I came across some social media posts about an upcoming visa to the UK that would allow recent graduates from the world’s top colleges and universities-UK graduates are not eligible for this specific visa- to gain temporary 2-3 year visas to work in the UK. This program sounds a little bit like the OPT visa in the US which is only open to graduates of US universities. This new program for the UK opens officially in May of 2022, more info at the UK’s Immigration Barrister, but they haven’t posted an official list of which colleges and universities.

Based on the requirements that the colleges and universities must rank in the top 50 of 2 of the 3 college rankings (THE, ARWU, and QS), I compiled a list of the colleges that as of April 2022 are likely to make the cut.

The official list will likely be different depending on how the UK adjusts the rankings, because there are quite a few UK colleges in the top 50 on each list as well as grad school only universities. But I wanted to just share what I personally found as of April 2022 by comparing each of the 3 rankings. Only 37 colleges appear on 2-3 lists based on what I looked at, and 20 of them are in the USA followed by China (including Hong Kong) with 4 . Here is the alphabetical list followed by a summary of the number by country:

• California Institute of Technology in USA qualified on 3 rankings: ARWU QS THE
• Chinese University of Hong Kong in China qualified on 2 rankings: QS THE
• Columbia University in USA qualified on 3 rankings: ARWU QS THE
• Cornell University in USA qualified on 3 rankings: ARWU QS THE
• Duke University in USA qualified on 2 rankings: ARWU THE
• Ecole Polytechnique Fédérale de Lausanne in Switzerland qualified on 2 rankings: QS THE
• ETH Zurich in Switzerland qualified on 3 rankings: ARWU QS THE
• Harvard in USA qualified on 3 rankings: ARWU QS THE
• Johns Hopkins University in USA qualified on 3 rankings: ARWU QS THE
• Karolinska Institute in Sweden qualified on 2 rankings: ARWU THE
• Kyoto University in Japan qualified on 2 rankings: ARWU QS
• Massachusetts Institute of Technology in USA qualified on 3 rankings: ARWU QS THE
• McGill University in Canada qualified on 2 rankings: QS THE
• Nanyang Technological University, Singapore in Singapore qualified on 2 rankings: QS THE
• National University of Singapore in Singapore qualified on 2 rankings: QS THE
• New York University in USA qualified on 3 rankings: ARWU QS THE
• Northwestern University in USA qualified on 3 rankings: ARWU QS THE
• Paris Sciences et Lettres – PSL in France qualified on 3 rankings: ARWU QS THE
• Peking University in China qualified on 3 rankings: ARWU QS THE
• Princeton University in USA qualified on 3 rankings: ARWU QS THE
• Stanford in USA qualified on 3 rankings: ARWU QS THE
• Technical University of Munich in Germany qualified on 2 rankings: QS THE
• Tsinghua University in China qualified on 3 rankings: ARWU QS THE
• University of British Columbia in Canada qualified on 2 rankings: QS THE
• University of California, Berkeley in USA qualified on 3 rankings: ARWU QS THE
• University of California, Los Angeles in USA qualified on 3 rankings: ARWU QS THE
• University of California, San Diego in USA qualified on 3 rankings: ARWU QS THE
• University of Chicago in USA qualified on 3 rankings: ARWU QS THE
• University of Hong Kong in China qualified on 2 rankings: QS THE
• University of Melbourne in Australia qualified on 3 rankings: ARWU QS THE
• University of Michigan-Ann Arbor in USA qualified on 3 rankings: ARWU QS THE
• University of Pennsylvania in USA qualified on 3 rankings: ARWU QS THE
• University of Texas at Austin in USA qualified on 2 rankings: ARWU THE
• University of Tokyo in Japan qualified on 3 rankings: ARWU QS THE
• University of Toronto in Canada qualified on 3 rankings: ARWU QS THE
• University of Washington in USA qualified on 2 rankings: ARWU THE
• Yale University in USA qualified on 3 rankings: ARWU QS THE

I was looking at my home's Redfin estimate chart, and the historical estimated property value was surprising when I noticed it said we overpaid by 10%. That was very surprising, since at the time several other units in our building were sold for the same price as what we paid. Plus, we purchased with a Redfin realtor and I would have remembered if there was so much of a difference between the estimated value on Redfin and the current price. I had originally thought that the historical value estimates represented the value that they thought it was worth on that date. For example, if it was Jan 2021, you would lock in an estimate and that was what would show up forever as the Jan 2021 estimate.

Redfin has been sending us an email with the estimate every month.

Lucky for us, we had signed up for Redfin's Home Reports a couple years ago which included a snapshot of the estimate at that moment, which is what I thought the graph originally represented. A lot of the emails also include a value for the percent change from last year or last month. Here's a plot of the results of those emails versus what was live on Redfin when I wrote this article.

Older Data is More Variable

Looking at my property as an example, there are some trends with more recent results being more consistent with the point-in-time estimates. The 2+ year old estimates are showing a relatively large amount of difference. An important fact to note is that the sale prices of comparable units in my building and neighborhood have been flat for this entire time duration. So it seems to me that their algorithm to pricing the estimates seems to trend towards painting a rosier picture of the market. The upward graph in the current price estimate does make me feel good, but it's really just fake.

