Kyle Piira

Tag: finance

  • How I organize my budget in YNAB

    I’ve been using YNAB for a few years now, but the way I organize my budget today is very different from how I started.

    Before YNAB, I used Mint. Mint encouraged a fairly traditional approach to budgeting: transactions were automatically sorted into categories like groceries, restaurants, rent, entertainment, and transportation.

    When I moved to YNAB, I initially tried to recreate that structure. It didn’t work particularly well for me.

    The problem was ambiguity. I’d buy something that didn’t fit neatly into any existing category, so I’d create a new one just for it. Other purchases could reasonably belong to two or three categories, forcing me to make arbitrary decisions about where they belonged.

    After a few months, I scrapped the whole thing and started over.

    The system I came up with has now remained mostly unchanged for two or three years. Instead of trying to create a category for every conceivable type of purchase, I organize spending around a small number of broad concepts with rules that tell me where almost any transaction belongs.

    Bills: Monthly and Non-Monthly

    The first meaningful distinction is recurring expenses.

    I have two category groups:

    • Bills — Monthly
    • Bills — Non-Monthly

    Monthly bills include things like rent, home internet, my cell phone, and streaming subscriptions. Non-monthly bills cover recurring expenses that happen less frequently, such as my annual Amazon Prime membership or an insurance premium.

    I use YNAB’s Refill Up To targets for these categories. I generally set the target slightly higher than I expect the bill to be. Any small surplus rolls over, and the following month YNAB only asks me to contribute enough to bring the category back to its target.

    This works well because these aren’t really things I’m “saving” for indefinitely. There’s simply an amount of money I want available when the bill arrives.

    Experiences

    My fun spending lives under a category group called Experiences.

    Most of the time, there’s just one permanent category inside it, also called Experiences. Restaurants with friends, movies, bowling, and other recreational activities all come out of this category.

    I deliberately don’t distinguish between restaurants, movies, entertainment, and similar categories. What matters to me is that I’m spending the money on an experience.

    Large planned experiences work a little differently.

    For example, I currently have a trip to Universal Studios Orlando coming up. Rather than dumping the money I’m saving for the trip into the generic Experiences category, I created a temporary Universal Orlando Trip category. I can save specifically for the trip, pay its expenses from that category, and see how much of the trip budget remains.

    When the trip is over, I’ll merge the category back into Experiences.

    That gives me the advantages of detailed budgeting when I’m planning something expensive without permanently cluttering my budget with categories for every vacation I’ve ever taken.

    Experiences uses a Monthly Savings Builder target. That’s an important distinction from my bills.

    If I budget $500 for experiences one month and only spend $300, I don’t want YNAB to tell me that I only need another $200 next month. I want to add another $500. The unspent $200 represents additional money I can spend on experiences in the future.

    In other words, underspending isn’t a reason to reduce next month’s allocation.

    Services

    My next category group is Services.

    The basic rule is simple: if I’m paying someone to do something for me, and it isn’t primarily a recreational experience, it’s probably a service.

    That includes things like haircuts, medical care, movers, and transportation.

    Transportation is one of the biggest categories here because I don’t own a car. Subway and bus fares, Uber and Lyft rides, plane tickets, and long-distance train tickets all go into Transportation.

    There is some unavoidable ambiguity here. A plane ticket to Orlando is simultaneously transportation and part of my Universal trip.

    I’ve decided that consistency matters more than finding some philosophically perfect answer. If something is transportation, I categorize it as Transportation.

    If the transportation is part of a larger trip I’ve been saving for, I can move money from the trip’s category into Transportation to cover it. The transaction itself still gets categorized consistently.

    Targets within Services depend on the nature of the expense.

    Transportation uses Refill Up To because spending less on transportation this month doesn’t mean I expect to spend correspondingly more next month.

    Medical, on the other hand, uses a Monthly Savings Builder. Medical spending can be sporadic and expensive, so I want unused money to accumulate over time.

    Goods: Consumables, Durables, and Intangibles

    Goods were one of the biggest sources of frustration in my original Mint-style budget.

    There are effectively infinite kinds of things you can buy. Trying to maintain separate categories for clothing, electronics, furniture, household supplies, groceries, toiletries, and every other conceivable product creates endless edge cases.

    I eventually settled on three categories that can accommodate almost any good:

    Consumables are physical goods that are used up relatively quickly. Groceries, toilet paper, toothpaste, laundry detergent, dishwasher detergent, and similar purchases belong here.

    Durables are physical goods intended to last. Furniture, televisions, smartphones, laptops, and similar purchases go here.

    The boundary between the two is a little fuzzy as almost everything eventually wears out, so I use a rough one-year rule. If I expect something to last less than a year, it’s probably a consumable. If I expect it to last more than a year, it’s probably a durable.

