Check out the upcoming speakers at: https://quwinterschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5fe3762099aa4a24691da924

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Alternative Data and the API Jungle

With Alternative Data becoming more and more popular in the industry, quants are eager to adopt them into their investment processes. However, with a plethora of options, API standards, trying and evaluating datasets is a major hindrance to adoption of datasets.

Check out the upcoming speakers at: https://qufallschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5f3c39ff99aa4a24691da5f3

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Fireside Chat with Dr. Matthew Dixon, Dr. Igor Halperin, Dr. Paul Bilokon, and Sri Krishnamurthy

Check out the upcoming speakers at: https://qufallschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5f3c39ff99aa4a24691da5f3

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Stochastic filtering and MCMC in finance

While the focus in machine learning is on neural networks, we shall demonstrate that other algorithms can be considered in this paradigm. In particular, we shall introduce stochastic filtering and MCMC with applications to finance.

Check out the upcoming speakers at: https://qufallschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5f3c39ff99aa4a24691da5f3

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Reinforcement Learning and Inverse Reinforcement Learning: simple examples and applications in Finance

This talk will introduce Reinforcement Learning (RL) and its Inverse (IRL) and illustrate how they work on very simple simulated experiments. I will then give a short overview of applications of RL and IRL for quantitative finance.

Check out the upcoming speakers at: https://qufallschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5f3c39ff99aa4a24691da5f3

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Deep Learning and Equity Portfolio Modeling

This lab session shall demonstrate how deep learning can be used to model equity factors, commonly used in asset management. The emphasis shall be on interpretability, the ability of deep learning to capture non-linearities, and understanding the differences between linear models.

Check out the upcoming speakers at: https://qufallschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5f6a21f299aa4a24691da797

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Frontiers in Alternative Data-Techniques  and Use Cases

Lecture 1: Alexander Denev

In this talk, Alexander will introduce Alternative Data and discuss it's uses from his book, The Book of Alternative Data

Lecture 2: Saeed Amen

In this talk, Saeed will discuss use cases in Alternative Data

-Deciphering Federal Reserve communications

Check out the upcoming speakers at: https://qufallschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5fd964e599aa4a24691da8fb

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: A Unified Framework for Model Explanation

Explainable AI is becoming increasingly important, but the field is evolving rapidly and requires better organizing principles to remain manageable for researchers and practitioners. In this talk, Ian will discuss a new paper that unifies a large portion of the literature using a simple idea: simulating feature removal. The new class of "removal-based explanations" describes 20+ existing methods (e.g., LIME, SHAP) and reveals underlying links with psychology, game theory and information theory.

Practical examples will be presented and available on the Qu.Academy site

Reference:

https://arxiv.org/abs/2011.14878

Check out the upcoming speakers at: https://qufallschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5f29eb1699aa4a24691da53a

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Generating Synthetic Data with Generative Adversarial Networks (GANs)

Limited data access continues to be a barrier to data-driven product development. In this talk, we explore if and how generative adversarial networks (GANs) can be used to incentivize data sharing by enabling a generic framework for sharing synthetic datasets with minimal expert knowledge.

We identify key challenges of existing GAN approaches with respect to fidelity (e.g., capturing complex multidimensional correlations, mode collapse) and privacy (i.e., existing guarantees are poorly understood and can sacrifice fidelity).

To address fidelity challenges, we discuss our experiences designing a custom workflow called DoppelGANger and demonstrate that across diverse real-world datasets (e.g., bandwidth measurements, cluster requests, web sessions) and use cases (e.g., structural characterization, predictive modeling, algorithm comparison), DoppelGANger achieves up to 43% better fidelity than baseline models.

With respect to privacy, we identify fundamental challenges with both classical notions of privacy as well as recent advances to improve the privacy properties of GANs, and suggest a potential roadmap for addressing these challenges.

Check out the upcoming speakers at: https://qufallschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5f33ad2a99aa4a24691da597

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Machine Learning for Factor Investing

In this presentation, Tony first introduced the concept of supervised learning. Then he covered the practitioners angle for constructing non linear multi factor signals using stock characteristics. He showed the added value of ML based signals over traditional linear stale factors blend in equity.

This master class is derived from Guillaume Coqueret and Tony Guida's latest book "Machine Learning for Factor Investing"

available at:

http://www.mlfactor.com/

Check out the upcoming speakers at: https://qufallschool.splashthat.com/

Subscribe to this podcast at www.anchor.fm/qupodcast

Or

On Apple Podcast at https://podcasts.apple.com/us/podcast/qupodcast/id1510865003

Slides and video at: https://academy.qusandbox.com/#/market/5fb54e3499aa4a24691da86c

A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!

Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.

Topic: Synthetic Data Generation in Finance

In this master class, Stefan shows how to create synthetic time-series data using generative adversarial networks (GAN). GANs train a generator and a discriminator network in a competitive setting so that the generator learns to produce samples that the discriminator cannot distinguish from a given class of training data. The goal is to yield a generative model capable of producing synthetic samples representative of this class. While most popular with image data, GANs have also been used to generate synthetic time-series data in the medical domain. Subsequent experiments with financial data explored whether GANs can produce alternative price trajectories useful for ML training or strategy backtests.

Reference: