New Research: A Machine Learning-Based Trading Strategy Using Sentiment Analysis Data
USING EQUITY SENTIMENT INDICATORS WITH TRADITIONAL FACTORS ENHANCE RETURNS
Article source: RavenPack
Lucena Research uses RavenPack Equity Indicators in two strategies. First, Lucena constructs a portfolio by using the RP Indicators together with a 5-day momentum factor and, secondly, it combines them with other factors selected by Machine Learning in the Lucena QuantDesk® platform.
Lucena found that constructing portfolios using sentiment indicators jointly with traditional factors can result in significant outperformance versus the S&P 500 benchmark over their Jan 2005 to Nov 2014 backtesting period. In particular, with machine learning, Lucena finds P/E ratios and moving average crosses to work well with the sentiment indicators, delivering:
- an outperformance of 339% against the benchmark over the period
- a Sharpe Ratio of 0.83 versus 0.46
This figure shows the return profile of the strategy suggested by Lucena’s QuantDesk® platform on the S&P500.
Source: Lucena Research, RavenPack February 2015
To view the original article and to request the white paper, visit: RavenPack Company News: Machine Learning Based Trading Strategy Using Sentiment Analysis Data