’re going to use them.

Metalogs – An Answer to the Normality Problem

Meta what?

“Metalogs”

They’re flexible distributions that more accurately reflect the underlying data than many of the classic distributions we’re used to (e.g., the Normal). Check them out here. They were invented by Tom Keelin who could be the 21st century’s Renaissance Man. By making distributions that can generate continuous samples from the underlying source data, Tom enabled us to reduce the bias in our original models. He helped us to fatten up our models’ tails when working with stock market return data (and his invention can be useful for modelling in any discipline. Have I sung his praises enough yet?).

Here’s a picture to help illustrate the differences between the actual data and two simulations. We can make 1802 annual return data points from Dr. Shiller’s dataset, called “Actuals” going forward. First, I calculated the mean/standard deviation of the Actuals and used those statistics to generate 1802 simulated returns using the Normal distribution. Then, I fit a Metalog to the original data (a 13-term metalog had the lowest standard error) and simulated 1802 more annual returns using a Metalog based on the actual data. Here’s a Box Plot (yes, the same George Box) showing how the three distributions compare.

Visually, you can see the Actual Returns and Metalog Simulation both have longer whiskers and more outliers than the Normal Simulation.

Wrap Up

That will do it for this first introduction to the topic of portfolio evaluation. It’s a fascinating problem. Inevitably, we will make mistakes along the way. I’m excited to dig into this topic and learn more about it. Hopefully, you have a better understanding of how we’re approaching this idea of portfolio evaluation. In subsequent posts, I will lay out some sample scenarios and start simulating!

How to Use Asset Allocation To Invest For Volatility

2 minute read

A worldwide recession. All time market highs. A global contagion. All time market highs. A foreign invasion. Are all time market highs in our future? The stock market is a wild ride. Stocks are a highly volatile asset class. They always has been. They likely always will be. So, how should one invest for volatility? How do you get to financial independence as quickly as possible while minimizing any missteps along the way?

My favorite investing strategy for volatile times (which is all the time) is pretty simple: subtract your age in years from 100. The result is the % of your portfolio you should keep in a total stock market index fund (like VTSAX). The balance (your age) should be in a total bond fund (like VBTLX).

It makes taking action (or remaining inactive) amidst volatility really simple. Is the market at all time highs? Sell some stocks and buy some bonds to rebalance and lock in your gains. Is the market crumbling around you? Sell some bonds and buy some stocks while they’re at a discount. Aim to keep your percentages within about 5% of their targets.

Selling At A Bottom Can Delay Financial Independence

One of the worst things an investor can do is sell at the bottom of a market correction/crash when emotions are high. Doing so can significantly delay the time to financial independence. Making an ill-timed sale turns a paper loss into a real one. Now, you need a correspondingly bigger increase to make up for the loss. Instead, invest for volatility so you never feel the emotional pressure to sell low.

Your Portfolio Adjusts For Risk As You Age

As you age, your portfolio will get more conservative. That’s not a bad thing, especially as you close in on needing to draw from the portfolio. But, the portion in stocks will still grow significantly, helping to ward off the insidious effects of inflation. And, this approach recognizes that human behavior, has a real effect on a portfolio’s performance.

A Variation

For more aggressive or risk tolerant investors, consider subtracting your age from 110 or even 120. You’re still investing for volatility! You’ll simply end up with a higher percentage of the portfolio in stocks (and likely a wilder ride). But, over the long haul, you can expect a higher total portfolio value because more of the portfolio is invested in growth assets (stocks).

How to Use Capital Gains Harvesting To Prepare An Amazing 21st Birthday Party For Your Kid

4 minute read

My girls will have awesome 21st birthday parties if they want them. Or, they will have startup capital, weddings, house down payments, or gap years. How, you ask? Some modest investments, time, and dependent capital gains harvesting.

