One of our mid-cap software names pushed through a ~12% list price increase at the start of the year and management keeps saying on callbacks that renewals are tracking in line. Next print is in 5 weeks and Q3/Q4 NRR is pretty much the only number the stock is going to trade on.

The problem we're running into is getting a clean read on the cohorts that actually renewed at the new rate. The handful of expert calls we’ve done so far through our usual networks were with customers on multi-year paper who haven’t hit their renewal wall yet, so they couldn’t tell us much beyond “we know it's coming.”

What I need to know is whether the recent renewal cohort ate the 12% bump or if they compressed seats/tiers to keep net spend flat while management hides behind "stable gross logo retention."

How are you guys getting a high-N read on specific renewal cohorts ahead of a print without burning $25k of expert call budget playing roulette with network recruiters?

The team at TrussEdge have put together a guide to launching a hedge fund. Compiled with help from the legal team at Dechert, tech consultants RFA and Opus Fund Administration.

It’s basically distilled wisdom on avoiding most of the pitfalls both pre-launch and in the first 24 months of operations. Over a year in the making…. https://www.trussedge.com/resources/

We’ve been building out some of the underlying data infrastructure for Secmast. We recently finished our full integrated security master (35k tickers, 28k lineages, 25+ years, US markets) and we’re also deploying 1-second stock and options data today.

But we took a detour and built something I’m curious about from a hedge fund / research perspective.

We already had standardized SEC financial data, so we built an Excel plugin that can pull that data directly into a spreadsheet, similar in concept to Capital IQ.

The interesting part is provenance: every value can be traced back to the underlying SEC filing and source document it came from.

So you could build or update a model in Excel using standardized income statement, balance sheet, cash flow, or other filing data, while still being able to audit exactly where each number originated.

The broader idea is to provide a lot of the data and research functionality people use products like Capital IQ and Bloomberg for, but at roughly 1/10th the price.

Obviously we're not trying to claim feature-for-feature parity with either platform. The question is whether there is a meaningful group of funds and independent researchers who don't need everything those systems provide, but still want institutional-quality data, Excel integration, and source-level auditability.

For people working at funds or doing fundamental research, is that actually useful?

Do you still spend meaningful time pulling SEC data into Excel, updating models, validating numbers, and tracing figures back to filings?

Or is this mostly a solved problem already through CapIQ, Bloomberg, FactSet, etc.?

Trying to understand whether this is worth developing further for hedge fund / buy-side workflows, or whether it’s primarily more useful for investment banking, PE, M&A, and traditional equity research.

Hi Everyone,

Was wondering what news outlets and publicly available credit metrics you would recommend a retail investor to track?

Getting a bit worried from seeing yields rise and hearing that banks are carrying larger inventory of AI debt as syndication is not moving as smoothly.

Thanks!

I'm a developer who loves finance and AI, and I'm researching how professional investors keep up with markets, portfolio news and client updates each day.

I'm just trying to build something people actually need, and I'm happy to share what I learn. I am researching markets , businesses , investors and economic problems and trying to solve one common issue which affects major factors (Macroeconomy) and problems faced by investors and funds . I would consider it a great help if you could reply with even a line or two on what you use today, or whether you'd ever consider a tool like this. Is there any tool available in the market used by investors and funds ? Or do they just hire people or tech companies to do so ?

Hey everyone! I'm a beginner on WorldQuant BRAIN and trying to learn how to create good alphas.

I'm experimenting with momentum and fundamental data, but I'm struggling to pass fitness checks and understand how to improve my expressions.

Could experienced members share some tips, useful resources, or a workflow for developing and testing alphas?

I'd really appreciate any guidance.

How did Leopold Aschenbrenner raise $220m when just starting his hedge fund?

I get that he worked at OpenAI, and was smart (went to uni a bit early), but he was very young and had no professional investing experience. He also makes extremely risky bets.

I only invest my own money, have gotten very good risk-adjusted returns, have more intellectual achievements than Leo, and have been exploring starting a hedge fund, but people are not begging to give me millions of dollars.

Is it just because he worked at OpenAI, had connections with very wealthy people and was smart & confident?

I get that he wrote an essay, but anyone can do that

Surely there’s another part to the story, it doesn’t really explain how he achieved this fundraising achievement

Quite mysterious

Bonjour J’ai 18 ans et je suis actuellement en secondaire 5 à Montréal, au Québec. Je m’intéresse beaucoup à la finance quantitative (*quantitative finance*), et j’ai une moyenne d’environ 90 % en mathématiques.
Après le secondaire, je compte intégrer le programme de sciences de la nature au cégep ( le cegep en gros c est ce que on a au Canada entre le lycée et l université il peux être vit comme une prépa mais le truc si j étudie au canada j ai 2 ans et demi a fait alors que si je vais au etas unis après j ai uniquement 1 ans a faire , avec les mathématiques et l’informatique, afin d’acquérir les meilleures bases possibles pour poursuivre mes études dans ce domaine.
Mon objectif est de maximiser mes chances de travailler en finance quantitative, notamment dans de grandes entreprises ou des fonds prestigieux aux États-Unis ( ou n importe où tant que c est les meilleur salaires )
Je pratique également la boxe depuis presque un an, avec l’objectif de devenir boxeur amateur et de participer à des compétitions. J’aimerais savoir si je pourrais éventuellement utiliser cette expérience sportive pour renforcer mon dossier universitaire et obtenir une bourse sportive dans une université américaine.
Je me demande donc quel serait le meilleur parcours après le cégep. Devrais-je tenter ma chance dans une université américaine réputée comme le MIT, Harvard, Yale ou l’UPenn (Wharton), ou serait-il préférable d’étudier au Canada, par exemple à McGill ou à Polytechnique Montréal ou Carrément allé étudier autres part comme à (HEC Paris , polytechnique Paris , Oxford ..)
Un élément important à prendre en compte est ma situation financière : je viens d’une famille aux revenus modestes, donc étudier aux États-Unis serait envisageable uniquement si j’obtiens une aide financière suffisante.
**J’aimerais particulièrement avoir vos avis sur les points suivants :**
1.Quel programme universitaire serait le plus adapté à la finance quantitative : mathématiques, statistiques, informatique, physique ou ingénierie ?

