Investing in ESG has been crazy in the past few months. A recent market-neutral backtest showed a 8.73% return (Sharpe of 4.98) for the period of January 1, 2020, to April 22, 2020.
Short-selling opportunities exist using ESG Alternative Data
A long-short portfolio outperforms the equal-weight S&P 500 ETF by 37.9%/year (after transaction costs) using Precision Alpha Alternative Data. Over 91.5% of the total return is pure alpha.
In our study of Environmental, Social, and Governance (ESG) data, we looked at holding positions based upon the G&S Quotient short term price predictor score. We found that 5-day holds and 20-day holds using this score were very interesting and produced positive returns. Based on this data set we saw that you could have traded and held some of these stocks and closed your positions at the end of the day last Friday. See the charts for $ADBE, $AAPL, $MSFT, and $LDOS
CloudQuant LLC has proven the value in the G&S Quotient Environmental, Social, and Governance (ESG) alternative dataset. The detailed data science study shows a long-short portfolio with a five-day or twenty-day position holding period produces an investment strategy with single year Sharpe Ratios as high as 2.046 and Alphas as high as 5.24%. The study shows that the dataset is highly distinct from other standard and so-called “smart-beta” factors.
What effect can alternative data sets have on trading algorithms? We asked a few of our teammates and systematic traders what the effect of alternative data sets is on trading algos. We thought we could spread some insight as to why our alternative data is so valuable the also developers. We all start using the […]
The CloudQuant team discusses their helpful thoughts for beginners on CloudQuant. We want to boost everyone starting out on our platform in their algo development and backtesting.
Everyone in our company uses the CloudQuant website and coding platform in one way or another. We all use our own application, just like the crowd researchers. When we say that our free backtesting tools are “institutional grade” we really mean it. Every algo we run in our trading and investment strategies is proven in the same backtesting engine as the crowd uses. We rely on the scorecards, the reports, and the simulated trades to ensure that our trading is successful.
CloudQuant’s portfolio managers and quantitative algo traders look back on their starts in Algorithmic Trading. This candid overview allows everyone to see the “Things We Wish We Knew When We Started AlgoTrading”. This is a short collection of the interviews with some of our amazing coders here in the office
Regular Trading Hours in the US Stock Market is 9:30 a.m. – 4:00 p.m. Trading can happen in the pre-market hours (4:00 a.m. – 9:30 a.m. ET) and in the After Hours market (4:00 p.m. – 8:00 p.m.). The free historical market data in CloudQuant allows you to examine the spread data and the differences between sessions.
On May 15th Trevor Trinkino presented part two of a three-part Machine Learning webinar with FXCM. Part one is here. Part 2 – Preprocess data for Random Forest. PnL and prediciton improvements… In part two Trevor goes over how to clean and pre-process data from CloudQuant to use in a Random Forest Classifier. He then looks at the […]