One of the big benefits of polars over pandas is not dealing with the constant index nonsense. Can’t tell you all of the issues I had as a beginner with pandas trying to debug silly index errors.
Having worked in both, there is a huge number of really smart people who turn down offers to work in quant shops. And people really underestimate how much tech will pay top researchers/overestimate how much the average quant makes.
I did work in the industry briefly and can confirm it is actually full of people who would post a comment like this. Just in case anyone needed another reason to avoid it!
Work on real problems. Try to make real people's lives better and happier. There are real problems in finance but my feeling was it's all very simple and solved decades ago, now it's just pointless complexity that isn't solving anyone's problems. I recommend John Kay's Other People's Money for a primer on what finance is actually good for and where it's gone wrong.
The real big problem in finance IMO is digital cash. Bitcoin started out trying to solve that problem, and there are still some people in the community interested in it, but it's mostly of interest to the finance guys now. Just another "instrument" in their "portfolios".
> Work on real problems. Try to make real people's lives better and happier. There are real problems in finance but my feeling was it's all very simple and solved decades ago, now it's just pointless complexity that isn't solving anyone's problems. I recommend John Kay's Other People's Money for a primer on what finance is actually good for and where it's gone wrong.
If the last few years have taught me anything it's that a large % of the population will actively aim to make their own lives worse long term because they are told lies. What benefit is there really in trying to undo their own self-inflicted damage.
It’s a bet on the continued existence, and willingness/ability to honor its obligations, of the US federal government.
If that bets goes bad, the typical investor in Treasuries has perhaps bigger problems to worry about, but it’s still a bet IMO (and one which will inevitably eventually go bad).
1. Interest rates can be negative
2. Volatility reduces the average. Take an example of +10% then -10% (1+0.1)*(1-0.1) = 1 - 0.1² = 0.99 < 1. It's due to the "log normal returns"
Not really. Today's mediocre code is tomorrow's technical debt. LLMs often inject subtle bugs or misunderstand the context they're being used in and have to be badgered into respecting the parameters of requests.
Would you rather write code yourself, or ask a first-year student to write it for you while you watch over their shoulder and tell them to go back and try again every time you notice a mistake? Which of these do you think is faster and better in the long run for the quality of your codebase?
