正在加载视频...

视频加载失败

Think Quant Memo is just quant finance? Think again. Algorithmic trading. Machine learning. Deep learning. Neural nets and LLMs. Stochastic calculus. Derivatives. Market making. And the research shaping all of it. One place. All free. We're here to disrupt, and we're coming straight for the paywalls. Something new ships...

391,266 次观看 • 2 个月前 •via X (Twitter)

39 条评论

Priyanshu Priyank 的头像
Priyanshu Priyank2 个月前

For people if they want my intro -

Striver | Building takeUforward 的头像
Striver | Building takeUforward2 个月前

@quantmemo Congratulations 🙌 looks amazing

amrit 的头像
amrit2 个月前

@quantmemo lets goo get coding jesus’s market

Khushi🪐 的头像
Khushi🪐2 个月前

@quantmemo insaaneeee

Ajeet ( opensox.ai ) 的头像
Ajeet ( opensox.ai )2 个月前

@quantmemo that looks really great!

ambuj 的头像
ambuj2 个月前

@quantmemo proud of you my man

Rahil Mittal 的头像
Rahil Mittal2 个月前

@quantmemo Super cool that this is free! Better than a lot of the paid interview prep websites and things like that

Athrix ☄️ 的头像
Athrix ☄️2 个月前

@quantmemo This insane broski

Zeeast (comeback arc) 的头像
Zeeast (comeback arc)2 个月前

@quantmemo lfg!!!!!

Kumar Nirupam🍂 的头像
Kumar Nirupam🍂2 个月前

@quantmemo congrats @PriyanshuP1405 🥳 do you need help in making a good video i can help you with that .

Priyanshu Priyank 的头像
Priyanshu Priyank2 个月前

@quantmemo I know I have poor editing skills dont roast me in open 😭

Kumar Nirupam🍂 的头像
Kumar Nirupam🍂2 个月前

@quantmemo why would i roast u 😅, just offering you my help mate ...

Priyanshu Priyank 的头像
Priyanshu Priyank2 个月前

@quantmemo Lol jk, we will hopefully need when we keep adding more features and announcing more domains stay tuned :)

Kumar Nirupam🍂 的头像
Kumar Nirupam🍂2 个月前

@quantmemo alright 🤠

I like my cheese drippy bruh 的头像
I like my cheese drippy bruh1 个月前

@quantmemo great resource !

AnantaVichāra 的头像
AnantaVichāra2 个月前

@quantmemo nice!

shydev 的头像
shydev2 个月前

@quantmemo NOICEEEEE!!!!

Om 的头像
Om2 个月前

@quantmemo Congratulations man ...it's peak 🔥

Kirtan Suthar 的头像
Kirtan Suthar2 个月前

@quantmemo 🔥🔥🔥

aarya pandey 的头像
aarya pandey2 个月前

@quantmemo Soooo crazyyyy wowwww

!Laraib👨‍💻 的头像
!Laraib👨‍💻2 个月前

@quantmemo Congrats letsgo

chastronomic 的头像
chastronomic1 个月前

@quantmemo insane, congrats!

Krishnav Kanoi 的头像
Krishnav Kanoi2 个月前

@quantmemo Crazy stuff

Neo the One 的头像
Neo the One2 个月前

@quantmemo your experience is trash and you will teach all this (a strategy database lmao)?

Brjan | AI Builder 的头像
Brjan | AI Builder2 个月前

@quantmemo free access to such advanced topics is a solid way to attract serious users

Chandresh Gohel 的头像
Chandresh Gohel2 个月前

@quantmemo Yo this is really good man

Tanu 的头像
Tanu2 个月前

@quantmemo woah looks good

abhinav 的头像
abhinav2 个月前

@quantmemo this is peak.

Aaditya 的头像
Aaditya2 个月前

@quantmemo 100/10

Faizan Shaik 的头像
Faizan Shaik2 个月前

@quantmemo Crazyy

Nakul 的头像
Nakul2 个月前

@quantmemo great Share

Aman Dwivedi 的头像
Aman Dwivedi1 个月前

@quantmemo Great work

Shabaz 的头像
Shabaz2 个月前

@quantmemo peak work man👏🏻👏🏻❤️

Pratik 📈 的头像
Pratik 📈2 个月前

@quantmemo cool stuff bro

cal 的头像
cal2 个月前

@quantmemo goat drop

Ankur Sharma 的头像
Ankur Sharma2 个月前

@quantmemo Is there anything you can't do 🔥

DROID 的头像
DROID2 个月前

@quantmemo Great bro

Anurag Jha 的头像
Anurag Jha2 个月前

@quantmemo Banger 🔥

Sarabjeet singh 的头像
Sarabjeet singh2 个月前

@quantmemo Great man

相关视频

goldman sachs packed 25 YEARS of Wall Street quant experience into a GitHub repo and made it FREE the craziest part? it’s built and maintained by Goldman Sachs’ own quant developers it’s called gs-quant, a quantitative finance toolkit covering risk, derivatives, trading strategies and financial analytics pair it with Machine Learning for Trading and you have a powerful open-source quant research stack here’s how to run it yourself: step 1 → open and install the library using pip install gs-quant step 2 → open and explore its 27 chapters covering financial data, machine learning, backtesting and execution step 3 → pull historical S&P 500 market data and build a trading dashboard with 15-minute candlesticks, volume and technical indicators step 4 → use gs-quant to analyze volatility, risk exposure, correlations and financial time series step 5 → combine it with ML4T to research market patterns, engineer features and develop trading signals step 6 → add moving averages, VWAP, volume profiles and market monitoring panels to your research terminal step 7 → evaluate strategies using Sharpe ratios, drawdowns and other quantitative risk metrics step 8 → backtest your strategies with transaction costs, then walk-forward test them on unseen market data the result: a quantitative finance research stack combining Goldman Sachs’ own toolkit with machine learning, market analysis and strategy evaluation two GitHub repos an entire quant research workstation i won’t say anything more…

ludoonchart

37,780 次观看 • 9 天前