Big tech is transforming every aspect of our world. But how, and at what cost? This season of Land of the Giants – The Disney Dilemma – focuses on Disney’s ability to weather the ups and downs of the business cycle and changing tastes and explores what has kept it successful for over 100 years. The entertainment giant has leveraged nostalgia and its intellectual property to build a beloved brand, but after an acquisition spree that included Marvel, Lucasfilm, and 20th Century Fox, can it sus ...
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Bayesian Neural Networks
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Manage episode 448852041 series 2686124
Content provided by The Quant / Financial Engineering Podcast and Patrick J Zoro. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Quant / Financial Engineering Podcast and Patrick J Zoro or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Edris Loftpouri MFE /24 discusses his interest on the implementation of Bayesian Neural Networks (BNNs) for macroeconomic forecasting. He also touches on Castastrophe Modeling https://www.linkedin.com/in/patrick-z-08bb5b5a/ https://www.linkedin.com/company/lehigh-master-in-financial-engineering/ This project develops a Bayesian Neural Network (BNN) for macroeconomic forecasting, using stochastic volatility and Bayesian shrinkage priors to manage complex, high-dimensional data. With layer-specific and neuron-specific activation functions, the model captures both long-term dependencies and short-term nonlinear dynamics. Offering adaptive uncertainty quantification and robust volatility handling, it’s ideal for risk analysis, economic policy, and quantitative finance applications. https://www.linkedin.com/in/edris-lotfpouri/
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59 episodes
MP3•Episode home
Manage episode 448852041 series 2686124
Content provided by The Quant / Financial Engineering Podcast and Patrick J Zoro. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Quant / Financial Engineering Podcast and Patrick J Zoro or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Edris Loftpouri MFE /24 discusses his interest on the implementation of Bayesian Neural Networks (BNNs) for macroeconomic forecasting. He also touches on Castastrophe Modeling https://www.linkedin.com/in/patrick-z-08bb5b5a/ https://www.linkedin.com/company/lehigh-master-in-financial-engineering/ This project develops a Bayesian Neural Network (BNN) for macroeconomic forecasting, using stochastic volatility and Bayesian shrinkage priors to manage complex, high-dimensional data. With layer-specific and neuron-specific activation functions, the model captures both long-term dependencies and short-term nonlinear dynamics. Offering adaptive uncertainty quantification and robust volatility handling, it’s ideal for risk analysis, economic policy, and quantitative finance applications. https://www.linkedin.com/in/edris-lotfpouri/
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