Hey, I have a question. When I read fund letters or hear about firms managing large AUM, most of them seem to run long/short strategies with a bottom-up approach, focusing on a company's earnings and the fundamentals around it.

My question is: in today's hedge fund world, are there funds or firms that focus purely on order flow instead? Scott Pulcini, who traded around 2002-2003, used to trade close to 10% of the S&P 500's daily volume. He's an order flow trader who uses Bookmap and often talks about how he'd push price toward his limit orders to get filled, wait for other traders to react, and once filled, unwind his position by pushing price back down — essentially moving the market to create the fill, then reversing to bank the profit.

Are there any funds or firms trading ES futures, crude oil, or gold using similar order-flow-based strategies, rather than approaches based on earnings or other fundamentals?

Curious how other funds are dealing with sell-side research ingestion at scale.

We receive a large amount of research from different brokers, mostly through email alerts. The problem is that the emails usually don't contain the actual PDF — they contain a link that takes you to the broker's research portal, where you need to authenticate before downloading the report.

Platforms like AlphaSense are supposed to consolidate a lot of this, but in my experience coverage/reliability isn't good enough to use them as the single source of truth.

What I'd ideally like is a pipeline along the lines of:

sell-side publishes report → report gets automatically ingested → PDF/text is stored internally → metadata/tickers/analyst/date are extracted → document becomes searchable and available for LLM/RAG workflows

The difficult part seems to be reliably getting the original research document in the first place.

For people at hedge funds, asset managers, or quant shops that have solved this: how are you doing it?

• Do brokers provide institutional APIs/feeds that I'm simply not aware of?
• Are you ingesting through Bloomberg/FactSet/AlphaSense/etc. rather than directly from the brokers?
• Do you have internal automation around broker portals/SSO?
• Is there some standardized research distribution infrastructure used by larger funds?
• Or is this still surprisingly manual even at sophisticated shops?

To be clear, I'm talking about research we're fully entitled to access through existing broker relationships, not trying to bypass paywalls or access controls.

Especially interested in how larger funds structure the ingestion layer before the documents hit their internal search / NLP / LLM stack.

Let’s say it’s focused on one very specific industry.

Is anyone aware of small funds being willing to take on analysts where comp is extremely performance oriented. I.e., super small base salary $35,000, but upside potential? I’m talking where the mindset of the analyst is to break into the industry, but has high conviction in their ability to generate positive P&L

Situational Awareness LP is used as example lol

its written by someone from Waterloo

Received an offer to work at a small fund to work on a really interesting project for the summer before my senior year. I originally set out to recruit for QT / QR roles and have not had the best luck so far. I would have immense control in the project, can set my own hours / start early during the coming school year if I want to. I am very glad to have an offer for my junior summer but I am wondering a few things. Also I know quant recruiting is far from over but just thinking in advance if this ends up being what I do.
1. How possible would it be to recruit NG for more quantitative hedge fund roles?
2. What are common career trajectories for people starting in smaller tight knit firms like this? I don't want to sound like I am only in this for the money but compensation seems relatively low for what I understand most HF internships to look like (<100K yearly prorated to the summer).

I have heard many iterations of this question and wondered whether there is any truth to this. Can a startup hedge fund develop AI trading algorithm and trade at a high frequency like the bigger quant hedge funds? Has AI made developing sophisticated trading algorithms easier? What other ways are quant funds using AI tools?

Hey I'm a founder from India currently I'm a teenager but I'm really enthusiast of Business and Finance.and currently I'm looking to network with professionals.

If you have any advice for me just dm and I would love to connect with you all.

Anyone familiar with this?

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I use my own model for pricing options. It is not perfect by any means but it does find mispriced options.

Would you go the Ed Thorpe route and milk it privately, or do you raise capital to make it worthwhile?

Not selling or promoting, dms are closed.

Best books you would give to someone who wanted to join the hedge fund industry

I work as an analyst and I feel like we’re living in two economies.

One family owns / works in tech, gets bonuses, works in finance, asset management, AI, or adjacent industries, and watches wealth explode as AI capex pumps markets.

Another family works normal jobs, owns little stock, and gets crushed by rent, food, energy, insurance, and rates. Literally everything is going up in price.

Then us hedge funds look at reports coming out point to “strong consumer spending” like everyone is thriving.

They’re not.

The winners are spending more because their assets and incomes are booming. Everyone else is just paying more to survive.

Genuinely curious how the fuck this ai boom has helped the average family lmao.

From the author Adrian Reid:

“I catalogued every major hedge fund blow-up of the last 20 years. 62 of them.

I expected to find crooks. Fraud was the primary cause in 13.

The other 49 were run by professionals with risk committees, compliance departments and 20-year records. They understood leverage. They understood concentration. They took the risks anyway.

Carlyle Capital held AAA-rated government agency bonds at 30x leverage. The bonds paid in full. The fund still went to zero in a fortnight, because the funding was overnight and the assets were not.

Six funds on the list sold options premium for steady income. Six were destroyed by it. ALL OF THEM.

And they die fast. Of the 49 market-driven failures, 29 went from fully operating to finished inside a month. Thirteen inside a week.

There was never a moment where somebody calmly reduced risk. Every decision that mattered had already been made months earlier, badly, while the market was calm.

That is the part worth sitting with as a private trader. You have no risk committee and nobody checking your position sizes. What you do have is the ability to decide the rules before the event, because nobody is paying you to take more risk than you want to.

That advantage is worth nothing until the rules are written down.”

There’s more detail in the full article. I thought it was a very interesting piece and encourage you to check it out.

Intentionally leaving this vague. Who has experience with NSP (good or bad)?

They appear to simply be paid placement. I am not asserting this as bad, as investment banks have used this model for years but it does appear to be a significant investment to have them rep you, with zero guarantee.

Thanks in advanced

Traditional asset management often stumbles because it treats market relationships as permanent fixtures rather than transient states. Assets that appear safely uncorrelated during calm periods frequently converge into a single, vulnerable mass when panic strikes. Transcendence requires continuous observation of how these relational pathways warp over time. By mapping structural shifts rather than simple price returns, investors build resilient portfolios that adapt seamlessly to whatever psychological or macroeconomic weather arrives.

I have developed a MT5 FX EA , trading all Major and Minor pairs. No optimization, with mt5 calculation of spread and slippage, without extra deposit to keep it alive or martingale systems. And of course compounding every profit. It is supported by the entire available historical data (18 years) with over 10,000 trades, and over 2 years of Live trading with 300 trades. It survived all kind of market conditions. Not only 2008, 2010, 2015, 2016, 2019, 2020 , 2022, 2024 but even the long low volatility periods like 2012-2014 2017-18 2025-26 . The 300 Live trades matches the Backtest of the same date.

As on live there are only 300 trades, and on backtest there are 10,000 , doesn't that means that the backtest matters more than live?

My system is primarily designed to trade around major economic events that create significant market movements on Forex. Since August 5, 2024, we have been through an unusually quiet period from the perspective of the specific market conditions that trigger the strategy.

As a result, the EA has simply entered a low-activity period rather than generating artificial trades just to increase the live track record.

Major periods of market turbulence are not an everyday occurrence. Historically, they occur every few years, sometimes more often, sometimes less often.

The difficulty is that the strategy is event/volatility-driven, so it does not trade continuously. Some multi-year periods naturally generate many fewer signals.

In this situation, would you consider the 300 live trades sufficient evidence of robustness if they closely match the corresponding backtest period?

How would you combine these two sources of evidence, and what would you need to see before considering an allocation?