I suspect the underlying problem here is that investors are more concerned about personal risk (being seen to make 'bad' investments) than they are about actual investment risk (net portfolio performance), because the former has near-term consequences and the latter does not.
The outcome is concentration, price inflation (good TVPI, poor returns), and a tendancy to compare against the herd rather than other asset classes or strategies.
If there was greater literacy on portfolio dynamics, finance and behavioral economics, venture investors would have greater risk appetite per-investment, a more contrarian posture, and deliver better returns (but perhaps worse TVPI, which is a persistent issue with incentives).
Appreciate the note Dan, and glad you've enjoyed reading. I agree there's a principal-agent problem here, but also lots of potential amendments are possible to the established investment approaches.
Settling for 3x shouldn't be the norm! Here's to having meaningful conversations with allocators to underwrite more tiny funds (as part of their flight to quality & barbell strategy).
P.S. Funny to see we both used the Fighting Temeraire in our recent posts ;)
Great read from an allocator perspective. You are correct, the biggest risk might be not taking enough risk. We're operating in an ecosystem flooded with capital and data, yet most funds keep chasing the same 'safe' deals: Ivy league founders, AI application layers, Silicon Valley postcodes. One problem is the way allocator's punish fund managers for both following and bucking trends: you get penalized for not joining the herd (even when it's wrong), and crucified for going your own way if it fails. This lose-lose dynamic is why so many keep playing it safe and that is why the next generation of top performers will be those brave enough to break the pattern backed by LPs like you!
Yavuzhan, this is a great read. At SignalRank we partner with almost 300 seed and Series A funds for their follow on Capital at B. We act as an LP in those B rounds. This effort to enable early stage investors to continue to help their portfolio companies results in an Index of top B rounds. Check it out at https://signalrank.ai
"In an industry of outliers, many allocators have ignored outliers for a long time and preferred funds that are sustainable, process-driven, big enough to scale relationships, often to settle with 3x returns over 12 years with no clear path to liquidity."
That's the infusion of method to madness. In an asset class as rife with uncertainty as the said one, finding patterns around outlier-detection-and-profit-making is a only a way to gain some control. It's easier to comment on why something is no longer serving well much after stabilisation to a certain extent has been received.
Thank you for the note. I agree that one needs pattern recognition of outliers, but 'outliers' is the key here, as methods can easily translate to drawing between the lines rather than looking harder to spot outliers.
I understand that. Definition of outliers has been a dynamic one from the outset ( pedigree, garages to cabal of investment bankers). To even define an outlier was to give some framework to an abstract concept, and hence, some sense of control.
That said, making a segue from a vintage’s definition of outliers might equate to taking more risk and expecting higher return (over 3x).
A great read, thank you for sharing Yavuzhan.
I suspect the underlying problem here is that investors are more concerned about personal risk (being seen to make 'bad' investments) than they are about actual investment risk (net portfolio performance), because the former has near-term consequences and the latter does not.
The outcome is concentration, price inflation (good TVPI, poor returns), and a tendancy to compare against the herd rather than other asset classes or strategies.
If there was greater literacy on portfolio dynamics, finance and behavioral economics, venture investors would have greater risk appetite per-investment, a more contrarian posture, and deliver better returns (but perhaps worse TVPI, which is a persistent issue with incentives).
Appreciate the note Dan, and glad you've enjoyed reading. I agree there's a principal-agent problem here, but also lots of potential amendments are possible to the established investment approaches.
Great read Yavuzhan!
Settling for 3x shouldn't be the norm! Here's to having meaningful conversations with allocators to underwrite more tiny funds (as part of their flight to quality & barbell strategy).
P.S. Funny to see we both used the Fighting Temeraire in our recent posts ;)
P.P.S. Big up to Juhana for sending me your way
Glad you've enjoyed reading it Saish.
Great read from an allocator perspective. You are correct, the biggest risk might be not taking enough risk. We're operating in an ecosystem flooded with capital and data, yet most funds keep chasing the same 'safe' deals: Ivy league founders, AI application layers, Silicon Valley postcodes. One problem is the way allocator's punish fund managers for both following and bucking trends: you get penalized for not joining the herd (even when it's wrong), and crucified for going your own way if it fails. This lose-lose dynamic is why so many keep playing it safe and that is why the next generation of top performers will be those brave enough to break the pattern backed by LPs like you!
Thank you Ayub, agree on the tension you've outlined, and glad you've enjoyed the article.
Yavuzhan, this is a great read. At SignalRank we partner with almost 300 seed and Series A funds for their follow on Capital at B. We act as an LP in those B rounds. This effort to enable early stage investors to continue to help their portfolio companies results in an Index of top B rounds. Check it out at https://signalrank.ai
Thanks Keith, glad you've enjoyed it.
"In an industry of outliers, many allocators have ignored outliers for a long time and preferred funds that are sustainable, process-driven, big enough to scale relationships, often to settle with 3x returns over 12 years with no clear path to liquidity."
That's the infusion of method to madness. In an asset class as rife with uncertainty as the said one, finding patterns around outlier-detection-and-profit-making is a only a way to gain some control. It's easier to comment on why something is no longer serving well much after stabilisation to a certain extent has been received.
Thank you for the note. I agree that one needs pattern recognition of outliers, but 'outliers' is the key here, as methods can easily translate to drawing between the lines rather than looking harder to spot outliers.
I understand that. Definition of outliers has been a dynamic one from the outset ( pedigree, garages to cabal of investment bankers). To even define an outlier was to give some framework to an abstract concept, and hence, some sense of control.
That said, making a segue from a vintage’s definition of outliers might equate to taking more risk and expecting higher return (over 3x).