- Price Action Lab Blog Strategies Performance in 2016
- Machine Learning With DLPAL PRO: Part Three
- Announcing The Release of DLPAL v1.0
- Announcing The Release of DLPAL PRO
- Machine Learning With DLPAL PRO: Part One
- Automatic Code Generation For Quantopian Platform
- Data-mining And Validating Thousands Of Potential Price…
- Deterministic Machine Design of Trading Systems With Strict…
- Asset Allocation (30)
- Economic Analysis (83)
- Forex trading (8)
- Machine learning (8)
- Market Statistics (351)
- Premium Content (210)
- Premium Signals (15)
- Price Action Lab Alerts (133)
- Price Action Strategies (160)
- Quantitative trading (147)
- Risk Management (52)
- Strategy Synthesis (90)
- Technical Analysis (836)
- Trading Strategies (162)
- Trend following (63)
- Uncategorized (42)
Category Archives: Machine learning
In this article we compare the out-of-sample performance of a trading strategy and a machine learning model that use the exact same features.
In this article we include R code for applying binary logistic regression classification to attribute data generated by DLPAL PRO and scoring a new instance.
We are pleased to announce that a demo version for DLPAL PRO v2.0 is now available for download. Demo users can generate unlimited historical attribute files for unlimited securities to test with machine learning for a full 20 days with … Continue reading
DLPAL PRO’s advanced capabilities are used to implement a long/short ETF strategy. We present the flow and examples of historical attribute, test/train and scoring files. A Binary Logistic Regression classifier is used to obtain the final results.
We are pleased to announce the release of v2.0 of DLPAL PRO. This new version offers generation, updating and creation of train/test and scoring files with just a few mouse clicks. The generated files can be used with machine learning … Continue reading
In this article we show how to prepare historical files with continues features and a discrete target for an ensemble of securities using DLPAL PRO. Then, we apply machine learning on a random sample of half of the data and … Continue reading
In this article we show how to prepare historical files with continues features and a discrete target using DLPAL PRO. Then, we apply a binary logistic regression classifier on a random sample of half of the data and test the … Continue reading
DLPAL workspace and deep learning results for DOW-30 stocks as of the close of Friday, October 21, 2016.