How is AI/Machine Learning changing the Hedge fund industry?

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To answer this you need to understand what quants do, They are mainly market-neutral and make money on most days. Now this is strictly equities. There are a lot of opportunities in credit like sovereign debt plays or corporate credit. There is more than one investing style, with technology proliferating there will be fewer roles but they will still exist and they will require you to have good technical prowess and be the best. You don't need to write complex code but still be comfortable with it. Hfts and quants operate on a different time horizon relative to other funds. An investor who wants to dump some of their beta risk and lower their portfolio volatility would go to a different fund relative to an investor who wants to make a few basis points of the equity volume traded. 

AI will change less than you think for quant funds because all the top quant funds were already using machine learning 20 years ago. Neural nets are newer and better, yes, and maybe they'll cause some of the existing top funds to be replaced by different funds, or maybe we'll hire more programmers and fewer math PhDs; but I see it as a evolution for quant funds, not as a major disruption. It's important to note AI will never "solve" the markets -- you can never write the perfect trading  algorithm that crushes everyone else, because the problem is non-stationary. Even if you did create the perfect trading algorithm, the instant you turn it on, all other traders (both humans and other AIs) will change their behavior and your algorithm no longer works anymore. 

For non-quant funds, they'll still exist. Humans won't be able to get any edge over competitors by reading 10-K filings anymore, but to be honest, you aren't really getting any edge from that today, either.

 In the next 10-15 years, will it be the case that best quant funds will dominate the industry in terms of returns (and drive other smaller hedge funds out of biz).

100% yes, but the reason has nothing to do with AI. There's just so much economy of scale in a large quant fund that it's hard for smaller funds to compete.

LLM's and other ML models are essentially inference machines; they take in a large amount of historical information and produce a response based on that data. As such, it is very difficult for AI models to generate novel ideas. They struggle to create new knowledge without heavy user direction.

Moreover, if you think about the way these models are built, they are necessarily designed NOT to be differentiated. Take an LLM like ChatGPT for example: the algo predicts the next most likely word in a sequence. In doing so, the algorithm essentially leans on the similar word sequences in its training data and chooses the most appropriate word. The algorithm cannot tell the difference between word choices and ideas that are uncommon because they are genius insight and ones that are uncommon because they are indefensible. You can test this out; choose a claim that is contrarian but defensible and try to get ChatGPT to agree with you. It is possible, but you really have to lead the algo there with baby steps.

Basically, I believe there's a fundamental conflict between training effective AI agents and making differentiated investment decisions. I could totally see AI replacing the sell-side though, and there's a lot of workstreams that investors currently do that could be substantially automated.

a lot. It revolutionized HFs, and I really mean it when I saw A LOT. When you're doing the input in the machine/system for a stock, the response one gets, literally is: "markets are efficient, it's not worth it king, go home", and the only thing a mortal spirit can do, in the face of such robotic zeitgeist, is just to gaze and feel the sense of awe rushing through his veins. One can only worship it, and not conquer it, for Ken Griffin get its, and in closed door, behind curtains of wool & cotton, he meticulously prays 5 times a day and worships the Sillicon Vally semi-gods so they can continue to bless him with the means to abnormal returns.

groundbreaking, truly groundbreaking times we live in... it's sounds as some type of sci-fi nightmare, but it's real... very real

This is what ChatGPT said after I copy pasted in your post:

AI and machine learning (ML) have indeed been making significant inroads into the hedge fund industry. Here's a breakdown of your questions:

1. Impact of AI on Hedge Funds:

- Data Processing: AI/ML excels at processing vast amounts of data quickly. This is particularly useful for hedge funds that rely on high-frequency trading or that use alternative data sources (like satellite imagery or social media sentiment).

- Predictive Analytics: ML models can identify patterns in data that might be too complex for human analysts to discern. This can lead to more accurate predictions about market movements.

- Risk Management: AI can help in developing more sophisticated risk models, ensuring that the fund's exposure is kept within acceptable limits.

2. Dominance of Quant Funds: - It's true that quant funds have been successful, but it's also worth noting that the financial markets are complex and ever-evolving. While quant strategies can outperform in certain market conditions, they can also underperform in others. - There will always be a place for human intuition and judgment. For instance, during unprecedented market events, algorithms might behave unpredictably, whereas a human might be able to make more nuanced decisions.

3. Career for Analysts: - While the role of analysts might evolve, it won't disappear. Analysts with deep industry knowledge can provide insights that are difficult for algorithms to grasp. - The value-add for analysts might shift towards interpreting the outputs of AI models, providing context, or focusing on areas where human judgment is crucial. - Soft skills, like relationship management, negotiation, and understanding the nuances of business operations, will remain invaluable.

4. PE vs. HF: - Private Equity (PE) indeed involves a lot of human judgment, especially when it comes to operational improvements, management changes, and long-term strategy. This makes it less susceptible to automation. - However, the hedge fund industry also offers opportunities that aren't purely quantitative. For instance, macro funds, distressed debt funds, and activist funds rely heavily on human judgment.

Final Thoughts:

While AI and ML are powerful tools that are reshaping the hedge fund industry, they are just that: tools. They complement human judgment rather than replace it. If you're passionate about investing and the hedge fund world, there will always be opportunities. It might be beneficial to gain some understanding of AI/ML, not necessarily to become an expert, but to understand its capabilities and limitations. This will make you a more versatile and informed investor in the future.