4 ms·
What do you suspect they are using?
by max_ 2y ago
What do you suspect they are using?
- meowkit 2y agoThey pull data from all kinds of things now. For example, satellite imagery of trucking activity correlated to specific companies or industries. Its all signal processing at some level, but directly modeling the time series of price or other asset metrics doesn’t have the alpha it may have had decades ago.
- greatpostman 2y agoAlternative data is passed into time series models. They are features. You don’t know as much about this as you think
- myhf 2y agoemoji hand pointing up
- nextos 2y agoSome funds that tried to recruit me were really interested in classical generative models (ARMA, GARCH, HMMs with heavy-tailed emissions, etc.) extended with deep components to make them more flexible. Pyro and Kevin Murphy's ProbML vol II are a good starting point to learn more about these topics. The key is to understand that in some of these problems, data is relatively scarce, and it is really important to quantify uncertainty.
- lopatin 2y agoI know next to nothing about this. How do people make use of forecasts that don't provide an uncertainty? It seems like that's the most important part. Why hasn't bayseyan statistics taken over completely?
- nextos 2y agoBayesian inference is costly and adds a significant amount of complexity to your workflow. But yes, I agree, the way uncertainty is handled is often sloppy. Maximum likelihood estimates are very frequently atypical points in the posterior distribution. It is unsettling to hear people are using this and not computing the entire posterior.
- deleted 2y ago[deleted]