Comments (5)
@waudinio27 Thanks Matthias for your interest and the kind words :-)
Concerning your questions:
Would this program be suited for the prediction of stock market returns with the StudenT distribution shown in the examples?
Generally, I am not sure if stock market returns can be predicted with high accuracy at all. So I would leave this to your expertise. Yet, if the returns can be approximated with a StudentT, you can give it a try.
Would normal Close Price data work with LightGMBLSS as well, or does it struggle with data that was not seen in the train data?
This is an important question, since it highlights an important drawback of tree-based models in general to forecast beyond unseen train data. This is true for all tree based models, since the forecasts would be the terminal-node means. Hence, for a dataset with strong trend, basic tree-based models would provide flat forecasts that vary with the seasonality, as shown in the following plot
However, there is this option in LightGBM, linear_tree=True
that fits a linear model at each leaf. Hence, this allows you to forecast data with strong trend for example, something which is not possible with the default implementations.
Do you plan to implement a Cauchy distribution as well at one point?
Currently, this is not on my list. I suggest you try the StudentT first and see how it goes
How would the out-of sample prediction work out for some timesteps into the future after the train test phase?
You can either train the model for one-step ahead forecasts and then enroll the model along the forecasting steps. This makes sense if you have lagged features or rolling means etc. Another way of doing this is to directly forecast for the entire horizon.
from lightgbmlss.
Hello Mr. März!
Thanks a lot for the detailed answers. You should consider at one point publishing your work on Medium to bring it to a bigger audience. I will try to implement a time series with the linear_tree and come back to you for questions if I get stuck, if this is okay for you.
Once again, this is a great program. Maybe you can add at one point a notebook that shows how to forecast as well to the examples.
And yes, you are right. It is possible stock market prices are not predictable. Maybe with your program one could build something to just follow the trend I was thinking today.
Greetings
from lightgbmlss.
@waudinio27 Yes sure, let me know if you need some assistance.
from lightgbmlss.
@waudinio27 Can I close the issue?
from lightgbmlss.
Yes.
from lightgbmlss.
Related Issues (20)
- General Discussion HOT 3
- Multi-parameter optimization with custom loss function for probabilistic forecasting HOT 6
- ETA for code HOT 2
- Binary Classification HOT 6
- [Feature request] latest lightgbm support HOT 2
- Monotonicity of expectiles HOT 2
- Can't install on Ubuntu 20.04 HOT 2
- Userdefine CV Class?
- Lower python version support
- error when using weights in lgb.Dataset HOT 3
- Models with init_score HOT 8
- Silent freezes HOT 3
- Zero-and-One-Adjusted Beta HOT 1
- kwargs from the lightgbm predict are not available with the LightGBMLSS.predict HOT 5
- lightgbm v4.0.0? HOT 3
- Multi-task learning and ONNX support
- IndexError: LightGBMLSS.train(valid_sets=[dataset_val]) calls set_valid_margin, which seems to expect both train+val HOT 7
- Prediction of quantiles for parametric distributions HOT 5
- SHAP interpretations from zero-adjusted gamma model HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from lightgbmlss.