u/Choice_Number3711

Hi

The API for Kalshi/Polymaket is a bit confusing.

I was wondering if anyone could guide me as to how to get US Macro prediction data from either one of the platforms.

Thanks

I started recently at a small shop. There isn't much of a senior bench to learn off and I came in from a stats and data science background rather than a pure maths or physics one. So I'm partly teaching myself the domain as I go(mainly the financial aspects but some new statistical approaches that I'd never heard of before too). I use a mix of Python and R.

I use Claude in VS Code most days. It's fast, but I've noticed I can ship something that works without being able to defend every line of it. That feels like a bad habit to be forming this early, especially when I'm still filling gaps in the underlying material.

For people actually working in the field:

• Do you use LLMs day to day, or is it restricted where you are?
• Where do you draw the line? Boilerplate and plumbing yes, model logic no? Somewhere else entirely?
• How do you make sure you actually understand the output instead of accepting it because the backtest ran clean?
• What are you doing outside of work to stay ahead of the tool rather than dependent on it?
• Finally, if you could go back 5-10 years(or the time you started in this field), what guidance would you give to your younger self so as to develop better skills and understanding)

I'd rather build the right habits now than find out in three years that I can't work without it and have not built the right foundations.

Thanks :)

I used to hate coding anything and relied on SQL, Excel, Power BI, Tableau and other software like JASP, jamovi etc. for doing anything with data. I didn't like the way Python dealt with data analysis and it seemed unintuitive.

Then I found R, RStudio and CRAN. That was the turning point. I actually started enjoying writing code and I could handle the whole pipeline myself, from data cleaning, ETL to beautiful plots, .qmd reports, Shiny dashboards. R4DS did more for my statistical thinking than any course I've taken, mostly because the libraries made it so easy to just try things.

However, due to recent requirements (specifically having to work in the quant field), Python has become more of a necessity, while R is used mainly for one-off analysis and limited statistical modelling. The main heavy lifting is done in Python and many of my co-workers also prefer it to R.

I've been able to suck it up a bit and use Claude/ChatGPT to help me code. While I do try to understand what the code is doing, having spent so long learning to code in R and knowing the ease with which it can be done there makes me reluctant to learn Python.

Now, coming to the question: any R users who've pivoted to Python and consider themselves competent in it, how did you learn it having used R before? What would you tell someone like me so I can pick it up quickly and get the benefit of knowing both languages (and also not feel left out when it comes to coding in Python... machine learning and deep learning have a more mature ecosystem there and I don't want to be left out of it if I have to start using them in my current work)?

Thanks!

My background is in Math/Stats fyi

What are some good resources to primarily learn Financial Risk Analysis techniques while, on a secondary note, learning how to apply them in R?

I am looking for specific libraries, books, and tutorials that can help someone like me....knowing nothing about Financial Risk Analysis but competent in R to learn these concepts.

The primary focus is on learning the concepts. An added bonus would be to know how to implement them in code. My focus is on R because I feel more comfortable using it given my background in Statistics. However, R is not a strict necessity since Python would also do if the situation requires it.

Thanks!

What are some good resources to primarily learn Financial Risk Analysis techniques while, on a secondary note, learning how to apply them in R?

I am looking for specific libraries, books, and tutorials that can help someone like me....knowing nothing about Financial Risk Analysis but competent in R to learn these concepts.

The primary focus is on learning the concepts. An added bonus would be to know how to implement them in code. My focus is on R because I feel more comfortable using it given my background in Statistics. However, R is not a strict necessity since Python would also do if the situation requires it.

Thanks!

What are some good resources to primarily learn Financial Risk Analysis techniques while, on a secondary note, learning how to apply them in R?

I am looking for specific libraries, books, and tutorials that can help someone like me....knowing nothing about Financial Risk Analysis but competent in R to learn these concepts.

The primary focus is on learning the concepts. An added bonus would be to know how to implement them in code. My focus is on R because I feel more comfortable using it given my background in Statistics. However, R is not a strict necessity since Python would also do if the situation requires it.

Thanks!

What are some good resources to learn Financial Risk Analysis techniques while at the same time learn how to apply the same in R.

Any specific libraries, books, tutorials that can help a someone like me (knowing nothing in Financial Risk Analysis but competent in R) to learn the aforementioned.

Thanks!

https://preview.redd.it/bli1xu6zsc9h1.png?width=1918&format=png&auto=webp&s=0c965023214d10b3058887f945908135e41ed9b2

Hey everyone

Hoping someone here has been through this before.

I'm an international postgrad student at UniMelb. I've had a paper accepted at an academic conference in Australia in September. It's a domestic trip (interstate, not international) so total costs (flights + early bird student registration + 2 - 3 nights accommodation + meals) will probably come in the ballpark of $1.8 to 2.2k......not something I can comfortably eat as an international student.

Trying to figure out what funding I can realistically apply for. A few specific questions would really appreciate any pointers:

1. Which UniMelb travel grants are real options for students? I keep seeing mentions of faculty-level travel grants and central Graduate Research Hub grants but not sure which actually fund coursework or research masters as opposed to PhDs only.
2. Do international students get treated the same as domestic for these grants or are there separate eligibility rules ?
3. For people who've been through it: what is the turnaround time? Conference is mid September so I'm trying to time the application properly without missing the window.
4. Any external pots (e.g discipline aligned society bursaries, ECR grants, anything else) people have used to top up conference travel?

Some context: I'm applying for this independently rather than via a supervisor's research grant, so I'd be the named applicant. First conference presentation, want to do it properly without going into debt over it (hopefully :| ).

Cheers! Any help massively appreciated.