In Progress

Python Programming -- 2

First Script (On main Server in folder "Marvis")

Marvis : Directional movement of stock prices

[url removed, login to view]

Original scripture is from [url removed, login to view]

Source code is 'python' which is really simple to learn/use, we will need python/php.

Task : Feed through our stocks (as a loop daily) and predict and store in database.

Official Data Description

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[url removed, login to view] - time series for 94 stocks (94 rows). First number in each row is the stock ID. Then data for 500 days. Data for each day contain - day opening price, day maximum price, day minimum price, day closing price, trading volume for the day. Price data normalised to the first day opening price.

> Our main stock listing ticker database, and their dynamic historic records ticker wise should provide this

[url removed, login to view] - data to create prediction. Data provided for 25 time segments. Each segment contains data for the same 94 stocks. Each segment has opening, max, min, closing, volume data for 9 days and opening for day #10. Each line of the file starts with segment number following by stock ID and then price and volume data organized by day the same way as training set. Price data normalised to the first day opening price.

> again historic records should provide this ticker wise

Each line in [url removed, login to view] and [url removed, login to view] contains consecutive trading days. Days when market was closed were excluded. Thus day N may be Friday and day N+1 may be Monday or even Tuesday if Monday was a holiday.

> again our historic data ticker wise should provide this

Value to predict - probability of stock moving up from opening of day 10 to closing of day 10. Prediction should be in 0-1 range, where 1 - "stock surely will go up", 0- "stock surely will go down".

> Store ticker wise (table creation wise in database

Test set is randomly sampled without overlapping from year following training data time period.

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Will include writing code to feed in our live data apposed to the CSV system in place and make dynamic and set on a cron to run every 12 hours, note we have [url removed, login to view] tickers.

You will need to know the tables for the processing.

Our end for listing stock tickers to feed through and process and live updated EOD data.

RDS : invaciodb

Table : stock_exchange_companies

Column(s) : company_id | company_symbol

** Note we allocate a ID which is then used for the dynamic side creation, so company symbol + id

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Then match the company_symbol with the symbols in the following

RDS: invacioquandl

Table : wiki_tickers

Column(s) : id | ticker | isHavingTickerTable

** Note stock_exchange_companies must compare company_symbol value against ticker value if value exists then confirm isHavingTickerTable has value of '1' in enum

Table : wiki_ticker_%Symbol

Colum(s) : date | open | high | low | close | volume

If company symbol in stock_exchange_companies matches with a symbol in wiki_tickers, and there is daily data in table wiki_ticker_%symbol ticker wise, then these will make [url removed, login to view] and [url removed, login to view] redundant, instead of using a static CSV(s) you will create a script that pulls in dynamically and processes through their scripts.

End results (Predictions) drop in to the folder Prediction > Ridge | Stacker < as CSV's again this needs making dynamic to store ticker wise in the following

RDS : invaciodb5

Tables to dynamically create with respective colums Stock Ticker ID wise and create new rows for daily prediction.

Example(s)

_____STACKER____

Table : marvis_id%_stacker (id% = stock ticker id from wiki_ticker 'id')

Colums: : id | date (inject) | prediction

____RIDGE_____

Table : marvis_id%_ridge (id% = stock ticker id from wiki_ticker 'id')

Colums: : id | date (inject) | prediction

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Skills: PHP, Programming, Python, Software Architecture

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