https://www.figgie.com/play/ https://www.ceremade.dauphine.fr/~cardaliaguet/MFGcours2018.pdf https://www.semanticscholar.org/paper/Mean-field-games-Lasry-Lions/53e6ace0948f9b3aeb72b80566cc3a357d7a2277

1. intro - what is? why is important?
2. if you want to donate/contribute
3. structure
4. contact?

• SUBJECT

  1. introduction
  2. subsets - links to respective subdivisions
  3. relevant books - links to purchase or read
  4. relevant organizations - links to websites
  5. relevant forums - links to websites
  6. relevant people or leaders - links
  7. relevant videos - links
  8. Relevant repositories - links

• SUB-SUBJECT

  1. Introduction a. What is it?
     b. Structure of walkthrough?
  2. Idea 1 a. Theoretical explanation
     b. Practical explanation
     c. Algorithm walkthrough
     d. Code?
     e. Expected results?
  3. Idea 2 a. Theoretical explanation
     b. Practical explanation
     c. Algorithm walkthrough
     d. Code?
     e. Expected results?

There will be significant changes in the coming months

Over the coming months I will change the layout and structure of this repository. At the moment, the repository has been structured after subject and resources. But I will gradually change it to a walk-through of each significant topic.

I will be starting with quantitative finance, specifically walking through work and examples on quantitative portfolio management, as this has recently become desired by others.

If you want to contribute

If you've found yourself wanting to contribute either with some content or with a donation. Please feel free to reach out to me on Email: mark@brezina.dk or Linkedin

Acknowledgment
Author: Mark Brezina
Contributors: Aksel Fristrup

Subject introduction pages

Quantitative finance - link

• Trading
• Portfolio management
• Risk management
• Pricing

Insurance - link

• Pricing
• Reserving
• Life
• Non-Life/General/causality

AI and Machine Learning - link

• AI
• Machine Learning
• Deep learning

Coding and IT - link

• Databases and SQL
• Windows Apps and Visual Basic
• Python and R
• C++ and C#
• Java and others
• APIs, connections and applications
• Automation, .bat, .cmd etc.

Abstract Mathematics - link

• Geometry
• Algebra
• Number theory

Probability and statistics - link

• Basic Probability
• Stochastic processes
• Stochastic calculus
• Basic Statistics
• Mathematical Statistics
• Time series
• Signal analysis
• etc.

Applied Mathematics - link

• Financial mathematics
• Optimization (linear, convex, stochastic)
• Advanced Financial mathematics

TEST

• AI and Machine learning
• Coding and IT
• Insurance and Risk
• Mathematics, pure maths, geometry
• Quantitative finance, Algorithmic Trading, Alpha
• Statistics, Probability, Stochastic processes
• Others

resource(Video, website, book, code)

• Books, Notes, Slides
• Code, repositories, packages
• Videos, channels, playlists
• Websites, forums, blogs

Special Topics

• Rough Paths and Signature Methods in ML
• Sustainable Finance and ESG with AI

• Carbon Credit Insurance

A massive thanks to the following.

Jonas Hal, Anton Vorobets, David Skovmand, Peter Cotton with his Microprediction, Henrik Hørsløv, Grananqvist, Jackal08, Snehilms, Je-suis-TM,

These need working on for quantitative finance

1. Blackrock - dig through their repos and find useful algorithms, blogs and documents
2. Jump Trading - dig through their repos, look through the CTO's repos
3. Hudson River Trading - look through followers, presumably lots of Hudson employees
4. Point72
5. AQR Capital Management
6. D. E. Shaw Research
7. D. E. Shaw Group
8. Bridgewater associates - not much here, try looking through followers
9. Jane Street - mostly OCaml, but maybe some useful algorithms
10. Goldman Sachs - these guys don't have anything interesting, dig through their followers.
11. https://www.acquired.fm/episodes/renaissance-technologies

Book collections

<img src="https://github.com/CtoL95/Knowledgebase/blob/main/books1.jpg" width="500"> <img src="https://github.com/CtoL95/Knowledgebase/blob/main/books2.jpg" width="500"> <img src="https://github.com/CtoL95/Knowledgebase/blob/main/books3.jpeg" width="500">

https://github.com/georgezouq/awesome-ai-in-finance

https://www.quora.com/What-is-the-method-used-by-quantitative-hedge-funds-such-as-Renaissance-Technologies-to-generate-profits https://www.linkedin.com/feed/update/urn:li:activity:7181549889821016066/?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7181549889821016066%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 https://colab.research.google.com/github/ksergiou/Time-Series-Forecasting/blob/main/Time_Series_Forecasting.ipynb https://quantecon.org/

https://github.com/ryanrussell/Lean/tree/master

https://github.com/ryanrussell

https://github.com/Velocities

https://github.com/f0ster/QuantResearch

https://github.com/letianzj/QuantResearch

https://github.com/wilsonfreitas/awesome-quant

https://github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading

https://github.com/firmai/financial-machine-learning

https://github.com/huseinzol05/Stock-Prediction-Models

https://github.com/pradeephyd/shashankvemuri-Finance

https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock https://github.com/robcarver17/systematictradingexamples https://github.com/robcarver17/pysystemtrade_examples

https://github.com/LongOnly/Quantitative-Notebooks https://github.com/MarcosCarreira/DermanPapers

https://github.com/rsvp/fecon235 https://github.com/rsvp/Kalman-and-Bayesian-Filters-in-Python https://github.com/dedwards25/Python_Option_Pricing

https://github.com/antontarasenko/awesome-economics

https://github.com/Finance-Hub/FinanceHub

https://www.deloitte.com/lu/en/services/risk-advisory/services/deloitte-quantitative-finance-master-classes.html https://macrosynergy.com/

https://github.com/xhshenxin/Micro_Price https://github.com/xhshenxin/lead-lag https://github.com/asavinov/awesome-systematic-trading https://github.com/asavinov/awesome-quant https://github.com/asavinov/awesome-deep-trading#high-frequency https://github.com/asavinov/awesome-deep-trading#cryptocurrency https://github.com/asavinov/awesome-deep-trading#guides https://github.com/asavinov/awesome-deep-trading#cryptocurrency-1 https://github.com/asavinov/awesome-deep-trading#presentations https://github.com/asavinov/awesome-machine-learning#python-neural-networks https://github.com/asavinov/awesome-machine-learning#python-reinforcement-learning https://github.com/asavinov/awesome-machine-learning#python-general-purpose

https://analyticsindiamag.com/comparing-arima-model-and-lstm-rnn-model-in-time-series-forecasting/ https://link.springer.com/chapter/10.1007/978-3-319-42297-8_40 https://arxiv.org/pdf/1707.07338 https://arxiv.org/pdf/1802.03042 https://www.mdpi.com/2076-3417/10/4/1506

https://github.com/amueller/introduction_to_ml_with_python https://github.com/justmarkham/scikit-learn-videos/blob/master/09_classification_metrics.ipynb https://github.com/justmarkham/scikit-learn-videos/blob/master/08_grid_search.ipynb https://github.com/justmarkham/scikit-l