DLPAL LS uses primitive attributes of price action to extract features types in an unsupervised learning mode based on general feature clusters. Then, the program uses the extracted features in supervised learning mode to identify long and short candidates in a universe of securities.
DLPAL LS is used to develop algorithmic and machine learning strategies for directional and long/short trading. Users of the program can sort results based on different criteria and generate output for trading APIs. Historical files of features can be generated for backtesting the strategies and for machine learning. Click here for an article on strategy development and execution.
DLPAL LS does not require any programming. The program will output signals you can immediately use. Save time from programming and concentrate on your trading.
Click here for more information about the reduced functionality license and pricing.
Quantitative Scan of S&P 500 Stocks
Trading ES Futures with DLPAL LS
Equity Long-Short with Price Action Features
DLPAL LS Software with Reduced Functionality
Trade Minimum Holding Period Impact
Low Risk Equity Long/short
Combining Results of DLPAL LS and DLPAL DQ
Performance of DLPAL LS Features in 2018
A Novel Strategy
Three Long/Short Equity Strategies
Announcing The Release Of DLPAL LS v3.0
Long/Short FAANG Strategy In Weekly Timeframe
Market Neutral Long/Short Needs Few Stocks That Buck The Trend
Market Neutral Long/Short Equity Example
Market Neutral Long/Short Equity Strategies In High Demand
DLPAL LS Conservative Versus Normal Cluster
Stock Market Directional Bias Reversal
Feature Engineering With DLPAL LS
Long/Short Strategy For Dow 30 Stocks In Weekly Timeframe
Evaluation Of New DLPAL Clusters For Feature Generation
Announcing The Release Of DLPAL LS v2.0
Strategy Development And Execution With DLPAL LS
Market Neutral Long/Short Equity Strategy
Announcing The Release of DLPAL LS