Share New Research 
Hello, I would like to use local equity history data for producing candle stick charts to compare entries/exits of various local backtests. I would like to use an angular front end, not a Jupyter notebook, so I tried loading the QC dll's using pythonnet and use QuantBook but ran into many many issues (currently here: https://www.quantconnect.com/forum/discussion/14428/loading-quantbook-locally-outside-of-research-using-pythonnet ), but if I am successful with that approach, it would be very hard for others to reproduce the various changes if I want to share the project for other people to use.
What is the default data normalization mode for the daily usa equity data files saved locally? If it is not adjusted, is there a simple process to get the adjusted data? I can try to load the history in a QC jupyter notebook and output the df in a csv however I am trying to avoid extra setup steps for others.
Derek Melchin
Hi No Name,
The US Equity files contain raw data (DataNormalizationMode.Raw).
To adjust the data, we need to use the factor files from the US Equity Security Master. The easiest way to adjust the data is to make a history request and set the dataNormalizationMode argument to DataNormalizationMode.Adjusted.
Best,
Derek Melchin
Want to invest in QuantConnect as we build the Linux of quant finance? Checkout our Wefunder campaign to join the revolution.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Non Compete
thanks Derek, I just went with a Jupyter notebook which uses the QuantBook to read the local data in normalized mode and write it out again, and adds technical indicators to it as well before writing. I think within the next couple weeks I will be able to open source my visualization tool. I'm using ag-grid and highcharts stock charting for now and already have the ag-grids set up.
Non Compete
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
To unlock posting to the community forums please complete at least 30% of Boot Camp.
You can continue your Boot Camp training progress from the terminal. We hope to see you in the community soon!