#HKEx Stock Analysis
A system to provide aid in analysing companies and industries listed in Hong Kong Stock Market
If you are interested to execute this code on a computer remotely, please take a look at my other tool listener.py
##Targets
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To obtain a complete list of listed company on HKEx, and archive the list from the past
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To scrap company information from the HKEx official website
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To scrap financial information from Aastocks
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To calculate ratios for the companies, and show by industries based on classification from HKEx
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To filter companies with criteria
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To help understand the recent development of the company with company announcements (In Progress)
##Setup for the system
On the computer executing the code:
|-> hkex.py
|>> Settings
|-> Criteria.txt
|-> keyword.csv
|-> settings.txt
|>> hkextools
|-> __init__.py
|-> fAnalysis.py
|-> highlight.py
|-> nettools.py
|-> statusSum.py
|-> utiltools.py
Alternatively, you can move the Criteria.txt file to the output folder, if you decide to specify the output folder in the settings.txt
##How to use
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Set the desired output path in settings.txt
"Output Path": "D:\Dropbox\Station\HKEx"
Note that you will need to ensure the specified location path exists By default, if no path was specified, an folder Output will be created in the same level as hkex.py There are also settings for currency and the location of the criteria file.
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Modify 'keywords.csv' for company announcement analysis, in the following format
[Announcement keyword] [Required? (Y/N)] [Category] ASSET RESTRUCTURING Y Restructure
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Modify the 'Criteria.txt' for company financial filter
"Gross Profit Margin" : {"Mode" : "M", "Value" : "15" }
For example, the above will mean a filter for companies with more than 15% in Gross Profit Margin
Notes:
M = More
L = Less
N = Not required
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Run hkex.py
python hkex.py
##Expect Outcomes
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IndustryIndex.csv - Industry Classification according to Information from HKEx
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consolRatios.xlsx - Showing all financial information based on Industry Classification
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highlight.xlsx - Showing financial information for filtered companies
Please refer to the Sample Output folder for outcome samples
This iss designed under the Python 3.5 environment, and have not tested under other versions of Python.