Investing In Your Child’s Financial Future

When my oldest daughter was born, her uncle Dan gave her a gift of $100 with the following instructions:

New Baby-
Tell your Dad to open an investment account for you (if he hasn’t already) and put this cash into the account. When you turn 21, you can have a big party with all your friends!
Uncle Dan

Any time she received money from other family members, we bought more of Vanguard’s total stock index ETF, VTI. Turns out infants don’t really need much more than diapers and onesies. So, we asked family members for any gifts during her first few years to be cash too. I also split up my 529 contributions so that every paycheck I put a bit more into this account instead of the 529.

Over time, we just kept adding more shares. Once her account crossed $3,000, we converted it to Vanguard’s total stock index fund, VTSAX and set it to auto purchase a little bit each pay check.

It has been a very positive 5 years during her investment career. I looked at my records and plotted the historical growth of her UTMA account. Being a nerd, I also extrapolated 3 scenarios into the future:

At the low end, we’re just contributing $300/yr and the account grows at a rather paltry 3%.
The nominal scenario has us contributing about $850/yr with the account growing at 5%.
In the high scenario, we’re adding $1700/yr and it all grows at 7%.

Three potential growth scenarios for a child investor

It’s a proud papa moment when my almost 6 year old is able to peer into her young adult years and have between 25-95k in capital at her disposal. Thank you, Uncle Dan!

Now for the fun part: Dependent Capital Gains Harvesting

As the market moves up and to the right, I periodically sell VTSAX and buy something similar like Vanguard’s S&P500 index fund, VFIAX. This is a taxable event. We sold shares for a profit, and my daughter, our dependent, owes capital gains taxes on her earnings from the sale. Note: to keep things simple, I’m assuming no other types of income (no dividends, no interest, no earned income).

For minors in 2023, the IRS taxes capital gains on up to $2200 of unearned income per year at 0%. My oldest daughter is almost 6. This is her only source of income. While she is our dependent, as long as she doesn’t profit more than $2200/yr, she owes nothing on the gains for that year.

Once she is no longer our dependent, she will be eligible to pay “filing single” capital gains taxes. Let’s pretend that we’ll flip that switch when she turns 18. That may not reflect reality, but it’s an example. In 2023, for individuals filing singly, the IRS capital gains tax rate on up to $40,400 of taxable income is 0%. Let’s take the low balance scenario and see what her cost basis looks like at 21. Remember, we’re making some assumptions here:

Selling enough shares each year until she turns 18 to lock in $2200 of capital gains with 0$ of taxes owed
After she turns 18, selling enough shares each year until she turns 18 to lock in $40,400 of capital gains with 0$ of taxes owed. OK, this may not be as realistic, but it should illustrate the point

A Deeper Look At The Scenarios

Using capital gains harvesting for a dependent while she has $0 of other income, by the time she reaches 21, the entire balance of her after tax account will already have had the capital gains taxes paid…at 0%!

Low balance scenario where we contribution ~$300/yr & it grows at 3%. See how quickly the basis catches up to the balance (the purple line is right at the orange line by the time she is 7). That’s the power of harvesting capital gains for your dependents.

By making these taxable transactions periodically and harvesting her capital gains, she will incrementally increase the cost basis of her investments. As her new cost basis increases, she has a lower potential tax burden in the future. The next two scenarios are a little more aggressive, but also show the power of this approach. Here’s the nominal scenario (contribute about $850/yr; grow at 7%/yr) resulting in around $50,000 of investments with little to no tax obligation at age 21:

In this scenario, the growth is high enough that she needs one year of filing single to fully catch back up. The net result is that by 21, she has a big asset with little to no tax obligation.

Finally, the high growth scenario is truly exciting. Yes, we’re contributing $1700/yr, which could be a pretty high burden for some folks. And, the funds are growing at 9% year after year. That’s high, but not unreasonable, I hope.

There it is: nearly $100,000 of assets with ~$0 of tax obligations against them. How cool is that?

By age 21, she has nearly $100,000 of investments, again with nearly $0 in tax obligation. Have a crazy cool 21st birthday? OK! Pay off a big chunk of student loans? OK! Down payment for a house? OK! Seed capital for a business? OK! It’s enough that she can do almost anything…but she cannot do nothing.