    Intangibles are goods that aren’t physical at all. Buying an app for my phone, a digital movie, or a downloadable Xbox game would fall into this category.

    Like Experiences, I sometimes create temporary categories for particularly large purchases.

    If I were saving for a new iPhone, for example, I might create an iPhone category and contribute money to it for several months. Once I bought the phone, I’d merge the category into Durables.

    All three of my permanent Goods categories use Monthly Savings Builder targets.

    Goods spending is inherently bursty. I might go several months without buying a significant durable good and then suddenly need to replace a broken television. I want the money I didn’t spend during those quiet months to accumulate so it’s available when that happens.

    Giving

    Giving has two categories: Charity and Gifts.

    Charity covers donations to nonprofit organizations. Gifts covers money I spend on friends and family for birthdays, Christmas presents, and similar purchases.

    Although both represent giving money to someone else, their spending patterns are different.

    My charitable donations are relatively predictable and largely automated, so Charity uses a Refill Up To target.

    Gifts are much more irregular. There might be relatively little spending for months followed by a cluster of birthdays or an expensive Christmas season. Consequently, Gifts uses a Monthly Savings Builder so money accumulates during quieter months.

    Domain Names

    Finally, I have one highly specific category group: Domain Names.

    Each domain I own gets its own category with a target based on its renewal date and price. YNAB gradually sets aside enough money so that the renewal is fully funded when it arrives.

    Technically, I could put these under Non-Monthly Bills. They’re recurring annual expenses, after all.

    But I own enough domains that doing so would clutter up the rest of my bills. Giving them their own group keeps things cleaner.

    The Principle Behind the System

    The biggest lesson I’ve taken from designing this budget is that categories don’t need to perfectly describe every purchase.

    My first budget that mimicked the categories I was used to in Mint was overly specific and it resulted in nearly 120 unique categories. It made it more difficult to try to figure out what was the correct category for each transaction.

    My current system is deliberately broader.

    A physical item is a consumable or durable. A digital item is an intangible. Paying someone to do something is generally a service. Doing something for fun is an experience. Giving money away is charity or a gift. Recurring obligations are bills.

    There are still edge cases. A plane ticket for a vacation could reasonably be Transportation or Experiences. Rather than trying to eliminate every ambiguity, I’ve established rules and apply them consistently.

    For expenses with a relatively stable ceiling, I use Refill Up To. For expenses where I want underspending today to increase my purchasing power tomorrow, I use Monthly Savings Builder.

    And when I’m saving for something unusually large like a vacation or an iPhone, I temporarily give it its own category and merge it into the appropriate permanent category afterward.

    The result is a budget that gives me detail when that detail is useful without requiring me to maintain hundreds of categories forever.

    After several years of using it, that’s probably the strongest evidence I have that the system works: I feel no need to redesign it.

  • The Case for Prediction Markets (Even If People Hate Them)

    I’ve been thinking a lot about prediction markets lately. And honestly, I keep running into people who really don’t like them. Not just mild skepticism, more like “these should be banned” or even outright illegal. That reaction kind of bums me out.

    I’ve been into the idea for a long time, even before there were any big platforms. Back when it was mostly just theoretical, before Polymarket, Kalshi, all that, I thought it was a really elegant concept. It just made sense. We already know markets can be pretty good at aggregating information. The stock market, for example, does a decent job pricing in everything people know (or think they know), and that usually leads to pretty accurate valuations. Way better than small private markets where fewer people are involved and less information gets reflected.

    So if you start from the basic problem, “we want to predict the future,” it feels natural to look for systems that are good at combining lots of information. Prediction markets fit that really well. They’re kind of like a general-purpose forecasting tool. You can point them at almost anything.

    One example I really like is weather markets. Kalshi has some live ones where you can predict things like temperature or whether it’ll rain on a specific day. That’s a case where prediction markets actually feel useful in a very direct way. Everyone cares about the weather. You’re planning a weekend, a trip, even just tomorrow, having a solid sense of what’s coming matters.

    Sure, you can check a weather app or watch the forecast. And they’re usually fine. But the people trading in a weather prediction market are pulling from all of that too, plus their own models, their own insights, maybe even niche data sources. They’re constantly updating their beliefs because there’s money on the line. And that pressure forces information into the price.

    Over time, the people who are actually good at predicting, like really good, end up with more influence because they win more and can trade more. So the market kind of self-selects for accuracy. The end result is a price that reflects a very informed, constantly updated probability. In theory, it’s about as good an estimate as you can get.

    That’s kind of amazing, if you think about it. A single number that summarizes everything people collectively know (and believe) about some future event. It feels like a genuinely powerful tool. Which is why it’s frustrating to see people want to shut it down entirely, it feels like throwing away something valuable.

