Multivariate Statistical analysis for prediction
Budget: $30 – $250 USD
I have an historic sqlite database file, with 100 tables.
Each table has more than 10000 registers.
Registers include price and timestamp (Example 1 register each minute)
Each register have about 20 indicators that will help to predict if price will go UP or DOWN.
I need a model for prediction of price direction using data of these indicators
Will be a Python script to show stats receiving the file and a probability as minimum example:
python3 example.py file.sqlite3 UP 0.8
- Results for each table and general results (using 100tables of data)
0< indicator 1 <0.1
0.23 < indicator 2 < 0.42
0.9 < indicator 3 < 2.0
...
- # of positive cases in table and in general.
You will use a python statistics package or AI model...
If you understood say "Hello eduardb" in your bid.
Ideally explain in private chat your experience and way to solve that.
Each table has more than 10000 registers.
Registers include price and timestamp (Example 1 register each minute)
Each register have about 20 indicators that will help to predict if price will go UP or DOWN.
I need a model for prediction of price direction using data of these indicators
Will be a Python script to show stats receiving the file and a probability as minimum example:
python3 example.py file.sqlite3 UP 0.8
- Results for each table and general results (using 100tables of data)
0< indicator 1 <0.1
0.23 < indicator 2 < 0.42
0.9 < indicator 3 < 2.0
...
- # of positive cases in table and in general.
You will use a python statistics package or AI model...
If you understood say "Hello eduardb" in your bid.
Ideally explain in private chat your experience and way to solve that.