Australian (ASX) Stock Market Forum

FiftyEight Fluffs Around In Futures

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First plot done.....took way too long but doneish. Something doesnt seem right, I didnt expect such a peak at and around zero.

Will have a look this afternoon.

Range was simply "settle - open". I had to think about this for a while actually, couldnt decide if I should use "settle - open" or "high - low"

If anyone actually cares I can find a better way to share, but I expect not so ill just snip haha

upload_2017-8-17_8-24-28.png
 
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Yeah, just wasnt sure which would give me the info I was looking for. I have a few other simple ideas ill play around with this arvo
 
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Some stuff from yesterday.

The below had 798 days of data on the Dax. Nothing ground breaking and not sure I can draw any meaningful conclusions



upload_2017-8-18_7-45-41.png

upload_2017-8-18_7-47-58.png
 
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I always knew this would be the case, but even though I am only scratching the surface of Python, not even scratching the surface but looking at it from a far it has become even more apparent the size of the task ahead.

Also, I am still not sure ill even need the additional features offered by Python over Ami unless I use ML.

But on the flipside, LIGO (used to detect gravitational wave) use Python for a lot of their data analysis. Its is open source via a Jupyter Notebook so you can actually have a look at what they have done. Awesome!!!!!
 
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If you want to truly analyse the markets you're heading in the right direction.

AB is great for it's intended purpose, which was to create a graphing / backtesting program. For in depth analysis there are better tools.

ML is not the only use. The time series problem can be negated easier python by analysing performance over time for your theorems and choosing ones that behave consistantly over time.

Backtesting 1 million strategies at once. This might seem like overkill, but AB's optimize function lets you fine tune ( curve fit ) for variables. Python can take that next level and allow you to curve fit formulas as well as variables.

But yeah, it's a long road.
 
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Until it does, stock and fund data can be loaded directly from the quote vendor into a Python Pandas database (like an array) from Yahoo, Google, or Quandl. No local files are required -- although you can set them up if you so desire. All are available free. As usual, free is not always best. If the quality is not to your standards, Quandl has a premium offering available with a subscription.
Best, Howard
A few people have suggested Quandl, I have emailed them to confirm they do not data for asx equities.

I am missing something here?

How are other getting asx equities data? Premium data seems a messy way to go
 
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Not sure how I missed it while I was looking yesterday, IB may be the way to go
 

tech/a

No Ordinary Duck
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I think so

They certainly are in all facets of scientific research.
 
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tech/a

No Ordinary Duck
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tickdata.com
It's cheaper than you think
 

CanOz

Home runs feel good, but base hits pay bills!
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Tickdata has gone up I think tech, minimum order $500. Roughly $100 per year / instrument
 

tech/a

No Ordinary Duck
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Yeh
It's about $250 a year / ticker
For what you get it's not that expensive
Well I don't think it is.
 
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