As Einstein (maybe) said, compounding interest is the eighth wonder of the world. In the previous posts in this series, we used a very linear benchmark: 4% off of the amount contributed forever. However, this is a weird way to benchmark results. Imagine you and friend (call him Baelish) are both investing and comparing results.Continue reading “Part 4: compounding returns”
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A multi-stock portfolio: comparing returns
The last posts have discussed portfolio performance with a very boring portfolio: one stock! Things get more interesting when there’s more than one stock to compare. Let’s say we have a two stock portfolio now: SPY (as before) and DOCU (Docusign). We’ll combine the two tickers into one dataframe: Now that things are getting moreContinue reading “A multi-stock portfolio: comparing returns”
Show me the money: tracking returns
Last post went over building a very simple portfolio tracker to show a portfolio’s performance over time. However, it would be easy to trick myself: “My portfolio value is going up over time, I’m doing great!” But I’m also adding money to my portfolio over time, so that money shouldn’t “count” in terms of performance.Continue reading “Show me the money: tracking returns”
Building a (very simple) portfolio tracker with pandas
All of these graphs were created in Colab. I’ve actually never found a commercial product that does everything I want, so I figured I’d build one up in a series of blog posts. We’ll see how many I get through! 🧵👇 First, we’ll get SPY’s stock history with pandas_datareader. This returns a dataframe that looksContinue reading “Building a (very simple) portfolio tracker with pandas”
The stock market is going down
Not the stocks, mind you, but the market itself. There are less than 4,000 companies listed, and new companies have less and less appetite for going public. Conversely, there are over 8,000 private-equity-backed companies in the US, and growing. There are a couple of problems with the stock market mouldering. One is that this isContinue reading “The stock market is going down”
Losing money sucks – the mathematics of loss aversion
There’s a lot of research on loss aversion: how bad people feel when they lose $50 vs. how good they feel good about gaining $50. This research is kind of taking an absolute value of emotion, positive or negative. We can represent this with emoji equations: 😀 == 😫 (large-magnitude happiness or sadness) 🙂 ==Continue reading “Losing money sucks – the mathematics of loss aversion”
The surprisingly complex math behind startup equity and taxes
Taxes for employees at startups are weird and can vastly change the amount you make. To illustrate why, let’s take a simple example. Suppose we have a group of early employees at a startup, we’ll call them the Unicorn Inc. Mafia. They’re all fresh out of college and managed to get through it without anyContinue reading “The surprisingly complex math behind startup equity and taxes”
Thinking with Pandas
You can see and run all of my work for this blog post at Colabratory. Pandas is a Python library for manipulating data. Wrapping my head around it took a while: I’ve been using it for ~6 months and I’m still learning how to use it “right.” It uses all kinds of syntactic sugar toContinue reading “Thinking with Pandas”
GV
Quick update: I’m now a partner at Google Ventures! I’m still doing engineering (although I would love to hear about it if you know about any cool startups I should check out) and I’m really enjoying being back at Google.
The thing about renting an apartment in NYC
There’s a lot of weird stuff about NYC real estate and this post attempts to cover some of the things that I’ve experienced. I’ve spent years renting apartments in NYC, mostly from rather small-time landlords with pre-war, rent stabilized buildings. If you’re looking for luxury rentals in new construction, a lot of this advice probablyContinue reading “The thing about renting an apartment in NYC”
Kristina Chodorow's Blog 