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The Macro Brief – Funding the future
24 Plays1 year ago
Mark McDonald, Head of Data Science and Analytics, looks at how venture capital is helping to fuel transformative technology and business innovation. Disclaimer: https://www.research.hsbc.com/R/51/9cHVhLJ Stay connected and access free to view reports and videos from HSBC Global Research follow us on LinkedIn https://www.linkedin.com/feed/hashtag/hsbcresearch/ or click here: https://www.gbm.hsbc.com/insights/global-research.
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Transcript
Podcast Introduction
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Welcome to HSBC Global Viewpoint, the podcast series that brings together business leaders and industry experts to explore the latest global insights, trends, and opportunities.
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Make sure you're subscribed to stay up to date with new episodes.
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Thanks for listening, and now onto today's show.
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The following podcast was recorded on the 10th of August 2023 by HSBC Global Research.
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All the disclosures and disclaimers associated with it must be viewed on the link attached to your media player.
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Remember, you can now subscribe to this weekly podcast on Apple and Spotify, or wherever you get your podcasts, by searching for The Macro Brief.
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Hello, I'm P.S.
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Butler in London and welcome to the Macrobrief.
Generative AI & Venture Capital Discussion
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Since the launch of ChatGPT back in November, investor interest in artificial intelligence and generative AI has surged.
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On today's podcast, we're going to focus on one important source of funding for this and other potentially transformative technologies, venture capital.
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This week, our data science team published a report on key developments in the venture capital industry.
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And Mark McDonald, head of data science and analytics, is here with me.
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Mark, thank you for joining us.
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Thank you for having me on the podcast.
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So Mark, what got you to look at the venture capital industry in the first place?
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In your intro, you mentioned generative AI, and I think this is a great example.
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What happens with venture capital flows can be an important source of information for investors more generally in public assets.
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So we've seen that ever since ChatGPT was released, this has spurred an intense focus on AI generally and generative AI specifically.
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And you can see that this has had a dramatic influence on equity markets.
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So in the piece, we have a chart comparing the behavior of the S&P 500 tech versus non-tech companies since that point.
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And there's been a dramatic
Venture Capital Trends & HSBC-VENT Introduction
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performance differential between the two, like over 30%.
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And so I think this is a great example of the ways that keeping an eye on the sort of behavior from venture capital investments and where are those funding flows going can be a very useful source of information for the market more generally.
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So of course the challenge with that remark is keeping an eye isn't as straightforward as it would seem there's a lot of data floating around and I guess that's where some of your data science tools come into play.
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Yes, I mean, I guess our team, we're probably the experts in the department at taking a new data set and trying to tease some interesting stories out of it.
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So I guess it fits more naturally with us than with anybody else.
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And so having looked at all this data, where are we in the state of the venture capital industry?
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There was obviously huge growth, but then a bit of a setback.
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Yes, absolutely.
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So if you look at the capital invested for venture capital through time, you can see there has, as you mentioned, been dramatic growth with a particularly high volume of capital deployed in 2021.
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And since that point, it's fallen back so that the in absolute terms, the level of capital being deployed by venture capital firms is kind of at similar levels to what we saw pre-pandemic.
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And so there are two ways of interpreting this.
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One way is to say, ah, 2021,
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was anomalous, and we've now come back to more typical levels.
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But of course, human nature and markets specifically don't really work like that.
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People make plans for the future based on what's been happening recently.
Historical Comparisons & Emerging Spaces
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And so it's not just the absolute level that's important in how it compares to recent history.
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And to illustrate this point, we created a measure called the HSBC-VENT,
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which tracks the level of capital deployment over the last quarter relative to the behavior over the last two years.
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And when you look at it on this basis, you can see that the scope of the collapse in funding being deployed is comparable scale to what we saw in the early 2000s,
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after the dot-com crash.
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And I think that is an interesting way of looking at things because it sort of highlights the sort of way in which these funding flows are much less than people were probably expecting two years ago.
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I noticed that, John.
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It's pretty striking, the falling off.
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But was I right in just observing that maybe it's bottoming up?
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Yeah, the last data points are ticking up a bit and associated with that, as the level of capital being deployed was falling, we also saw valuation multiples contracting significantly.
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And they've come back to more typical levels and are also showing signs of bottoming out in the recent data.
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So there are indications that that might be coming to an end.
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So let's step away from the sort of cyclical measures, if I put it that way, and look at the sort of longer term trends of where the VC investments have been heading to.
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Again, in your report, you have a great sort of box chart, which is color coded and kind of very quickly shows you where the money has been going.
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So maybe share that with our listeners.
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Yes, of course.
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So this is not just where the money is going, it's areas that are showing interest.
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So to look at this, we look at PitchBook data, and PitchBook have categories of investments which they call emerging spaces.
