70 episodes

Flirting with Models is the show that aims to pull back the curtain and meet the investors who research, design, develop, and manage quantitative investment strategies.

Join Corey Hoffstein, Chief Investment Officer of Newfound Research, on a journey to explore systematic investment strategies, ranging from value to momentum and merger arbitrage to managed futures.

Episodes released in topic-specific seasons.

For more on Newfound Research, visit ThinkNewfound.com. And to learn about Newfound’s suite of mutual funds and other investment offerings, please visit ThinkNewfoundFunds.com.

Flirting with Models Corey Hoffstein

    • Zaken en persoonlijke financiën
    • 4.0 • 2 Ratings

Flirting with Models is the show that aims to pull back the curtain and meet the investors who research, design, develop, and manage quantitative investment strategies.

Join Corey Hoffstein, Chief Investment Officer of Newfound Research, on a journey to explore systematic investment strategies, ranging from value to momentum and merger arbitrage to managed futures.

Episodes released in topic-specific seasons.

For more on Newfound Research, visit ThinkNewfound.com. And to learn about Newfound’s suite of mutual funds and other investment offerings, please visit ThinkNewfoundFunds.com.

    What would Cliff Asness ask St. Peter at the pearly gates?

    What would Cliff Asness ask St. Peter at the pearly gates?

    In July 2020 I interviewed Cliff Asness, co-founder of AQR.  This was several months after he penned a perspective piece titled The Valuesburg Address, where he waxed poetic about the multi-year drawdown in the value factor.
    Nearly three years later, he recently wrote the perspective piece titled, The Bubble Has Not Popped.  I say wrote, but it is just a single image of the value spread between growth and value, adjusted for just about every possible noise factor you can imagine.  The spread still hovers near generational highs.
    This isn’t Cliff’s first value drawdown.  While never easy, I suspect his past experience at least makes it a bit easier.
    In this archive clip, I wanted to highlight the wisdom of experience.  To me, that entails understanding what you know, what you wish you could know, and what you believe.
    I hope you enjoy.

    • 19 min
    A data-driven approach to picking growth stocks and thematic baskets

    A data-driven approach to picking growth stocks and thematic baskets

    It’s no secret that high flying growth stocks were hammered in 2022, so I thought it would be fun to revisit my conversation with Jason Thomson back in Season 3.  
    Jason is a portfolio manager at O’Neil Global Advisors, where he manages highly concentrated portfolios of growth stocks.
    Now, Jason is a discretionary PM, which may seem like an unusual guest for a quant podcast.  But his approach is so data and process driven, it’s hard to tell the difference.  
    I selected a few questions about his take on growth investing in general, but I’d highly recommend you go back and listen to the original episode for his thoughts on portfolio construction and risk management as well.
    Enjoy!

    • 14 min
    How quants have changed equity markets and how discretionary managers can use this information to sharpen their edge

    How quants have changed equity markets and how discretionary managers can use this information to sharpen their edge

    After March 2020, a growing research interest of mine was the question, “how do strategies reflexively impact the markets they trade?”  Beyond crowding risk, can adoption of strategies fundamentally change market dynamics.
    In Season 3 Episode 11, I spoke with Omer Cedar, who argues that equity quants have done precisely that.  The mass adoption of factor models, whether for alpha or risk, fundamentally changed how baskets of stocks are bought and sold.  For a discretionary manager to ignore this sea change is to ignore a fundamental shift in the current of the water they swim in.
    In this clip from the episode, Omer discusses how quants have changed the market and how fundamental managers should use this information to sharpen their edge.

    • 18 min
    Replacing linear factors with a non-linear, characteristic approach in quant equity

    Replacing linear factors with a non-linear, characteristic approach in quant equity

    We’re back with another clip from the archives.  This time it’s Season 4 Episode 9 with Vivek Viswanathan.
    For three decades, equity quants have largely lived under the authoritative rule of the Fama-French 3 Factor Model and linear sorts.  In this episode, Vivek provides an cogent alternative to the orthodoxy.  Specifically, he explains why an unconstrained, characteristic-driven portfolio can more efficiently capture behavioral-based market anomalies.  I think this is a master class for alternative thinking in quant equity.
    It was really tough to clip this episode.  Vivek’s comments about Chinese markets provide a tremendous example about finding alpha in alternative markets.  But I’ll leave that for you to go back and dig out!
    Okay, let’s dive in.

    • 21 min
    Options, volatility, and the things we don't know we don't know (ARCHIVES S3E3)

    Options, volatility, and the things we don't know we don't know (ARCHIVES S3E3)

    We’re rewinding to Season 3, Episode 3 to chat with Benn Eifert, founder of QVR.  
    Benn was my first repeat guest and this is probably one of our more popular episodes.
    Instead of the usual interview format, I called this episode “Bad Ideas with Benn Eifert,” and basically just asked him a bunch of questions about naive option trades and whether they are a good idea or not.
    For anyone starting their journey with options or volatility, the whole episode is a must listen.
    The clips I chose here were selected because I thought they provided a really good cross-section of topics in the world of options while highlighting one important common thread: the risk of unintended bets.  I think this is one of the most universally important concepts in trading and investing, and Benn really drives the points home here as we cover topics ranging from writing options for income to why VIX minus realized doesn’t mean what you think it does.  The subtle through line is the reminder that it’s what we don’t know we don’t know that will eventually get us in trouble.

    • 18 min
    Formulating the machine learning problem, how research questions should be asked, and the trade-off of complexity versus accuracy (ARCHIVES S1E7)

    Formulating the machine learning problem, how research questions should be asked, and the trade-off of complexity versus accuracy (ARCHIVES S1E7)

    We’re trying something new here, folks.  I’ve got 5 seasons and 60 brilliant episodes and I thought it would be fun, in the off season, to go back to the archives and highlight past conversations.
    So using my trusty random number generator, I chose an episode at random.  So, we’re going back to 2018 to my conversation with John Alberg, co-founder of Euclidean Technologies, where machine learning is applied to the value investing problem.  
    The part I’m highlighting starts around minute 20 and is about the formulation of the machine learning problem and how the research question should be asked.  I like this section because I think it really highlights how we can think about the tradeoff of degrees of complexity versus accuracy and the problem of overfitting.
    Enjoy!

    • 15 min

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