You would have also very strongly outperformed the S&P 500. That is quite good.
When you backtest stock picks against SPY, you usually want to compare that portfolio to holding SPY levered to the same volatility (or just compare Sharpe ratios). Having a higher total return might mean that you picked good stocks, or it might just mean that you took on more risk. People generally care about return on risk rather than return on dollars, since sophisticated investors can take on ~unlimited amounts of leverage for sufficiently derisked portfolios.
In this case, the portfolio has a Sharpe ratio of 2.0, which is indeed pretty good, especially for an unhedged long equity portfolio, so props to NoahK! (When I worked at a hedge fund, estimated 2 Sharpe was our threshold for trades.) But it’s not as much of an update as 60% annual return would suggest on the surface.
That is… OK. Honestly, also looking at the composition of this index fund, I am not very impressed. Making only a 12% return in the year 2024 on AI stocks does feel like you failed at actually indexing on the AI market.
IRBO’s Sharpe ratio is below 1, which is pretty awful. In my not-financial-advice-opinion, IRBO is uninvestable and looking at the top holdings at the time of this interview was enough to recognize that (MSTR is basically a levered crypto & interest rate instrument, SPLK was a merger arb trade, etc.).
May I ask what hedge fund? Or at least what kind? From what I know, the big ones (Citadel, Millennium, etc.) target and achieve a Sharpe ratio of ~2.0 for the firm as a whole. Which means individual bets must be quite weak. If you could get 100 bets with a Sharpe of 2, you could have a 20.0 Sharpe portfolio, which would be roughly Virtu-level. And they’re scarcely a hedge fund; they market-make on a level that is essentially “the consistent provision of a service.”
Yeah, I was a little hand wavy with that, sorry. You’re right about Sharpe scaling with (the square root of) number of trades, but that gets dampened a lot by pairwise correlation between trades and correlated leverage/financing costs. I worked at a hedge fund that had a lot of siloed strategies (“pods”) and each one targeted a Sharpe of ~2, but then they would get sliced and diced into end products for investors with different risk levels etc. (I never worked on that side of the firm and tbh do not know all the details of how that works).
In practice, you actually care about incremental Sharpe, which you get by subtracting the Sharpe of your strategy minus the covariance-adjusted Sharpe of your existing portfolio over the norm of the covariance matrix, and you want to keep that pro-forma portfolio Sharpe above 2. It would be awesome to have 100 uncorrelated bets each with a 2 Sharpe, but in practice our strategy was so specific that a lot of our trades were still pretty correlated and created incremental transaction and hedging costs. And beyond being directly correlated (if position A goes up position B will also go up), the structure of a pod means you introduce auto-correlation (if our financing rate goes up all of our positions will have reduced Sharpe, or if one position blows out we will have to exit multiple other trades suboptimally) so you end up getting pretty high covariance matrix norms. The cutoff for a standalone position is maybe like 1.2-1.5 Sharpe, if that position is small enough relative to the overall portfolio that you can just think about marginal Sharpe as a first-order effect. So a little lower but still pretty non-trivial for an individual investor picking single stocks to achieve, and in the case of this discussion—a pretty concentrated, highly auto-correlated, long-only equity portfolio—I don’t think it’s unreasonable to just round off individual thresholds to 2.0 even if it’s more like 1.8 or 1.9.
When you backtest stock picks against SPY, you usually want to compare that portfolio to holding SPY levered to the same volatility (or just compare Sharpe ratios). Having a higher total return might mean that you picked good stocks, or it might just mean that you took on more risk. People generally care about return on risk rather than return on dollars, since sophisticated investors can take on ~unlimited amounts of leverage for sufficiently derisked portfolios.
In this case, the portfolio has a Sharpe ratio of 2.0, which is indeed pretty good, especially for an unhedged long equity portfolio, so props to NoahK! (When I worked at a hedge fund, estimated 2 Sharpe was our threshold for trades.) But it’s not as much of an update as 60% annual return would suggest on the surface.
IRBO’s Sharpe ratio is below 1, which is pretty awful. In my not-financial-advice-opinion, IRBO is uninvestable and looking at the top holdings at the time of this interview was enough to recognize that (MSTR is basically a levered crypto & interest rate instrument, SPLK was a merger arb trade, etc.).
May I ask what hedge fund? Or at least what kind? From what I know, the big ones (Citadel, Millennium, etc.) target and achieve a Sharpe ratio of ~2.0 for the firm as a whole. Which means individual bets must be quite weak. If you could get 100 bets with a Sharpe of 2, you could have a 20.0 Sharpe portfolio, which would be roughly Virtu-level. And they’re scarcely a hedge fund; they market-make on a level that is essentially “the consistent provision of a service.”
Yeah, I was a little hand wavy with that, sorry. You’re right about Sharpe scaling with (the square root of) number of trades, but that gets dampened a lot by pairwise correlation between trades and correlated leverage/financing costs. I worked at a hedge fund that had a lot of siloed strategies (“pods”) and each one targeted a Sharpe of ~2, but then they would get sliced and diced into end products for investors with different risk levels etc. (I never worked on that side of the firm and tbh do not know all the details of how that works).
In practice, you actually care about incremental Sharpe, which you get by subtracting the Sharpe of your strategy minus the covariance-adjusted Sharpe of your existing portfolio over the norm of the covariance matrix, and you want to keep that pro-forma portfolio Sharpe above 2. It would be awesome to have 100 uncorrelated bets each with a 2 Sharpe, but in practice our strategy was so specific that a lot of our trades were still pretty correlated and created incremental transaction and hedging costs. And beyond being directly correlated (if position A goes up position B will also go up), the structure of a pod means you introduce auto-correlation (if our financing rate goes up all of our positions will have reduced Sharpe, or if one position blows out we will have to exit multiple other trades suboptimally) so you end up getting pretty high covariance matrix norms. The cutoff for a standalone position is maybe like 1.2-1.5 Sharpe, if that position is small enough relative to the overall portfolio that you can just think about marginal Sharpe as a first-order effect. So a little lower but still pretty non-trivial for an individual investor picking single stocks to achieve, and in the case of this discussion—a pretty concentrated, highly auto-correlated, long-only equity portfolio—I don’t think it’s unreasonable to just round off individual thresholds to 2.0 even if it’s more like 1.8 or 1.9.