Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

This 3-hour algorithmic trading video with Python is like getting a mini course from Massachusetts Institute of Technology - for free It reveals more about quant trading and bots than most traders learn in years on the market Bookmark it. Watch it. Then watch it again.

161,273 Aufrufe • vor 6 Monaten •via X (Twitter)

40 Kommentare

Profilbild von Strategy Trader
Strategy Tradervor 6 Monaten

Most Python quant backtesting tutorials skip slippage/execution... key for real trading.

Profilbild von Hussain Hashim | Building SundayBack
Hussain Hashim | Building SundayBackvor 6 Monaten

@sopersone perfect timing, been trying to wrap my head around quant stuff. hope it's not too heavy on the math 🤞

Profilbild von 0xSurdo.ETH
0xSurdo.ETHvor 6 Monaten

grabbing it now haha

Profilbild von Samu3l
Samu3lvor 6 Monaten

Please share the link to the YT video🤲🏾

Profilbild von Hemisphere Research Capital
Hemisphere Research Capitalvor 6 Monaten

You've gotta be really intelligent to watch this and think you're getting a mini course from MIT.

Profilbild von NOT MY FAULT🥴
NOT MY FAULT🥴vor 6 Monaten

Hope you know about this.

Profilbild von Archive
Archivevor 6 Monaten

I think you could even make a bot on a calculator

Profilbild von Liquidity Sniper
Liquidity Snipervor 6 Monaten

Free MIT-level quant course? Say less. My intuition just got benched. Bookmarking and replaying.

Profilbild von The Skeptic's Advantage
The Skeptic's Advantagevor 6 Monaten

great stuff, thanks for sharing!

Profilbild von magsimich
magsimichvor 6 Monaten

lol

Profilbild von slash1s
slash1svor 6 Monaten

nice video, saved!

Profilbild von Dano
Danovor 6 Monaten

exactly - but most people watch and don't implement. saw this pattern with 20+ devs last year. real learning happens when you code your own algo and break stuff. what's your first trading bot gonna focus on?

Profilbild von Blockwise Technologies
Blockwise Technologiesvor 6 Monaten

Unfortunately this is just academic stuff, not working in real world production environment.

Profilbild von Spicy Brwny
Spicy Brwnyvor 6 Monaten

Every minute worth it in this 3 hour vid... already saved it

Profilbild von Dean van den Heever
Dean van den Heevervor 6 Monaten

@threadreaderapp unroll

Profilbild von OdeToJoy
OdeToJoyvor 6 Monaten

@grok make an assessment of the strategies covered in this post in relation to trading on Polymarket. Anything in particular to highlight as revolutionary or impactful?

Profilbild von Caducado
Caducadovor 6 Monaten

Link del video?

Profilbild von Marieluv 🇺🇸 🇨🇻 🇬🇭 💞
Marieluv 🇺🇸 🇨🇻 🇬🇭 💞vor 6 Monaten

@kwesi_dadson

Profilbild von TRAIDEFLOOR
TRAIDEFLOORvor 6 Monaten

the video probably teaches the right foundations — backtest loops, signal construction, position sizing. what it can't teach is what happens when your signal fires at the same time 500 other algos trained on the same public data fire the same trade. alpha decays fastest in the strategy classes everyone learns from the same sourcethe video probably teaches the right foundations — backtest loops, signal construction, position sizing. what it can't teach is what happens when your signal fires at the same time 500 other algos trained on the same public data fire the same trade. alpha decays fastest in the strategy classes everyone learns from the same source

Profilbild von Liquidity Sniper
Liquidity Snipervor 6 Monaten

MIT-level for free? Say no more. Bookmarking now. If my algo starts printing cash, I'm naming it Professor and retiring early.

Profilbild von Paone
Paonevor 6 Monaten

thx for alpha bro bookmarked

Profilbild von Reitcircles
Reitcirclesvor 6 Monaten

Do you have a GitHub repo of the code ?

Profilbild von Rafał Cheliński
Rafał Chelińskivor 6 Monaten

It’s advertisement.. why you cheating 😎🤔

Profilbild von sopersone
sopersonevor 6 Monaten

What am I advertising, and where am I deceiving anyone?

Profilbild von Rafał Cheliński
Rafał Chelińskivor 6 Monaten

I don’t know you tell me 😎

Profilbild von sopersone
sopersonevor 6 Monaten

Looool

Profilbild von Jimmy Ashcot
Jimmy Ashcotvor 6 Monaten

watching a lecture is not the same as building. the lecture gives you the map. you still have to walk

Profilbild von Hrundel75 🐷
Hrundel75 🐷vor 6 Monaten

Pure alpha lecture

Profilbild von Hanako
Hanakovor 6 Monaten

long content pays depth builds edge

Profilbild von sopersone
sopersonevor 6 Monaten

yeap

Profilbild von silvio
silviovor 6 Monaten

How did you upload it to X?

Profilbild von sopersone
sopersonevor 6 Monaten

Just grabbed it and uploaded it lol

Profilbild von h100envy
h100envyvor 6 Monaten

That very moment when three hours of video replace a semester at MIT and a couple of years of learning the hard way in the real world

Profilbild von monokern
monokernvor 6 Monaten

bookmarked, thanks

Profilbild von sopersone
sopersonevor 6 Monaten

Ty too

Profilbild von ASHURA.V
ASHURA.Vvor 6 Monaten

link

Profilbild von Alpha Batcher
Alpha Batchervor 6 Monaten

i need to learn something on this video, ty for sharing

Profilbild von sopersone
sopersonevor 6 Monaten

welcome bro

Profilbild von Alpha Batcher
Alpha Batchervor 6 Monaten

appreciate it

Profilbild von Apurba Mohapatra.
Apurba Mohapatra.vor 6 Monaten

@grok give the YT link or name of this freecodecamp video

Ähnliche Videos

A finance professor manages $200M with AI agents, and he told everyone why: "Large language models are at the level of a fourth-year PhD student in every field" Alejandro Lopez-Lira's AI fund, Autopilot, returned 56% last year. The S&P did 16%. There are 52,000 people with money in it, and most of them just watch the machine work. What he automated is the same six-step loop every fund on earth runs: find an idea, code it, backtest it, deploy it, read the autopsy, learn from it. A quant at Two Sigma runs that loop once a month, and the salary time alone costs around $50,000 per hypothesis. All steps from this loop now fit in AI trading text box. Plain English in, executable strategy out, five-year backtest in 12 seconds, live on a broker 90 seconds after you typed the sentence. He runs $200M with AI. You can run same AI fund in two clicks, free to try: Step 6 on this loop is where everyone is stuck. Your agent has no memory. Every strategy it kills goes into a log nobody reads, and the next one starts from zero. Nobody keeps negative results. Not Citadel, not Man Group, not a single repo on GitHub. Fix that and the agent remembers every hypothesis it killed and the regime it died in. It stops burning cycles on your old mistakes. Jane Street pays 3,500 people to run this cycle and made $39.6 billion doing it. Five sixths of it is now free. Bookmark & read full map of this loop in the article below. Most people still think AI trading is out of reach for them - it isn't.

sopersone

48,482 Aufrufe • vor 1 Monat