Can we use Mixture Models to Predict Market Bottoms? by Brian Christopher - 25th April 2017

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Date and Time:
Tuesday, April 25th, 2017
8:00 PM IST | 09:30 AM CST | 8:30 AM MST

This session explains and illustrated the use of Mixture Models with a sample strategy in Python.

The webinar covers:
- Problem with Traditional Time Series Analysis
- Traditional issues with Asset Return Prediction
- Are Mixture models the solution?
- What are mixture models and how do they work?
- Can Gaussian Mixture Models (GMMs) model non-stationary data sets?
- Can Gaussian Mixture Models (GMMs) approximate non-linear data distributions?
- Designing and evaluating a trading strategy to test the application of GMMs
- Further areas and resources to explore in GMMs


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  1. QuantInsti Quantitative Learning
  2. python
  3. python trading
  4. mixture models
  5. algorithmic trading
  6. quantitative trading
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Комментарии
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Is it just me, or is the audio not synced correctly to the slideshow? Eg. at 14:40 and for a while after that, he's clearly talking about a previous slide

rodreynolds
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Thank you for your very explicit and very rich presentation. I want to run your model on my
 PC.Please send me the links allow me to download the python code of the GMM model and
the database.

Thanks for your understanding,

yvanngoyi
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Next time you consider doing a presentation you should think about being more organized and having your sides, lesson plan already put together before you attempt to do a presentation.

nackyding
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mkt is dynamic only way continous update skills for ttrading n

rksharma