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So it's not just what's seeing the most investment flows, it's what's seeing the interest and what's growing unusually quickly.
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And there are lots of different individual emerging spaces that come out, but I'd say two common themes across all of them.
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One of them is AI and another one is sustainability.
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So across all these themes, the majority of them would have some kind of influence from one of those two factors.
Technology Growth & Late-Stage Investments
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In your report, you mentioned some other areas which captured the imagination like quantum computing, air taxis, gene therapies, small satellites, indoor farming.
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I mean, I guess these seem a little bit more peripheral, but your point is that this allows you to keep track of where perhaps interest is beginning to accelerate, and that is a precursor to what might happen in the public markets?
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Yes, exactly.
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These technologies, some of those more speculative disruptive technologies, they need venture capital funding in order to grow.
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But successful venture capital companies, they end up becoming big competitors to public companies,
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are acquired by public companies or public companies themselves.
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And so it is very, very helpful for investors to keep an eye on what's hot and where is this funding going because those investments today, they become the hot products of the future sometimes.
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Now, just a little bit more on the industry itself.
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In your report, you talk about the differentiation between early versus late stage and also exits.
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Just fill us out on that.
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So, yes, I think the stage that has seen quite a significant drop recently is late stage investments.
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And, you know, late stage investments, these are the ones that are often precursors to IPOs.
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And we've seen a concomitant fall in activity in the IPO market as well.
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And so I think this is something else that, you know, investors in public markets should be aware of.
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You know, there has been a crunch in that activity
Diversification & Venture Capital Data
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as well.
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You talk also about venture capital as a useful source of diversification, but against that it's more challenging obviously in terms of liquidity.
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So there are some investors who have a flexible enough mandate that they can allocate capital to these alternative asset classes.
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And if so, venture capital has some attractive qualities.
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Firstly, on the diversification space, these investments, they are equity investments, and so they're exposed to many of the same factors as equity markets.
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But if you calculate the measured correlations between returns in venture capital investments,
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with investments in public equity markets, then the correlations are positive, but nowhere near as strong as you might expect.
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And I think part of what's going on is that, you know, in public markets, it's always being marked a market where we're pricing in expectations.
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And if reality oscillates from kind of
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pretty good to not great, then market expectations tend to amplify that and it goes from perfect to terrible.
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And so you can really see this where we have a chart where we compare performance on an annual basis for venture capital and compare that to the NASDAQ.
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And you can see that in the bad years, even the bottom decile venture capital funds, their returns are not as bad as the return in the NASDAQ that year.
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And so I think this ability to kind of, you know, the fact that it's not being marked to market on a constant basis and you don't have to price in these very emotional swings can actually provide some downside protection and it reduces the measured correlations and thus the overall portfolio volatility.
00:09:34
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Well, it's a treasure trove of data, I must say, and fascinating, and there's been a lot of interest in this area.
00:09:39
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So is this going to form part of your regular suite of data sets that you publish?
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And maybe just to finish on, remind us of some of the other models that you publish on a regular basis.
00:09:49
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Yes, this data set, I think, should be interesting on an ongoing basis.
00:09:54
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So we publish this.
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in our data matters reports, which comes out monthly.
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I don't think there would be enough to say on a monthly basis here, but you'd imagine there'd be new signals on a quarterly basis that would be worth reporting on.
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So keep an eye out for that.
Data Matters Publication & Announcements
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Data matters more generally, this is our flagship data science publication.
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And it contains all our analysis with our predictive machine learning models, which answer sort of big picture directional questions for assets, either on an absolute return or a relative value perspective.
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And this is also the home of our regular listen up analysis, where we apply natural language processing technologies to earnings call transcripts.
00:10:37
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Mark, thank you so much for joining us today.
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Thank you very much, Piers.
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That's our macro brief for this week.
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Don't forget, you can subscribe to the podcast on Apple and Spotify or wherever you get your podcasts by searching for the macro brief.
00:10:54
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Also, a note for your diary.
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HSBC's Global Emerging Markets Conference is taking place online from the 18th to the 29th of September.
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If you're an HSBC client and would like to attend, then please get in touch with your HSBC sales representative.
00:11:08
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And finally, we here on The Macrobrief are taking a short break for the summer holidays.
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We'll be back again at the end of the month, but the team producing our Asia-focused podcast, Under the Banyan Tree, have just returned from their holidays, so don't miss out on their newest episode next week.
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That's with Asian Chief Economist Fred Newman and Head of Asia Equity Strategy, Harold van der Linde.
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So that's it from me, Piers Butler in London.
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Special thanks to Mark McDonnell for his insights on the VC industry this week.
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And thanks to our producer, Tom Barton.
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We'll be back soon.
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Thank you for joining us at HSBC Global Viewpoint.
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We hope you enjoyed the discussion.
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Make sure you're subscribed to stay up to date with new episodes.