Trading Technologies and CloudQuant Launch Strategic Partnership to Explore Creation of Alternative Data Offering
$TSLA Skyrocketed Ahead of Stock Split
Shown in the spikes in the acceleration of change of volatility spread.
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.
As Managed Funds decrease in popularity and Passive Funds take over there has been one bright spark for Fund Managers as Investors have realized that they can dramatically influence the behavior of companies through their investments.
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
Short-term ESG data is showing some very interesting opportunities. Our recent whitepaper shows that 5-day and 20-day positions profitable.
Spot checking the white paper shows the following simulated trades from last week.
The simulated trades were MOO on Monday, MOC on Friday.
Some traders are visually oriented. They need charts. As data scientists, we need to be able to present information in a way that others can understand. Presenting traders a candlestick chart is one of the best ways to transfer useful data.
✅ Demonstrate how to create a basic candlestick chart in Python 3
✅ Demonstrate how to highlight/annotate points on the chart
Topics covered in this post: Python, Plotly, OHLC, Candlestick Charts, Jupyter, Pandas, Traders
CloudQuant CEO John Morgan Slade will be taking part in THE TRADING SHOW – CHICAGO 2019 on Wednesday 8th May 2019. At 13:20 (Central) he will be partaking in a Panel to discuss “Deep Neural Networks – how supervised do deep learning machines need to be?” At 14:00 (Central) He will be moderating a discussion […]
CloudQuant LLC today announced the addition of RavenPack analytics within their trading strategy incubator. Crowd researchers can now use RavenPack historical data to discover tradable alpha signals on CloudQuant’s online Python and JupyterLab-based tools.