Hi
I request that you provide a way of creating a traditional scatter plot (i.e. independent x- & y-axes). This has been requested before, but the answers suggest you misunderstand what's being asked for. The QuantConnect scatter plot is a time seires plot with markers instead of lines (correct me if I'm wrong); a traditional scatter plot plots data pairs on independent axes.
Maximum Adverse and Farourable Excursions (MAE/MFE) are usually plotted on a scatter plot.
System development produces better results if you understand what correlation exists between your set-up factors and subsequent move. Calculated correlation coefficients can go some way to illustrate that, but the best way to see it is with a scatter plot and regression line.
Other platforms also don't make scatter plots, but you can write data to a file for importing into a spreadsheet for analysis. I understand and accept that you can't allow file writing because you need to prevent breaches of your 'free data' agreements. That brings me back to "please provide scatter plots", or another creative solution.
Thanks.
Jared Broad
Interesting points thank you for the suggestion Tony. It sounds like something better suited for the research environment - where we support many different types of charts in any form you want?
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Tony Shacklock
Hi Jared
Thanks for coming back so quickly. You're right, it is suited for the research environment - I had fogotten about that. I looked at it when I first arrived at QuantConnect, but didn't progress with it because I've never used Python or Jupyter and thought I could do what I wanted with C# in the Algorithm lab.
I guess I'm facing another learning curve. Do you have any suggestions for newbies to Python and Jupyter?
Cheers
Tony
Jared Broad
None specifically but I'm sure you'll pick it up quickly. I'm also a newbie to Python but with a solid C background you can pick up anything. We've been working on bug fixes in a C# version of Jupyter which hopefully should be ready for production shortly =)
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.
Tony Shacklock
Thanks. I've worked through an online Python tutorial and it seems reasonable to learn quite quickly.
Also, there seems to be a lot of really useful packages for Python that aren't there or not as good for C# (matplotlib, numpy & pandas, and more).
I think I've talked myself into learning what it takes to do my research with Jupyter and Python. Thanks for the push ;-)
Tony Shacklock
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.
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