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.
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.
SMB Quant Video 1 – Developing a Model
Jeff Holden develops algo trading models at SMB Capital in New York. He utilizes CloudQuant extensively during his research and development process. In this video he details his process for developing an idea into a model.
In video two of SMB’s new Quant series Paul Tunney discusses why you should use CloudQuant to develop an algorithmic trading model.
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.
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 […]
Backtesting Trading Strategies
If you knew your trading strategy would work 50% of the time, would you commit your scarce savings to trade it? What if it worked 75% of the time? Backtesting gives one the confidence to know that your trading strategy will work.
“Bring us your ideas and we will share the money with you,” agreed Morgan Slade, CEO of the crowdsourced algorithmic trading startup CloudQuant. “For us, engagement means breaking it down into a contractible problem.”
Anyone who has ever worked on developing a trading strategy from scratch knows the huge amount of difficulty that is required to get your logic right. … TA-LIB Turbo-Charges Your Research Loop: TA-Lib is widely used by quantitative researchers and software engineers developing automated trading systems and charts. This freely available tool allows you to gather information on over 200 stock market indicators.