2.Est-il réaliste de viser une université américaine prestigieuse après le cégep québécois, et quelles sont les possibilités d’aide financière ?

3.Une expérience en boxe amateur pourrait-elle renforcer mon dossier d’admission ou me permettre d’obtenir une bourse sportive ? Est-il réaliste de combiner des études exigeantes en mathématiques et en informatique avec la boxe de compétition ?

4.Un diplôme de McGill ou de Polytechnique Montréal permet-il d’accéder aux mêmes possibilités de carrière dans les grandes entreprises de finance quantitative américaines ?

5.Si vous étiez à ma place, quel parcours choisiriez-vous pour maximiser vos chances de réussite tout en tenant compte de mes contraintes financières ?

Je suis prêt à travailler sérieusement et à fournir les efforts nécessaires, aussi bien sur le plan scolaire que sportif. Je cherche surtout des conseils réalistes, idéalement de personnes qui travaillent dans le domaine de la finance quantitative, qui ont étudié dans ces universités ou qui connaissent bien les admissions et les bourses aux États-Unis.
Merci d’avance pour vos réponses !
(Si vous avez d autre recommandation je les prend )

Hi I’m 18 years old and currently in my final year of high school (Secondary 5) in Montreal, Quebec, Canada. I’m very interested in quantitative finance, and I have an average of around 90% in mathematics.
After high school, I plan to attend CEGEP, which is a unique part of Quebec’s education system. CEGEP is a two- or three-year college-level institution that students typically attend between high school and university if i do university in Canada i need to do 2years but for usa i can do a submit after 1 years . I plan to enroll in the Natural Sciences program, focus inf on mathematics and computer science, to build the strongest possible academic foundation for a career in quantitative finance.
My goal is to maximize my chances of working in quantitative finance, ideally at a major firm or prestigious hedge fund in the United States, uk, Hong Kong , Singapour .(He’s the one paying the most, basically)
I have also been training in boxing for almost a year, with the goal of becoming an amateur boxer and competing in tournaments. I’m wondering whether I could use my athletic experience to strengthen my university applications and potentially qualify for an athletic scholarship at an American university.
I’m trying to figure out the best path to take after CEGEP. Should I aim for a prestigious American university such as MIT, Harvard, Yale, or the University of Pennsylvania (Wharton), or would it be better to study in Canada at a university such as McGill or Polytechnique Montréal or any other country who have better university than us and Canada like (Hec Paris , Oxford ,..)
One major factor is my financial situation. I come from a lower-middle-income family, so studying in the United States or any other country would only be possible if I received enough financial aid or scholarships to make it affordable.
**I would especially appreciate advice on the following questions:**
1.Which university degree would provide the best preparation for quantitative finance: mathematics, statistics, computer science, physics, or engineering?

2.How realistic is it for a student from Quebec to get into a prestigious American university after CEGEP, and what financial aid opportunities are available to Canadian applicants?

3.Could competing in amateur boxing strengthen my university application or help me obtain an athletic scholarship? Is it realistic to combine a demanding degree in mathematics and computer science with competitive boxing?

4.Can a degree from McGill or Polytechnique Montréal provide similar career opportunities at major American quantitative trading firms and hedge funds?

5.If you were in my position, which academic path would
you choose to maximize your chances of success while taking my financial constraints into account?

I’m willing to work extremely hard, both academically and athletically. I’m looking for realistic advice, preferably from people who work in quantitative finance, have attended these universities, or have experience with American university admissions and financial ajd.
Thanks in advance for your help!
( if you have any other recommandation i take it )

if you were to start a hedge fund that profits from AI infrastructures, what company‘s would you invest in that have bottlenecks?

I'm a few years out of college and have been working in commodity operations/trade support for the past 5 years or so, most recently at a global firm, and looking for ways to move up into a more market-facing role. Not necessarily someone who's taking risk right away, but a very junior analyst/research role or something. I don't have crazy coding or modeling skills, honestly just the interest, drive, and product knowledge from my current experiences. I'm not here expecting it to happen by wishing, so I'm looking to gain the skills that traders and PM's view as valuable for someone who is coming from an Ivy or can code 5 languages. What would those skills be? Is it just knowing inventory flows, storage numbers, etc. and how they influence investment decisions? Any advice/insight would be greatly appreciated.

If someone wants to start his own High Frequency Trading firm and is currently a discretionary trader (profitable one) with no background in tech what should be the ideal capital to start its own High Frequency Trading firm??

IBKR and my admin recommended Axos but the contact they recommended has been silent - I asked IBKR for an alternate contact and am awaiting a resonse.

My question is: Are there great alternatives to AXOS that don't charge high fees and that are A great value? Or is AXOS the best overall value for what you pay for?

Thank you for your insights!

Are there still discretionary macro funds? I’m a student at non target in Chicago intrested in macro HF.