269.6K
MAabout to film some tutorials for you guys on these too #python #fintech #financialmodeling #coding
@mar_antaya
#Fintech Developer
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120.0K
MAAlso don’t start from scratch…those days are over but if there is a certain framework you want to leverage tell Claude code or @claudeai or whatever you are using to use that’s framework! I feel like I shouldn’t have to say this but we are moving quickly and I’m seeing people still get caught up in wanting to learn and implement from scratch. These are my recommendations if you’re just starting but seriously also ask your LLM and tool what you are trying to build and they will probably give you better advice on what exactly framework or tool you should be using too! #financialengineering #fintech
@mar_antaya
652
GONew financial plug-ins just hit Anthropic GitHub.
New finance AI plugins just hit GitHub for investment banking and equity research.
This dropped on Feb 24, 2026.
I pulled up Anthropic's Financial Services plugin repo and the update is real.
It's the kind of release where if you work in IB, PE, or WM, you instantly see the workflow shortcuts.
Here's what you'll get from this video:
- 📈 What the new investment banking, equity research, private equity, and wealth management plugins cover
- 🧰 Where the code lives on Anthropic's GitHub and what was updated yesterday
- 🔌 What "skills, commands, and MCP integrations" actually means in practice
Quick detail that matters: the repo lists 41 skills, 38 commands, and 11 MCP integrations.
Which team would benefit first from this in your world - investment banking, equity research, private equity, or wealth management?
Drop your pick in the comments.
#financialservices, #investmentbanking, #equityresearch, #privateequity, #wealthmanagement, #financialanalysis, #github, #anthropic, #mcpintegration
@gotspreadsheet
6.6K
MAThe finance industry is not ready for me 😈
Comment “engineer” if u want early access
#ape #ai #money #trade #stocks
@martinwang.trades
864
TUComment “links” and I’ll send you the GitHub repos ✨
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Follow @tuba.captures for more
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#quantfinance #algotrading #pythonprojects #fypシ #explorepage
@tuba.captures
46.4K
TUComment “links” and I’ll send you the GitHub repos ✨
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Follow @tuba.captures for more
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#quantfinance #algotrading #pythonprojects #fypシ #explorepage
@tuba.captures
311
QUCurious about quant roles? Dive into machine learning & high-frequency trading. Real insights for aspiring pros. #QuantFinance #MachineLearning #TradingStrategies #FinanceJobs #CareerInFinance #FinTech #QuantitativeFinance #HFT
@quantlabsnet
202
COBuild a real credit risk scoring system that predicts loan default probability using machine learning and explainable AI for fintech applications.
#DataScience #MachineLearning #Fintech #RiskAnalytics #CodeVisium
@codevisium
35
ARUnderstand tokenized assets #techjobs #softwaredeveloper #softwareengineer #fullstackdeveloper #fullstack
@arnold_hayes_
251
QUBuilding quant finance knowledge from scratch? The correct order is what most people get wrong.
If you're starting out, this is the sequence that actually makes sense. Most people begin with Python because it feels productive, or jump straight to strategies because that's what interests them. Both approaches produce the same result, knowledge that falls apart the moment problems get serious.
Each subject builds on the one before it, and the order matters more than most content will tell you.
Probability comes first. Everything in quant finance is a statement about uncertainty, and probability is how those statements are made precisely. Skip this and you spend the rest of your time guessing at why your models behave the way they do.
Statistics comes next. Probability tells you how a model generates data. Statistics works in the other direction, given data, what can you actually conclude? This is what you are doing every time you evaluate a backtest or test whether a signal is real.
After that, calculus and linear algebra. Pricing models, optimisation, risk decomposition.. all of it lives here. You don't need to be a mathematician. You just need to be comfortable enough that it doesn't slow you down.
Then programming. Python first to move quickly and build intuition, C++ later when performance starts to matter. Code is not a separate skill you add on top. It is how the work gets done.
Then machine learning and deep learning. It sits here in the sequence because it needs everything above it. Without the statistical foundations, you end up applying methods you don't understand to problems you haven't correctly framed.
Then markets, derivatives, risk management, and stochastic processes in that order. This is where the theory meets the actual objects it was built to describe.
Done properly, this is 12 to 18 months of serious work. There are no shortcuts that don't cost you somewhere down the line.
Comment "Quant" and I'll send you the full structured guide covering every subject, the reasoning behind the order, and the exact resources for each one.
#quant #quantfinance #maths #finance #machinelearning
@quant_shubham
358
COLast week, our students demoed the MVPs they built during Tech Residency 👏
One of them? SecureBank AI.
If you’ve ever struggled to track multiple bank accounts… this is for you:
💳 Consolidated dashboard
🤖 AI-powered transaction categorization
📊 Real-time budget tracking
🔐 Secure login system
Built in 8 weeks. From concept to working product.
Comment "AI" if you’re considering learning AI and build real-world projects like this!
#AIApp #FinTechProject #TechBootcamp #CodingTemple #FullStackDevelopment #AIEngineering #FinTech
@codingtemple
252
QUQuantitative finance needs specific coding skills and deep knowledge. Understand the requirements to land your dream role. #QuantFinance #CodingForFinance #FinancialModeling #QuantitativeAnalysis #FinTech #CareerAdvice #TechJobs #FinanceJobs
@quantlabsnet
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