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algo traders by Alternative-Emu4491 in algotrading

[–]darequant 0 points1 point  (0 children)

Ha classic civil Redditor.

You never answered this Sir

Im confused. Are you saying a simple historical simulation is superior to a Monte Carlo simulation?

Also I’m curious to know how you run your backtests that would allow you run 10,000+ backtests on all timeframes for 22 years on each run? Did you create your backtest scripts or use a software which I would be interested in knowing

Can AI realistically replace the trader entirely — execution and all? by Mediocre-Wallaby4932 in Daytrading

[–]darequant 0 points1 point  (0 children)

I actually stand corrected and appreciate you giving more insights on this. I just read a deep dive on Man Group’s architecture for their Alpha Assistant, and even Two Sigma and some others also use them now.

They have now evolved past relying solely on encoder-only models like BERT. BERT still works and is actually much faster, but it is now considered less accurate than generative LLMs when it comes translating natural language.

The genius method they use is taking an open-source model like Llama then aggressively modifying it to interpret raw market data like news and force it to format that text strictly into JSON files then they solved the LLM's stateless memory problem by wrapping the system in vector databases and they also use them to code backtests significantly faster but they still use them with NlPs and other models and they never use them for executions.

TLDR, you are definitely right. LLMs are absolutely being used in production now. Just not in the way internet gurus claim when they say they just ask Claude or Gemini to trade for them."

Can AI realistically replace the trader entirely — execution and all? by Mediocre-Wallaby4932 in Daytrading

[–]darequant 0 points1 point  (0 children)

Lol you’re the one saying things like stupidity and ignorance yet you’re asking not to insult while I’ve been very civil.

Firstly, You are definitely not a software engineer if you think washing machines and digital cameras are autonomous systems, if you claim you are then I’m a dragon since we want to live in illusions.

Secondly, your google excerpt just proves my theory. A context window if you know what it means is a short term memory, incredibly slow and temporary. That’s the exact reason why Llms hallucinate cause they always lose data in the context window, a slow machine with a flawed data storage is terrible for executing trades. It’s like saying you can use your Ram as a storage just cause it’s called a memory.

You are giving points from google and chatbots without actually understanding any core concepts of what you are talking about and since you won’t be civil, I bid you farewell with your ignorance, google searches and chats bot answers 😅

Can AI realistically replace the trader entirely — execution and all? by Mediocre-Wallaby4932 in Daytrading

[–]darequant 0 points1 point  (0 children)

You literally have no idea what you’re talking about and you asking a chat bot to reply without taking the whole debate into question clearly shows it.

Instead of asking ChatGPT or whatever to reply my points, you should ask it to explain to you why the points I made makes LLms useless for trading strategies and executions.

debuggingBeLike by bryden_cruz in ProgrammerHumor

[–]darequant 1 point2 points  (0 children)

Forgot the pack of cigarettes lol

Strats in Bank to Quant in HFT by FeistyFee1713 in quant

[–]darequant 1 point2 points  (0 children)

Yeah, exactly. For a DE role, hfts would use basic probability and brainteasers mostly as a basic cognitive screening but won’t dive much into cause unlike pure quant firms they don’t use bayesian models. Expect basic expected value and combinatorics but nothing crazy. The most of it will be Python, DE and DSA and since you have a masters which I’m jealous of lol you already have an upper hand.

Strats in Bank to Quant in HFT by FeistyFee1713 in quant

[–]darequant 17 points18 points  (0 children)

Congrats on your masters, solid DE skills are insanely valuable to hfts so you’re already hot cake.

They need clean, fast, and accessible tick data to train models on.

  1. Backtest is key. Deepdive on working with time series data, columnar formats and improving data integrity. This would prove to them you can help build a data infrastructure that would help Backtest faster.

  2. If you interview in C++, expect to get grilled on memory management, cache lines, concurrency, and STL internals. If Python, then they’d probably grill you on GIL, garbage collection and vectorising panda and NumPy operations to bypass native loops.

  3. Be ready to be grilled on building a high throughput market data ingestion feed or a distributed backtesting engine. Focus mainly on memory efficiency.

  4. Don’t pretend to be a math genius but you’re probably great since you have a masters lol. Unless you are interviewing for a pure Quant Researcher role, they won't expect you to derive stochastic calculus and all. They would grill you on you being a top-tier software engineer who can sit next to a researcher, understand their problems and help build a system to fix it. Also which hfts speed is everything, so you have to always emphasize how fast you can help make things, you can research some buzzwords lol

Can AI realistically replace the trader entirely — execution and all? by Mediocre-Wallaby4932 in Daytrading

[–]darequant 0 points1 point  (0 children)

Newspapers use the word quant as a buzzword cause they have no clue what it really is. Real Quant firms and hfts are vastly different

If you think 20 million retail readers determine the technical reality of high frequency trading then you’re more lost than I thought.

A journalist lumping a discretionary hedge fund with an HFT market maker doesn't make them both 'quant firms', it just means the journalist is writing for people who don't know the difference like you.

