I can also confirm this. I used to curate data and develop equities forecasts professionally for about 30 or so funds, including Citadel and Two Sigma. It’s getting harder to build a successful trading strategy based on “quantamental” analysis alone (“alternative data”) each year.
A lot of fundamental hedge funds turned to this in the early 2010s as awareness of big data became a thing, thinking they could close the performance gap with the quant funds. It didn’t work. The quant funds that purchase this data use it as only one dimension of analysis to confirm a hypothesis which has already been empirically tested across many other inputs.
I have a specific example I can talk about, because my old firm abandoned the data: I found a reliable method for predicting exactly how many Model X and Model S vehicles Tesla sold well before earnings each quarter of 2017, including complete configuration data for each vehicle. Even with that KPI in hand, I couldn’t successfully forecast where the stock would go after each earnings call.
A lot of fundamental hedge funds turned to this in the early 2010s as awareness of big data became a thing, thinking they could close the performance gap with the quant funds. It didn’t work. The quant funds that purchase this data use it as only one dimension of analysis to confirm a hypothesis which has already been empirically tested across many other inputs.
I have a specific example I can talk about, because my old firm abandoned the data: I found a reliable method for predicting exactly how many Model X and Model S vehicles Tesla sold well before earnings each quarter of 2017, including complete configuration data for each vehicle. Even with that KPI in hand, I couldn’t successfully forecast where the stock would go after each earnings call.