Why Is A Market Decline So Bad Early in Retirement?

2 minute read

A 50% decline is bigger than a 50% gain if it happens first. Let’s take a quick look at Sequence of Returns risk.

Your investment portfolio is represented by a pie, raspberry if you like.

Pretend that you have worked hard for 15 years, saving 54% of your income and are ready to embrace your financial independence. The day after you step into your new life, the market crashes 50%, wiping out half of your portfolio’s value. Think of your portfolio looking like half a pie now. Ouch.

One half of the pie. It was either “lost” due to declining portfolio value or after eating.

In our simple example, it is a volatile market. The very next day, the market soars 50%!

You’re back to where you started, right?

Nope.

You’re only at 75% of your original balance. A 50% gain after a 50% loss is only a 25% gain on the original amount.

Take away half the pie and then add half back. You don’t get the full pie.

If you needed to buy groceries or pay your mortgage (or make any withdrawal from your portfolio) while the market was down, you have even less left.

This simple example illustrates sequence of return risk where a decline in the portfolio happens shortly after someone starts to draw from it (e.g., in early retirement or FI years).

How to mitigate sequence of return risk:

Manage your asset allocation. Keep some bonds, cash, & stocks in your portfolio, especially if you’re planning to draw from it soon. In this way, you won’t have to sell stocks when they’re down in order to eat.
Continue to generate some income so required portfolio withdrawals can be reduced. If you keep working or pick up some extra work, that income can be used for living expenses instead of selling assets at a loss during an early down turn.
Start with a bigger pie.
Eat less pie (reduce expenses during downturns)

Most Mortgage Refinances Are For Suckers.

8 minute read

Should I refinance my current mortgage? Banks/mortgage companies want you to refinance your loans because they will make more money from you. Sure, they may advertise lower rates, lower payments and show pictures of smiling people having fun. Make no mistake: unless you do the math, odds are they will take more of your money.

With interest rates still low by historic standards, lots of folks have been refinancing to lock in lower payments. Add a booming housing market to the mix, and people are refinancing and withdrawing additional equity from their homes in droves. It seems like we get solicitations weekly from our own lender.

By the way, we’ve made this mistake too. Twice! Please learn from our missteps so you don’t have to make the same mistake.

Buying a House Is Like Buying a Car

Let’s start with an analogy. You are at the car dealership shopping for a different, used Camry. You have $2,000 in cash and want to stick to a 20% down payment. Therefore, your budget is $10,000. If you put down 20%, you need to borrow $8,000 to complete the purchase. For a 3 year auto loan at 3.69%, your monthly payment is $235.09.

Then the sales person says, “you know, I can get you into a new Camry for the same monthly payment.” Your ears perk up. New car smell for the same monthly payment? Maintenance free miles at the same price? Tell me more about how I could get more swagger for the same dollars.

You can’t, of course. Let’s see how this trick works.

For starters, take the first scenario and multiply the monthly payment of $235.09 times 12 for an annual total of $2821.08. Then multiply that times the 3 years you will have the loan. Your $10,000 car actually costs $10,463.25. The 463.25 is the interest you will pay over the life of the loan. That’s what financing will cost you. What could you do with that extra money if you just bought with cash?

Now let’s look at how our crafty dealer can get you more car for the same monthly payment. We’ll keep the interest rate the same, but we’ll push out the loan duration to 7 years. Let’s see how much we can borrow while keeping the payment no higher than $235.09. Looks like $17,375! Woo hoo! With your $2,000 in cash, you have a total of $19,375 to throw around. New car smell, here we come. The real costs of this upgrade are your indebtedness for an extra 4 years and a total of $2,367.03 in interest. Your $19,735 Camry actually costs you $21,742.03 over the life of the loan.

If you spend any time on “how much house can I afford?” websites, you’ll usually see that they focus on what your monthly payment will be. And, it works! According to an expert at Fannie Mae, 90+% of US home mortgages are 30 year loans.