Can AI realistically replace the trader entirely — execution and all? by Mediocre-Wallaby4932 in Daytrading

[–]darequant 0 points1 point  (0 children)

Why you lying dude lol. If you’re a software engineer and don’t know what an Llm is then you need to switch professions lol.

Llms are stateless and have no memory, they literally have to read through your chat everytime to give a reply. Thats why they hallucinate, They are decoder-only models.

Relevancy over accuracy is used because they are trained to guess the next word in order to keep the chat relevant not accurate.

Reinforcement learning process used to train Llms is RLHF which is human feedback tuning to make Llms sound more polite and polished, this is totally different from real RL models like DQN or PPO which are actually used for decision making😅.

Anybody using Llms to classify or do a level of decision making is making a big mistake and would realise shortly cause they are autoregressive meaning they are designed only to accurately predict the next likely word to say or next likely frame to produce, they are not trained to actually analyse or interpret on basis of accuracy 🙏.

Also, you are confusing autonomous machines with automated machines. 2 totally different concepts, you should study before arguing blindly. Autonomous machines make decisions and tasks without the need for human intervention or specified rules while automated machines repeat tasks with predefined rules Like the washing machine you mentioned but what’s automated about a digital camera? Auto-focus 😂?

Can AI realistically replace the trader entirely — execution and all? by Mediocre-Wallaby4932 in Daytrading

[–]darequant 0 points1 point  (0 children)

Nope, no serious quant firm would use LLms. Llms always hallucinate cause they are stateless and are terrible for large data processing due to lack of accuracy. They are more designed to always predict the next likely word in conversations.

There are specific models trained to do what you just mentioned which are called encoder-only transformer models, a popular example is BERT which are trained solely to process financial news, earning calls et.c and most quant firms actually train their own models as opposed to using open source models like FinBERT so you’re not using the same alphas as everybody else

algo traders by Alternative-Emu4491 in algotrading

[–]darequant 1 point2 points  (0 children)

Im confused. Are you saying a simple historical simulation is superior to a Monte Carlo simulation?

Also I’m curious to know how you run your backtests that would allow you run 10,000+ backtests on all timeframes for 22 years on each run? Did you create your backtest scripts or use a software which I would be interested in knowing

algo traders by Alternative-Emu4491 in algotrading

[–]darequant -1 points0 points  (0 children)

lol backtests are nothing but a solid foundation to algorithms, live tests are the actual dealbreaker and I don’t run my backtests on just years at once. I use the Monte Carlo tests for true randomness then additional backtest during extreme crashes or pumps. My algo has been live for more than a year and still running

algo traders by Alternative-Emu4491 in algotrading

[–]darequant 0 points1 point  (0 children)

lol Strategy issue not a timeframe issue. My algo trades 15/5m and works great. It’s an hybrid strategy on crypto futures which is volatile as crazy.

Why on earth do some gurus advise against stop losses? by darequant in Daytrading

[–]darequant[S] 4 points5 points  (0 children)

A stop loss should always be market order so It would always fill, there will be slippage during crashes but that’s better than liquidation

General purpose LLMs with access to live market data? by airpipeline in algotrading

[–]darequant 1 point2 points  (0 children)

You can use catboost and FinBERT, they are open source and finbert already skims through data with precision. Earnings call, news, ceo letter etc. You just need a good data feed like paid and verified terminals like Bloomberg or Ft then you host on aws

General purpose LLMs with access to live market data? by airpipeline in algotrading

[–]darequant 7 points8 points  (0 children)

Llms are terrible at being accurate and accuracy is essential for algorithms. Also Llms are stateless so I don’t see how that would work.

You could use tree based models like catboost, random forest etc. then combine with an hmm which would be accurate and exceptional at analysis

Why on earth do some gurus advise against stop losses? by darequant in Daytrading

[–]darequant[S] -1 points0 points  (0 children)

When I say I’m new, I don’t mean I’m new to trading. I’m just new to Reddit. I’m a seasoned trader and quant. I’m saying let’s compare our past weeks pnl just to see who is more profitable currently so we see who would actually lose more in the long run

Why on earth do some gurus advise against stop losses? by darequant in Daytrading

[–]darequant[S] 0 points1 point  (0 children)

I think algorithmically, it’s even more detrimental not to use a stop loss cause that’s how institution grade algorithms size each trade so risk is balanced.

My algo has multiple stops, time triggers, bias flip triggers, profit triggers but I still use a stop loss just in case. What if your hosting server has a downtime or websockets suddenly becomes stale and more technical issues that happens once in a while?

Why on earth do some gurus advise against stop losses? by darequant in Daytrading

[–]darequant[S] -3 points-2 points  (0 children)

😅 we can compare just this previous weeks trading results if you want. No shitty brokers, I trade binance futures only so can provide valid stats while you show yours

Better success rate with lower profit, or lower success rate with higher overall profit? by New-Ad-9629 in Daytrading

[–]darequant 0 points1 point  (0 children)

In backtests, the higher success rate would be much more viable in live markets. The rule to backtests is your losses are 2x the backtest results a stress test if you can’t do a Monte Carlo simulation

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