The Venture Capital Case Study: What to Expect and How to Survive

Поделиться
HTML-код
  • Опубликовано: 9 июл 2024
  • Learn more: breakingintowallstreet.com/ve...
    For all the files and resources and a written version of this tutorial, please go to:
    mergersandinquisitions.com/ve...
    Table of Contents:
    0:00 Introduction
    1:58 Part 1: What to Expect in VC Case Studies
    3:10 Part 2: What Do VCs Want in Early-Stage Investments?
    4:51 Part 3: “The Numbers” for PitchBookGPT
    8:16 Part 4: The Market, Product, and Team
    11:45 Part 5: Recommendation and Counter-Factual
    13:04 Recap and Summary

Комментарии • 10

  • @financialmodeling
    @financialmodeling  Год назад

    For all the files and resources and a written version of this tutorial, please go to:
    mergersandinquisitions.com/venture-capital-case-study/
    Table of Contents:
    0:00 Introduction
    1:58 Part 1: What to Expect in VC Case Studies
    3:10 Part 2: What Do VCs Want in Early-Stage Investments?
    4:51 Part 3: “The Numbers” for PitchBookGPT
    8:16 Part 4: The Market, Product, and Team
    11:45 Part 5: Recommendation and Counter-Factual
    13:04 Recap and Summary

  • @Latin_American_Economic
    @Latin_American_Economic Год назад +5

    From someone in venture debt in Silicon valley the 5x - 10x revenue multiple is pretty much in line with what we often see. Anything above that, does happen, but are often outliers like what happened during the pandemic. I would also add that since we are looking at a SaaS business model, once we take into account churn rate the probability of 100% market dominance is unlikely so yes a 10% - 20% looks more likely. Wonderful job, gave me a new perspective on the VCs funding such startups so thank you for sharing.

    • @financialmodeling
      @financialmodeling  Год назад +1

      Thanks! Glad to hear it. Yup, I didn't even mention the churn rate but that is a factor as well - especially for something like this which is "enterprise" but also not highly integrated into customers' workflows. Churn would probably be less of a factor for a very complex $100K+ per year product like an ERP system.

  • @noor-hj4fn
    @noor-hj4fn 10 месяцев назад

    Hey Brian, return offers are low for summers in both NY & London. I know FT recruiting will be heavily affected, but do you think getting a summer in 2024 will be as difficult?

    • @financialmodeling
      @financialmodeling  10 месяцев назад

      In the U.S., the 2024 summer internship recruiting season is already over. It starts ~1.5 years in advance of summer internships and finishes up quite early as well. Yes, banks have probably reduced the number of spots available for interns, but not by a huge amount because they always need new Analysts coming in. In other regions with slower recruiting timelines, yes, there will probably be a modest reduction in the number of internships available.

  • @georgebritto416
    @georgebritto416 Год назад

    First one to like

  • @mandateonmandalay7632
    @mandateonmandalay7632 Год назад

    Why 100 x is a must. Just like in the crypto market every person chasing 100 x return. The only difference here is bankers doing slightly more DD. Form the statistical standpoint the variables you just used to evaluate for this startup look so narrow and not significant enough to predict whether they can eventually be reached to 1~2 Bil valuation. Might have lost the opportunity due to a lack of time and variables to analyze for a proper outcome. AI should have fill that kind of gap. Just my humble opinion.

    • @financialmodeling
      @financialmodeling  Год назад +1

      100x isn't a "must," it's a "potential target if everything goes very well," and we don't think that is plausible. Even something like 10x may be a stretch for this company because the asking price is too high.
      This is a *60-minute* case study where you have to read quickly and make a decision backed up with some numbers and thoughts. You don't have time to do a statistical analysis or do anything complicated. Obviously, if you had 5-10 hours or a week or something similar, you would do more research.
      But a quick read of the numbers and some knowledge about the market tells you this will probably not work. It's just too narrow a use case with unclear product/market fit, which is actually a bigger issue than any single number.