- 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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Category Archives: Trading Strategies
Short-term portfolio trading strategies can generate absolute returns during times that longer-term strategies experience a drawdown. In this article we include an example of how to use DLPAL to develop of strategy for trading Dow stocks.
Although the high of VIX was below 11 on January 27 of this year, the SPY ETF has gained 1.11% since. Some traders expected a quick rise in volatility and shorted the market but any gains in VIX evaporated fast … Continue reading
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.
In this article we list the validation tools provided by DLPAL. Validation methods are an important integral part of strategy development. DLPAL offers different validation methods to increase the significance of the results.
In this article we show one way DLPAL can be used to execute a long/short equity strategy. The features generated by the p-indicator function of the program are used to identify long and short candidates. An example is included.
Price Action Lab Blog Blog offers signals generated by three strategies and also has a strategy developed via machine learning tracked in the Quantopian platform. Below are performance details for 2016.