kchodorow

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”

Goals for 2019

Followup from last year’s post: Programming: I really dug into Pandas and not I feel pretty comfy with Python & Pandas. This year, I’d like to focus a bit more on stats and machine learning. Work-life balance: I am freakin obsessed with my job, which is terrific. But I also feel comfy taking days offContinue reading “Goals for 2019”

AST Financial: the dumpster fire of a company

As an employee at MongoDB for several years, I had a bunch of shares that MongoDB was holding for me when it went public which I had to get to my brokerage account to actually sell. It turns out that the company can’t just hand you your shares, they have to go through a transferContinue reading “AST Financial: the dumpster fire of a company”

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.

Staying out of trouble on Elastic Beanstalk

Editor’s note: devops always makes me cranky and Domino is in the doggy hospital (he’s okay), so have a rant about Elastic Beanstalk. This is my life: If you’re unfamiliar with Elastic Beanstalk: healthy is green, unhealthy is red, and grey is unreachable. Grey is the worst, because it’s inescapable: you can’t change the configurationContinue reading “Staying out of trouble on Elastic Beanstalk”