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Check out the upcoming speakers at: https://qusummerschool.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/#/library?tagId=5f06326c55fd05416e7fd28a 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 and Model Risk (With a focus on Neural Network Models) All models are wrong and when they are wrong they create financial or non-financial risks. Understanding, testing and managing model failures are the key focus of model risk management particularly model validation. For machine learning models, particular attention is made on how to manage model fairness, explainability, robustness and change control. In this presentation, I will focus the discussion on machine learning explainability and robustness. Explainability is critical to evaluate conceptual soundness of models particularly for the applications in highly regulated institutions such as banks. There are many explainability tools available and my focus in this talk is how to develop fundamentally interpretable models. Neural networks (including Deep Learning), with proper architectural choice, can be made to be highly interpretable models. Since models in production will be subjected to dynamically changing environments, testing and choosing robust models against changes are critical, an aspect that has been neglected in AutoML.
Check out the upcoming speakers at: https://qusummerschool.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/#/library?tagId=5f06326c55fd05416e7fd28a 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. Implementing model validation through a set of interdependent modules that utilizes both traditional econometrics and data science techniques can produce robust assessments of the predictive effectiveness of investment signals in an economically intuitive manner. The proposed methodology, modular machine learning, also answers a number of practical questions that arise when applying block time series cross-validation such as what number of folds to use and what block size to use between folds. It is possible to re-interpret the Fundamental Law of Active Management into a model validation framework by expressing its fundamental concepts, information coefficient and breadth, using the formal language of data science. In this talk, we introduce an approach towards model validation which we call modular machine learning (MML) and use it to build a methodology that can be applied to the evaluation of investment signals within the conceptual scheme provided by the FL. Our framework is modular in two respects: (1) It is comprised of independent computational components, each using the output of another as its input, and (2) It is characterized by the distinct role played by traditional econometric and date science methodologies.
Check out the upcoming speakers at: https://quspeakerseries.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/5f062b8455fd05416e7fd285 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: Practical Issues in Asset Management The markets have seen significant volatility in the past few months. With the Factor investing boom of the nineties to the whiplash we have seen during #Covid19, Quants and asset management institutions are questioning accepted best practices in asset management. In this talk Dr.Reha Tutuncu from Point 72 will share his expertise and thoughts on the challenges and issues in Asset management from a practitioner's perspective. Reha will discuss issues associated with Factor investing and multi-period models and discuss how investors should strategize in the day of Covid19
Welcome to the QUpodcast - the podcast about life, learning, technology, and all topics that fascinate us as we seek to learn and grow! I am Sri from QuantUniversity and in today’s episode, I want to talk about a question I keep asking myself on every project.. when should you stop? In life, we encounter so many situations where we don’t finish projects thinking it isn’t good enough. Worse, we don’t even start thinking we don’t have time to build a good quality product. I have been struggling with this dilemma so many times. So the next time, you encounter a situation where you have to choose between waiting or to stop and call it done, choose the latter. Believe me, the satisfaction you get when you complete many projects is much higher than finishing one fully polished project but has left a trail of many unfinished projects. Visit us at www.quantuniversity.com to know more about our offerings --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app
Hi everybody! Welcome to the QUpodcast - the podcast about life, learning, technology, and all topics that fascinate us as we seek to learn and grow! I am Sri from QuantUniversity and in today’s episode, I want to talk about what's the best way to learn? In today’s day and age, we are bombarded with information whether it is audiobooks, online videos, or just the constant barrage of information that makes it to our doorsteps and browsers! So how should we learn? - Is it scrolling through bite-sized posts? - Is it going for summaries by someone because the original publications are ? - Is it watching bite-sized videos pioneered by likes of Udacity and Coursera giving us a false sense of accomplishment through certification? - Is it attending the unlimited number of "FREE" webinars we have access to in the day of #Covid19? Ultimately, the true test is how much do we understand and how well can we explain it to others! I remember the engaging lectures from my favorite professors where a 3-hour lecture just flew-by. Some of the best books I have read were difficult to put-down. Some of the hard problems I solved made me lose track of whether it was day or night. As we sift through posts, get up to date on all our social media channels, track all the thousands of influencers we follow, really question! Are we really learning or just familiarizing ourselves with the trending topics of the day! Just being familiar isn't really learning! You have to actively "be there" to engage and it requires time and attention. Focus on "doing" rather than sifting! --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app
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. Check out the upcoming speakers at: https://qusummerschool.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://Qu.Academy --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app
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Podcast Details

Created by
Sri Krishnamurthy
Podcast Status
Potentially Inactive
Started
Apr 26th, 2020
Latest Episode
Aug 1st, 2020
Release Period
7 per year
Episodes
6
Avg. Episode Length
34 minutes
Explicit
No
Order
Episodic
Language
English

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