Last Updated: 7th November 2022
FEATURED CATEGORIES
Fintech
Blockchain
Machine Learning
Explainable AI
Data Science
Digital Economy
Cryptocurrency
Maths & Stats
FEATURED COURSES
Last Updated: 7th November 2022
Pricing Kernels and Risk Premia
- Components: 2
- Free
Bitcoin Pricing Kernels are inferred using a novel data set from Deribit, one of the largest Bitcoin derivatives exchanges. This enables arbitrage-free pricing of various instruments. State Price Densities are estimated with Rookley’s method.
Last Updated: 7th November 2022
DS2 Data Science & Digital Society
- Components: 2
- Free
DS2 Data Science & Digital Society
Last Updated: 7th November 2022
Kalman Filter
- Components: 2
- Free
Introduction of Kalman filter including the background, calculation methodology and application.
Last Updated: 7th November 2022
Financial Risk Meter for Emerging Markets
- Components: 2
- Free
Financial risk measure FRM (Financial Risk Meter) is proposed for Emerging markets (FRM@EM).
Last Updated: 7th November 2022
Hedging Cryptocurrency Options
- Components: 2
- Free
Crypto Hedging strategies based on the paper Hedging Cryptocurrency Options.
Last Updated: 7th November 2022
Advanced Mathematics
- Components: 20
- Free
This background course on mathematics aims to provide fundamental mathematical knowledge essential for advanced economic analysis. Although open to all master students, it is specifically tailored to those wishing to directly pursue the advanced Y-track of courses. Therefore in content and form, this intensive course is intended to deliver methods beyond refreshing advanced calculus and linear algebra. The course solely deals with deterministic mathematics. For some theorems formally rigorous proofs are presented in order to make participants more comfortable with - and ideally to provide some intuition for – constructing and understanding of mathematical proofs. Throughout the course proper use of notation will be stressed. Topics presented in class constitute the minimal required program given the above aim, and the maximal feasible program given time.
Last Updated: 7th November 2022
Network Analysis on Financial Market
- Components: 2
- Free
Investigate the financial market from the perspective of networks.
Last Updated: 7th November 2022
Statistics with R
- Components: 4
- Free
Basic calculations Vectors and matrices Data frames and data IO Plotting
Last Updated: 7th November 2022
Multivariate Statistical Analysis
- Components: 2
- Free
Descriptive Techniques Principal Component Analysis
Last Updated: 7th November 2022
Business Analytics and Data Science
- Components: 17
- Free
Introduction to the foundations of Data Science with focus on business applications. We emphasize supervised machine learning algorithms to build predictive decision support models for credit risk, marketing analytics, and several other use cases.
Last Updated: 7th November 2022
Computer Museum
- Components: 2
- Free
Introduction to the Computer Museum
Last Updated: 7th November 2022
QuantLet
- Components: 2
- Free
QuantLet: A open-source platform hosted on GitHub for demonstrating your research project
Last Updated: 7th November 2022
Statistics of Financial Markets
- Components: 86
- Free
Statistics of Finance data; Quantitative finance; Forecasting
RECENT BLOGS
Digital Economy and Decision Analytics
Welcome to the blog of the Digital Economy and Decision Analytics class!Today we started this class after many years of education at Humboldt-Universität zu Berlin. Enjoy the lecture and do not forget to visit Quantlet.com for the source codes !
Instructor welcome message
Welcome to our new instructor Lucas Umann from the School of Business and Economics of Humboldt-Universität zu Berlin. He will be teaching our DEDA and Network centrality classes.
Explainable AI
We have created a new courselet category on Quantinar, Explainable AI.As Machine Learning and its black box models have known great success and wide adoption among practioners in the last years, the need for explainability and transparency has arisen. At Quantinar, we aim at teaching you with the best state-of-the-art solutions for opening the black box and regaining control over your machine lear
Statistics of Financial Markets
Welcome to the blog of the Statistics of Financial Markets class!Today we started this class after many years of education at Humboldt-Universität zu Berlin. Enjoy the lecture and do not forget to visit Quantlet.com for the source codes !
Machine Learning and FinTech
Welcome to the blog of the Machine Learning and FinTech class!Today we started this class in 复旦大学, wonderful athmosphere, good mood and perfect slides. The quantlet technology is really exciting. Hope to see more of this inspring Machine Learning tools in the next classes
WHAT WE HAVE TO SAY
Georg Keilbar, Vienna U
The DEDA course on Digital Economy & Decision Analytics presents modern machine learning tools for tomorrow's data. Based on a solid founding of Python applications, DEDA evolves into a powerful decision tool for navigating through heterogenous and massively unstructured data. The quantlet.com technology enables transparency and reproducibility in all scales.
Sheila Xiaohe XU, Fudan U
Quantinar provides a perfect intro into Machine Learning & Fintech. It equips students with the basic ability to analyze data using Python. The lectures and videos are super cool, understandable and really attractive. For the first time, it made me realize that data science could be very interesting. In the first class, I drew a cute little PY elephant.
Rupesh Poudel, HU Berlin
I also use edX, udemy and Coursera. I am extremely happy with the quality of the content and its practical applications. This is a very good initiative. I hope that more courses would follow this style.
Matthias Fengler, St Gallen U
The absence of transparency and reproducibility of scientific research are the root of a credibility crisis. Quantinar.com is an initiative that that offers brilliant insights into data science, Machine Learning, and up to date FinTech tools without losing the solid grip on mathematical and statistical foundations. Every student or teacher should like to become a Quantinar!
Teodor Nicolau
I used Quantinar in order to acces the DEDA courses. I can tell about me that i am a beginner regarding python but the information was well structured and came in handy to support the work done at the Research Methods course at my university.
Vasile Strat, ASE
Quantinar is an excellent platform for those looking for an intro to Machine Learning and concepts connected with Fintech. The lectures and videos have a good structure that are understandable and are created so that they are appealing also to those non-technical students.
Patrick Woitschig
Quantinar is a unique website devoted to educating on cutting-edge statistics and machine learning techniques. The courses masterfully blend theoretical foundations with detailed empirical applications. These are key to understanding much of recent research. Quantinar will become the new benchmark for online teaching.
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