Buying a House With a Loan Spends Your Future Earnings Today

Now, let’s scale it up. Houses usually cost more than cars. And, at least in the US, we accept 30 years as the typical amortization period. Once you sign on the lines, you have effectively pre-spent 30 years worth of income. (There’s a reason mortgage contains “mort” the french root word for death)

Why Banks Love New Mortgages (and especially mortgage refinancing)

I remember when we signed our first mortgage. We were pretty young. We knew this was not going to be our dream house, but it was our first house. Despite doing lots of homework, we never really had any one challenge our approach or suggest there might be another way (like house hacking). So, we went for a 30 year note to keep the payments low. The total interest we would pay over the life of the loan was almost double the principal. Let’s dig into how a mortgage is structured to better understand things from the bank’s view.

Let’s start with the concept of amortization. When you take out a loan, a lender gives you a sum of money. You agree to pay that sum back over time. The lender charges you interest as their price for the service of loaning you money. An amortization schedule is the sequence of payments over time where how you agree to repay the lender. By the way, amortization comes from old French/Latin. It means to “kill it off”. As in to destroy an asset that generates revenue. When you pay off your loan, you have killed one of the lender’s assets. Do you think they really want their assets killed off? (Hint: no!)

So you have a new letter in the main offering a mortgage refinance. Sounds interesting, right? Lenders love new mortgages because so much of a borrower’s payment goes towards interest. You need to look at an amortization schedule so you can see why. The amortization table shows the monthly payments for the life of the loan. It is your repayment plan. It also shows how much of each payment goes towards paying down principal and how much goes to interest. You can also see how much total principal and interest a borrower has paid.

Here’s a simple example. Let’s say a borrower took out a $200,000 mortgage. The duration is 30 years and the interest rate is fixed for the life of the loan at 4% per year. With these terms, each month, the borrower commits to pay $954.83. Because this is a 30 year loan, the full amortization table is 360 rows long. So, here’s a condensed summary showing every 36 months instead (with a couple extra highlight rows added).

condensed amortization table showing when a hypothetical mortgage has greater than 50% repayment of principal and when cumulative principal exceeds cumulative interest — Condensed amortization table showing when a hypothetical mortgage has greater than 50% repayment of principal and when cumulative principal exceeds cumulative interest

It Can Take Years Before You Pay More Principal Than Interest

A few observations from the table above:

Initially, almost 70% of the monthly payments are used to pay interest. Yes, you might be writing $1000 checks every month, but when you start, only $300 of that pays off the balance. $700 goes to your lender’s pocket.
It takes until the 154th payment (almost 13 years in) before 50% of the payment is applied to principal.
You have to wait until the 283rd payment (23 years!) before your cumulative principal payments outpace your cumulative interest payments.

Wait…what!?

No wonder bankers wear fancy suits! A new loan generates significantly more interest (potential profit) than an old loan. And, the longer the term (e.g., 30 years vs. 15 years), the more favorable the loan is for the lender.

Most People Do Not Pay Down The Full Balance Their Mortgages

Now that we understand why lenders have such a strong incentive to get you into a new loan, we can add another wrinkle. Mortgage companies/banks know you are unlikely to keep the loan to the end. According to the National Association of Realtors, the overall US “median duration of home ownership is 13 years.” And lots of folks complete a mortgage refinance even without moving. With rapid turnover on a 30 year mortgage, it can be difficult to build equity because so much of one’s payments go towards interest for so long.

That’s right. The 30 year fixed note that 96% of us sign up for is closed after 13 years. In our example above, that’s right about when each payment finally has 50% going towards principal. And a substantial number of folks close their mortgages before 13 years, meaning they accumulate even less cumulative principal payments than interest.

In addition, the lender gets the closing fees associated with originating the new loan (that’s the mortgage refinance). They get the most profitable period of time for the loan (where you gain the least equity and they gain the most interest). And then, as borrowers, we start their most profitable revenue stream all over again when we refinance or move. Who is winning here?