Digging into the Details of the Change Since Last Year and Last Month

As I mentioned before, most of the emails contained an additional data point of change since last year or last month. None of those year-over-year or month-to-month changes was ever a negative, so I believe they must just omit the value if it isn't positive. Here is a chart with each email's data points plotted with the estimate from that month with a line that goes to the implied price based on the percentage change since last year or last month. These values (gray lines) are plotted next to the most recent Redfin Estimate.

The 2018's estimated values are all over the place with estimates ranging from $209k to $240k over a few months timespan.

Be a little cautious with the estimates

The values on Redfin can be useful, and I still use them frequently. But, this example has really highlighted to me how much these numbers can change over time on a whims notice. Now that I think about it, it's not too surprising to me that they restate their numbers historically as they update their data models. But what is really surprising to me is just how much the estimates can very month to month in a stagnant market.

I decided to look into which careers are the most rewarding early in your career. Most of the jobs aren’t a surprise with Software Engineers topping the list with almost 60k young adults under the age of 30 earning over $100k. This means about 21% of Software Engineers between the ages of 20-29 are making six figures annually. Here’s a treemap of the top jobs of 20-29 year old Americans who earn more than $100,000 per year.

I recently came across a dataset on Kaggle from a popular peer to peer lending company with data up to 2/2019–the start date was in 2007 but there weren’t that many loans from the early years. I’ve been reading other FIRE/personal finance bloggers touting more non-traditional investments, and I was a little bit interested to see the overall average performance of these kinds of instruments. Sometimes you never know if the bloggers are just pushing a product because it’s good or if they’re after ad money. So to find out, I decided to fire up R and run some quick analysis on the returns and my goodness they are very terrible.

36 Month Loans

Looking at 36 month (3 year) loans that have had at least 3 years between the start date and the data set’s end date, the returns are terrible. The only thing nice I can say is that at least it looks like you average a slightly positive return.

That total return is the total amount paid out over the life of the loan. A total return of 107.1% is basically an interest rate of 2.28% per year compounded each year. That’s pretty close to what an Ally CD would yield for the same period, which is pretty sad considering the amount of risk you’d be taking on to give out these loans to people. % Bad is the percentage of the loans that have negative statuses like charged off, grace period, or late.

How does this number work?

Okay so I was thinking maybe I made a calculation mistake or the data on Kaggle was bad, so I went over to this company’s website to get the official public stats. They don’t make sense to me either. This company only offers loans of 36 months (3 years) or 60 months (5 years). So I picked issue dates up to 2014, so all the loans are paid off or charged off–nothing is outstanding.

Looking Grade A loans, their website has total payments of $740,746,894 = $669,115,583 (principal payments) + $71,631,311 (interest payments).

They issued $686,112,100 in loans. Simple division puts this return at $740,746,894 / $686,112,100 = 1.0796 meaning they got paid 7.96% more for loans that took 3 to 5 years to complete.

How in the heck do you get an annualized return of 5.14% over 3 to 5 years when the total return is 7.96%? None of this makes any sense to me, but maybe my untrained eye has just grossly misunderstood the basic figures on the dashboard.

I recently got a new computer, and decided to go back to the Microsoft Home Use Program to get a new key to get Excel installed on my new computer. Much to my surprise they’ve completely gutted that program and the package now costs $70 / year for one license or $100 / year for 6 licenses. This is a huge increase when it was only $20 for a permanent license as recently as 2018. Now my old computer is completely gone, so I kind of gave up on rescuing my old license some how.

Free Alternatives : LibreOffice, Rstudio, and Google Sheets

As you know from this website, my typical data analysis toolkit is Excel, R and PHP/Javascript, so I’m currently exploring the open source options. So far, I’m really getting used to LibreOffice. LibreOffice is related to OpenOffice, but has been kept more up to date than OpenOffice. It looks like OpenOffice has basically been frozen in time for like 5+ years and really isn’t a great option at this point. A lot of the functions are the same as in Excel, but the only bad part about LibreOffice is that it feels a lot like using Excel 2003 from the UI perspective. It just isn’t as slick and fluid as the newer versions of Excel, but it does seem to be getting the job done. Pivot tables work, and the structure is very similar to how they are used in Google Sheets.

I’ve also started to lean a little bit more heavily on R (specifically RStudio) to do exploration via coding vs spreadsheet style. It certainly has been a learning curve, but I also feel like R is a marketable skill. I’ve also been using Google Sheets quite a bit for smaller spreadsheets, but Google Sheets feels a little clunky if you try to use a sheet that’s large.

Is the Microsoft Home Use Program worth it for some people?

Yes, it is worth it if you are going to use the 1 terra byte in free cloud back up. If you’re a light user of Docs, Excel and PowerPoint, LibreOffice or Google Docs should cover you pretty well for free.

If you’re trying to run a business from home, I could also see it being useful in situations where you’re going to be sharing files with clients or contractors. I can see it being important to make sure that your files are formatted perfectly across computers. For me, since my hobby data analysis work isn’t really shared via Excel, I don’t think that it’s worth an extra $70 / year for that.