It does seem plausible there are not many yet. If you do a google news search on fundseeder it comes across as a startup just beginning to sort itself out (appointment of new CIO, CSO and external funding just recently for example). I also received an email from them recently which suggested things are moving forward. So, it's too early to read anything into it I think, basically.

So, FS are pushing a "Virtual Summit" (free) for traders to attend online (https://www.summit.fundseeder.com/welcome). Surely if you are good enough to be trading real money profitably and serious enough to be interested in funding that list of speakers is a bit, you know, "retail"?

FundSeeder needs to revise their performance metrics by which they rank the trading accounts. In their leader-board, the #1 ranked account has a 1.7% annualized return, 3.5% cumulative return over the last 2 years, and the $4,800 account balance. That's especially ironic, given that the FundSeeder rank calculation formula is "proprietary".

Well it seems to be more or less a version of the probabilistic Sharpe Ratio (ie it doesn't just look at average returns over standard deviation of returns but incorporates skew and kurtosis of those returns). This makes sense and helps to penalise highly negatively skewed, high kurtosis strategies like selling vol. But yes they should also consider, if not already, penalising high correlation with the s&p500 and high correlation with a simple compounding bank account like structure. That would weed out that #1 account and also penalise many of the leaders which are in effect just long stocks in massive bull market.

Yep, my account jumped from #33 to #16 in one day last Friday, and all I had was a very small gain on that day. So, it does appear that many of the top FS accounts have a high correlation with the S&P 500 index.

I agree with penalizing the negative skewness, but the penalty for the high kurtosis is debatable. The FundSeeder's definition of kurtosis is wrong. Here is what it says: Kurtosis is a measure of peakedness (or flatness). And here is what Wikipedia says: Kurtosis measures outliers only; it measures nothing about the "peak". Now that we got this out of the way, consider a return distribution with a normal left tail, and a fat right tail. This would have the high kurtosis (by Wikipedia's definition). Would you really want to punish a trader who has a large number of abnormal gains?

That would give a strongly positive skew which would increase your FS score. If you look at the definition of sample kurtosis on the wikipedia page the powers used are 4 and 2. So kurtosis is a measure of the "symmetric" fatness around the mean (ie the value of kurtosis increases for negative and positive deviations from the mean more than that measured by variance/standard deviation). Does the gain in FS score from positive skew balance out any effect of increased kurtosis? Not sure, but there is "a" balancing effect.