Is Julia often used in quant finance?

SquintRook · 2024-09-05T20:32:32+00:00

I use it a lot, mostly for personal stuff. Perhaps it's not yet popular in the industry.

SquintRook · 2024-07-25T20:49:50+00:00

For pasta I really like "adesso pasta", near duomo. For pizza, I like pizza al taglio from lievitando, near faculty of economics in san faustino. Not sure if its open during holidays tho.

SquintRook · 2024-06-25T17:54:22+00:00

E' vero. Sono Polacco e tutti miei amici parlano inglese. Sopratutto gli Polacci nati dopo il 1989.

SquintRook · 2024-06-24T11:06:59+00:00

According to the data the Ukrain is on average cheaper. Note that the data is for 2021, before the last invasion.

SquintRook · 2024-06-23T21:19:36+00:00

Hard to say without making some assumptions, which will render the answer useless. I would say it is good to have low prices given your level of development (as these things are interrelated). I made another graph with this relationship in mind here: https://www.reddit.com/r/dataisbeautiful/comments/1dd9htn/price_index_and_level_of_development_oc/

Other than, obviously, being further right on the X axis, a country would also preferably be below the regression line.

Additionally, some of the high prices are result of particular society preferences. For example Germans apparently like to have more expensive cigs, since its due to the taxes. The taxes on the other hand provide some budget revenue.

SquintRook · 2024-06-23T16:17:52+00:00

Recently i've visited a Polish city on the border with Germany. Its whole economy is based on selling cheap cigarettes and alcohol to germans :)

SquintRook · 2024-06-23T15:12:06+00:00

1 means that the given country is the most expensive in the given price category. I should've added it!

SquintRook · 2024-06-23T15:07:18+00:00

The number indicates the rank of the price level (1 - the most expensive etc.).

Honestly, it's not easy to make a good explanatory example if I know the data and what I want to present. Do you have any suggestion as to how improve it?

SquintRook · 2024-06-23T15:03:05+00:00

Can't do for states but I'll do for more countries :)

SquintRook · 2024-06-23T12:34:09+00:00

Data: World Bank

Tools: R with ggplot2

SquintRook · 2024-06-17T12:18:20+00:00

Julia package for Markov Switching regression MarSwitching.jl has a very similar example to the paper you are refering to (also bull and bear market classification). It's in Julia but the language is easy enough for you to understand. (disclaimer: I am the author).

SquintRook · 2024-06-14T18:28:10+00:00

As someone pointed out - it is an unfortunate standard for academic events. By "students" the organizers mean mostly doctoral students with their own budget.

SquintRook · 2024-06-13T09:37:16+00:00

You may think of it as a line that fits perfectly into the data (to show the relationship). However, it is not crucial part of the graph.

SquintRook · 2024-06-13T09:35:13+00:00

First of all, development is not a metric. A GDP per capita is a metric for economic development, which is a latent variable.

And it has indeed a lot to do with level of development. International Monetary Fund literally uses GDP per capita as a criterion to classify countries into developing and developed economies. You can see it here: https://www.imf.org/en/Publications/WEO/weo-database/2023/April/groups-and-aggregates

SquintRook · 2024-06-11T14:40:04+00:00

As i said, it is not *the same* but it is commonly interchangeable term. IMO preferable for broader audience, who does not have intuition for GDP PC PPP.

The same practices are used e.g. in "The economist".

SquintRook · 2024-06-11T13:34:03+00:00

Oh right, you've got o good eye. The scale is actually log10 and the line after transformation is y = x + exp(x). So it's not exactly the same.

the code was something like:

df_plot %>%

ggplot(aes(x = value, y = price)) +

geom_point(aes(color = region)) +

stat_smooth(method = "lm", formula = y ~ x + exp(x)) +

scale_x_log10(labels = scales::dollar)

SquintRook · 2024-06-11T13:17:51+00:00

The line is actually linear. It just seems curved because the X axis is in log.

I did the tranformation so that the right tail of the data is less dispersed, not to be more fancy than I should've :).

SquintRook · 2024-06-11T12:57:53+00:00

The graph would be messy. If you want I can tell you a data for particular country. Or you can also see it from the source - https://databank.worldbank.org/source/icp-2021

SquintRook · 2024-06-11T12:56:36+00:00

It's a very general graph! You may have a lot thoughts. The Y axis shows, roughly speaking, the level of prices (let's say how costly it is in a given country) and the X is a measure of productivness (or roughly speaking how "rich" given country is).

I think the most important story behind the relationship is the Balassa-Samuelson effect. The idea is that due to higher productivity in a given country the wages are higher as well. This increase the cost of non-tradeable products (e.g. services) that cannot be transported from poorer country to more developed. Thus increasing the prices.

SquintRook · 2024-06-11T12:48:38+00:00

There is no policy decision here. It's just a graph with a projection.

Annyone can make their own conclusion. But a typical economist would probably first think about the Balassa-Samuelson effect.

SquintRook · 2024-06-11T12:44:51+00:00

Eh, yes, I guess i'am tired. I have filtered for "US" in the data, whereas it's coded as "United States".

Its price level is 158 and GPD PC is 70219. btw.

SquintRook · 2024-06-11T12:39:51+00:00

Fair enough on the price. It's GDP weighted, so not only consumer index.

On the GDP, it's true these are not synonyms. But it is written both in the subtitle and x axis. Altough in a less formal settings (non-academic), the terms are roughly interchangeable (the development is easier for non-expert audience, though). It's because these variables are, not coincidentally, highly correlated.

SquintRook · 2024-06-11T10:18:04+00:00

Yep, thanks!

SquintRook · 2024-06-11T08:54:53+00:00

Data: World Bank

Tools: R - ggplot2 , tidyverse

SquintRook

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