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Understanding the Perfect R-Squared: A Quant Interview Deep Dive

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Manage episode 423228658 series 3426945
Content provided by QuantLabs.net. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by QuantLabs.net 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://player.fm/legal.

Join Brian from Quantlabsnet.com as he delves into a thought-provoking quant interview question sourced from StackExchange. In this episode, recorded on June 12th, Brian breaks down the concept of R-squared (R2) and its significance in statistical models, particularly in the context of investing.

Brian explains the definition and calculation of R-squared, emphasizing how a perfect R2 value of 1 indicates that all movements of a security are completely explained by an independent variable. He discusses the implications of a high R2 value and the potential pitfalls, such as spurious regression.

The episode explores various responses to the interview question, including the irony of needing an expected value when you already know the outcome. Brian also covers practical considerations like trading fees and taxes that can affect real-world applications of these models.

Whether you're preparing for a quant interview or just curious about advanced statistical measures in finance, this episode offers valuable insights. For more detailed discussions and resources, visit quantlabsnet.com.

  continue reading

100 episodes

Artwork
iconShare
 
Manage episode 423228658 series 3426945
Content provided by QuantLabs.net. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by QuantLabs.net 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://player.fm/legal.

Join Brian from Quantlabsnet.com as he delves into a thought-provoking quant interview question sourced from StackExchange. In this episode, recorded on June 12th, Brian breaks down the concept of R-squared (R2) and its significance in statistical models, particularly in the context of investing.

Brian explains the definition and calculation of R-squared, emphasizing how a perfect R2 value of 1 indicates that all movements of a security are completely explained by an independent variable. He discusses the implications of a high R2 value and the potential pitfalls, such as spurious regression.

The episode explores various responses to the interview question, including the irony of needing an expected value when you already know the outcome. Brian also covers practical considerations like trading fees and taxes that can affect real-world applications of these models.

Whether you're preparing for a quant interview or just curious about advanced statistical measures in finance, this episode offers valuable insights. For more detailed discussions and resources, visit quantlabsnet.com.

  continue reading

100 episodes

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