Ever wondered if backtesting can really predict future investment success?In this episode of Quant Radio, our AI hosts dive deep into the three key types of backtests: walk-forward testing, resampling, and Monte Carlo simulations. Using simple, relatable analogies, they explain the pros, cons, and common pitfalls of each method.Whether you're new to finance or looking to refine your investment strategies, this episode will give you insight into using backtesting effectively while avoiding the traps of survivorship bias and data snooping.Tune in to discover why backtesting is a helpful tool but not a foolproof prediction method, especially in quantitative trading and quantitative analysis.For more quant-focused content, join us at https://community.quantopian.com. There, you can explore a wealth of resources, connect with fellow quants, engage in insightful discussions, and enhance your skills through our extensive range of online courses.Quant Radio is an AI-generated podcast, intended to help people develop their knowledge and skills in Quant finance. This podcast is not intended to provide investment advice.

Former practicing quant and current AWS executive, Jason Strimpel, discusses his journey from web development to mastering trading technologies, overcoming personal struggles, and the balance of work, family, and business ventures. He explores complexity in trading, algorithmic trading projects, and open-source community engagement, offering insights into software implementation and portfolio optimization data sets.

Christina Qi founded DomeYard, a high frequency trading hedge fund. In this incredibly candid interview, she takes us through DomeYard's founding, shutdown, and all the adventures in between. Disclaimer Quantopian provides this presentation to help people learn about quant finance - it is not intended to provide investment advice. More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian. In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.

This episode is with Thomas Wiecki, who was one of the first Quantopian employees and lead our data science efforts. Thomas is well-known among Bayesian practitioners, as well as the python community. We talk about his perspective on Quantopian, his own company PyMC Labs, what he took away from the whole experience, and what he is interested in creating in the future.

Anju is the founder of Eventvestor. In this episode, he shares his journey and some of the big lessons from building his own company, as well as a prediction for the future role of quant in investing.

If you were at the top of your field in computer science, pursuing post-doc research and publishing frequently, would you consider moving to industry? Would finance be a draw? Many quants start in academic positions and move to finance; a rare few manage to do both. This week we will get to know Yuri Malitsky, who has done top tier computer science research in academia, ML research at IBM Watson, data science and trading at JP Morgan, and most recently he directs product analytics for a major financial data provider. All along the way, he has kept his academic connection — lately by lecturing at the University of Virginia’s Data Science program. Yuri has a voracious curiosity that takes him on many interesting adventures in machine learning, AI, game development, finance, and large scale software development. A consistent theme for his work is automating large and complex processes. In this interview, Yuri shares his favorite quant interview question, his prediction for the next 18 months in AI, and thoughts on AI powered software development.

Welcome to the Quantopian Retro, a short series of interviews of Quantopian teammates, community members, and outside quants/experts. The goal of the series is to look back on Quantopian and reflect on what went right, what went wrong, and what we can learn from it all. This episode is with Dan Whitnable, erstwhile head of community at Quantopian. Dan was an engineer and started using Quantopian for his own trading. Over time, he became a major contributor to the Quantopian user forums and eventually joined Quantopian to work with the community full time. Dan has a unique mix of internal and external perspectives on Quantopian. I hope everyone enjoys his insights as much as I did. Have questions or ideas about the retro? Someone you want me to interview? Drop me a line via feedback at quantopian, or make a comment.thanks,fawce Disclaimer Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice. More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian. In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.

Welcome to the Quantopian Retro, a short series of interviews of Quantopian teammates, community members, and outside quants/experts. The goal of the series is to look back on Quantopian and reflect on what went right, what went wrong, and what we can learn from it all. This episode is with my friend and Quantopian CTO/co-founder, Jean Bredeche. Jean has many strengths, in this episode I hope you will be able to appreciate his easy candor and warmth, hear his motivations, and understand what he learned from building Quantopian. Have questions or ideas about the retro? Someone you want me to interview? Drop me a line via feedback at quantopian, or make a comment.thanks,fawcep.s. You can sign up for our weekly newsletter at www.quantopian.com. Disclaimer - Not Advice Quantopian provides this presentation to help people learn about quant finance, algorithmic trading, and related topics - it is not intended to provide investment advice. More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian. In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the videos, newsletter issues, social media posts, or website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.