Now we know why banks sends so many refinance offers. It’s not really because they want to see us lower our monthly payments. What are the top selling points of these marketing campaigns? We can lower your rate. We can lower your monthly payments.

Now you understand why looking at just rate or monthly payments is a red herring. Unless your name is Jeff, Oprah, or Bill, you probably aren’t paying cash for your house. Or, maybe you want to take advantage of historically low mortgage rates. What are mere mortals to do?

Look at Your Potential Mortgage Refinance Like an Accountant

Run the numbers like an accountant.
Calculate time to be free of the debt.
Figure out how much less (or more) interest you will pay.
Bonus/Caveat: think about opportunity cost

First, run the numbers like an accountant: yes, you should consider your monthly payments. If you’re in a cash flow crunch (there is a pandemic on after all), freeing up several hundred dollars each month may be a huge relief. But understand that the short term relief comes with a long term cost. That’s why you need to look at more than just a lower rate/monthly payment.

Consider how much faster you can pay off the note. If you move from a 30 year to a 15 year note, depending on your original terms, you may get similar or smaller monthly payments and a shorter time horizon. For most people, eliminating the house payment eliminates the second biggest single line item in a family’s budget (hint: taxes are usually #1). And, anything that puts time back in your pocket aligns with our main life goal. “Time is the ultimate non-renewable resource”, after all.

Finally, look at how much less (or more) interest you will pay over the life of the new loan vs. your current note. If the change in interest rates is big enough, maybe you can justify refinancing into a new 30 year note. For us, we’re 10 years in, so it becomes really hard to make this criteria work because we’re mostly past the most expensive part of the mortgage now (smacks forehead).

Caveat/Bonus – Don’t Forget About Opportunity Cost

Don’t forget about opportunity cost. This is the counter example that could toss out all of the math and analysis we’ve talked about above — which is why it’s so important to mention.

The counter-example goes like this, “if you can do something else with the money that earns a higher rate of return for your risk tolerance, you could consider that instead.” This means, you might be able to refinance your mortgage into a 30 year loan at 3%, saving a few hundred dollars each month. If you can re-invest those dollars into something that returns more (e.g., a rental property earning 8%), you will have become the bank. You are now borrowing money at a low rate to invest it at a higher rate. And, that’s not a bad place to be.

Of course, there be dragons here too. The higher rate may come with more risk. And, this is why personal finance is … well… personal.

A Better Mortgage Refinance Calculator

One of the nice things about not trying to sell you mortgage products means we can tell it like it is. So we built a refinance calculator so you can compare two different mortgages to see if you can win on all 3 dimensions: monthly payments, time to freedom, and total interest paid to your lender.

Let’s walk through an example and then make the tool available. Consider our example from above: a $200,000 30 year mortgage at 4%. Let’s say the note started 1/1/2018. The borrower considers a couple refinancing scenarios.

Mortgage refinance to a new 30 year note at 3.25%
Mortgage refinance to a new 20 year note at 3.00%

Comparison of a 30 year note at 4% refinanced into a new 30 year note at 3.25%. Lower monthly payment and less interest over the life of the loan, but a longer time to pay it off.

In both cases, we’re holding the cost of refinancing fixed at 1.5% of the value of the new loan (although that is adjustable too). In the first scenario, the borrower has a lower monthly payment by about $228/mo. Because of the lower rate, they also save on interest over the life of the loan…not too bad. However, they’re pushing out the payoff date by almost 4 years. For some this is a great trade-off: more money in their pockets every month but slightly more time carrying debt.

Comparison of a 30 year note at 4% refinanced into a new 20 year note at 3.0%. Lower monthly payment and less interest over the life of the loan, but a longer time to pay it off.

On to scenario 2. What if the borrower chooses to go with a 20 year note at a slightly lower interest rate? They don’t get the same monthly savings…the new monthly payment is only $30/month less. However, they save over $60,000 over the life of the new loan. And, they are debt free 6 years earlier. That’s what I would look for in a refinance: accelerating my Speed to Freedom!

Coming soon! A mortgage refinance calculator upgrade that lets you have a shorter time horizon.