    Now, to be fair, there are criticisms.

    One that comes up a lot is insider trading. People don’t like the idea that someone with privileged information could profit off it. And yeah, I get why that feels unfair, especially since we regulate that heavily in stock markets.

    But prediction markets aren’t really about fairness in that sense. They’re not trying to give everyone an equal shot. If that’s the goal, there are plenty of games for that, go play roulette or something. The whole point here is accuracy.

    From that perspective, insider trading isn’t a flaw, it’s kind of the point. If someone knows something the market doesn’t yet reflect, you want them to trade on it. That’s how the information gets incorporated into the price. It actually makes the market better as a forecasting tool.

    Another criticism is that this is basically just gambling with extra steps. Especially with things like sports or politics. And yeah, I think there’s something to that. Gambling can be a real problem for some people, and a lot of these markets, especially sports, do look a lot like betting.

    Honestly, I don’t think sports prediction markets add much value. Predicting who wins a game doesn’t really matter in any meaningful sense. It’s entertainment. So if people want to clamp down there, I’m not too bothered by that.

    Politics is a bit more nuanced. There’s arguably some real value in forecasting elections. Markets can sometimes pick up on signals that polls miss. But even then, I could see the case for tighter rules or guardrails.

    Where I think we’d really lose something is in the more practical, information-heavy markets, like weather, economic indicators, maybe even things like supply chain risks or disease outbreaks. Those feel genuinely useful. They help people make decisions.

    So yeah, I don’t think prediction markets are perfect. But as a tool for aggregating information and forecasting the future, they’re kind of incredible. It would be a shame to throw that away entirely.

  • I’m Done With Bilt

    Bilt dropped details yesterday about their new credit cards. I’ve been using the original Bilt card for a little over a year, mostly for one very specific reason, and after reading through the announcement I’m pretty confident I won’t be switching to any of the new ones.

    I’ll probably just close the account at the end of the month and go back to paying rent directly out of my bank account.

    The original Bilt card worked because it did one thing unusually well. It let you pay rent with no fee and earn points on it. You got an account number and routing number, gave that to your landlord, and rent came out like it was a checking account. One point per dollar on rent. Simple.

    My rent is about $2,000 a month, so that came out to roughly 2,000 points every month. That’s not a ton of money, maybe $20 in value, but it was enough to matter in small ways. I mostly used the points for Lyft rides. Not flights, not aspirational travel redemptions, just “cool, this ride is free.” A couple of those a month was nice. It felt like getting something back for an expense that otherwise just disappears.

    There was a catch, though. You had to make at least five non-rent transactions per month to earn the rent points. And I never wanted to actually use the Bilt card for real spending. It wasn’t competitive with my other cards, and I didn’t feel like thinking about it.

    So I did what a lot of people probably did. I gamed it. I put five recurring charges on the card: iCloud storage for 99 cents, a few other subscriptions in the $5 to $10 range, and called it a day. Total monthly spend outside of rent was maybe $30. Rent was thousands. Points flowed.

    From Bilt’s perspective, I was almost certainly a terrible customer.

    Which is why none of this is surprising.

    The new cards are clearly designed to stop people from using the product the way I was using it. Under the new setup, if you want to earn points on rent, you need to spend a lot more elsewhere on the card. Roughly 75% of your rent amount, from what I can tell. If your rent is $2,000, you need to put about $1,500 of other spending on the card every month.

    That’s where it completely falls apart for me.

    I’m not interested in rerouting $1,500 a month away from cards I already like just to preserve a rent reward setup that used to be effortless. Five token transactions was annoying but manageable. Rebuilding my entire spending strategy around one card is not.

    And honestly, that’s fine. This feels very intentional. Bilt doesn’t want people who do the bare minimum, harvest rent points, and disappear. I was exactly that person. I don’t blame them for tightening things up.

    But it does mean I’m done.

    The new cards might be great for people who want a primary spending card and like the Bilt ecosystem. I’m not that person. I just wanted the rent thing to keep quietly working in the background, and it no longer does.

    So I’ll take the small loss and go back to paying rent the old-fashioned way. No points, no Lyft credits, no Wells Fargo relationship I didn’t really want in the first place. It was fun while it lasted.

    Adiós, viejo amigo.

  • The relationship between college enrollment and tuition

    I spent my evening determining a reasonable expected growth rate for future college tuition. The graph below displays the correlation between college attendance rates and tuition. While I’m not concluding causation from the data, it seems plausible that increased enrollment rates have led to higher tuition costs. With enrollment now peaking at around 100% and appearing to decline, I anticipate a lower future growth rate. The historical growth rate was approximately 6%, but I’m considering a rate closer to 2% going forward.

    In the data attendance rate is defined as the number of people enrolled in college divided by the number of people aged 18-22 in the United States.