Trading, Risk, and Reinsurance with Otakar Hubschmann


Manage episode 283894059 series 2632853
Player FM과 저희 커뮤니티의 Data Science Salon and Dat Science Salon 콘텐츠는 모두 원 저작자에게 속하며 Player FM이 아닌 작가가 저작권을 갖습니다. 오디오는 해당 서버에서 직접 스트리밍 됩니다. 구독 버튼을 눌러 Player FM에서 업데이트 현황을 확인하세요. 혹은 다른 팟캐스트 앱에서 URL을 불러오세요.

Our Senior Content Advisor Q McCallum sat down with Otakar Hubschmann, Head of Applied Data at TransRe, to talk about ML/AI in the world of reinsurance. They take a deep dive into the insurance industry and the role reinsurance plays there, with a side-trip to show how this differs from the quantitative finance you see in hedge funds. Along the way, Otakar offers his favorite tips for hiring data scientists. (Whether you're applying for a job, or hiring for one, take note.) Near the end of the episode, Otakar and Q mention some of their favorite books on risk, machine learning, and taking a quantitative approach to businesses. Here's the list they promised:

  • Against the Gods: The Remarkable Story of Risk (Bernstein)
  • Acts of God and Man: Ruminations on Risk and Insurance (Powers)
  • When Genius Failed (Lowenstein)
  • The Smartest Guys in the Room (McLean)
  • Moneyball (Lewis)
  • The Big Short (Lewis)
  • Models Behaving Badly (Derman)
  • The Gray Rhino (Wucker)
  • Bad Blood: Secrets and Lies in a Silicon Valley Startup (Carreyrou)
  • The Quants (Scott Patterson)
  • A Man for All Markets (Edward Thorp)
  • Fortune's Formula (Poundstone)
  • The Man Who Solved the Markets (Zuckerman)
  • Artificial Intelligence (Norvig)
  • Deep Learning (Goodfellow)
  • Python Machine Learning (Raschka)
  • Python for Data Analysis (McKinney)
  • An Introduction to Statistical Learning: with Applications in R (James, Wittin, Hastie, Tibshirani)
  • The Visual Display of Quantitative Information (Tufte)

Also, to learn more about the insurance industry, please check out David Wright's Not Unreasonable podcast. Otakar's interview on that show is the episode from November 02, 2020.

16 에피소드