- 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…
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Tag Archives: Machine learning
In this article we list some of the reasons DLPAL does not include in trading strategy synthesis exits based on number of bars since entry. An example is included.
In this article we outline the steps for developing a trading strategy for TLT ETF using the delay trade input option. Out-of-sample performance is analyzed in Amibroker and Quantopian platform.
In this article we outline the steps for developing a trading strategy for XLF ETF. The out-of-sample performance is analyzed in the Quantopian platform and it is shown to significantly outperform the SPY benchmark.
Articles in mainstream media constantly praise the returns of some hedge funds and attribute them to quantitative trading. But can quantitative models extract billions of dollars worth of alpha from noisy data? Is it possible that these hedge funds have … Continue reading
The P-Dow indicator has generated the first bearish signal for stocks in about two months. Details and backtests are included below.
In this article we review a trading strategy developed with DLPAL and specifically the out-of-sample and forward performance using code generated for the Quantopian platform. The strategy outperforms the benchmark and year-to-date return is higher by about a factor of … Continue reading
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.