Tag Archives: Machine learning
In this article, we present recent performance results of a market neutral long/short equity trading strategy executed in weekly timeframe for minimum transaction cost impact and lower risk in bear markets.
Validation of trading strategies is important for minimizing probability of Type-I error, or false discoveries. Below is an example of how to quickly validate strategies developed with DLPAL S on correlated but more importantly, anti-correlated securities.
Engineering of features with economic value, also known as attributes, predictors or alpha factors, is the first step in the extraction of market alpha. The example in this article shows proper classification of DJIA stocks in the weekly timeframe has … Continue reading
This article shows how to develop and execute a long/short equity strategy for Dow 30 stocks in the weekly timeframe with DLPAL LS software.
We evaluate the performance of two new clusters implemented in DLPAL LS for feature generation. We find that the new clusters can lead to increased performance. Especially one of these new clusters appears quite promising.