Skip to content

datasets
datasets
Commit e6cbe4b8 by Rahim Rasool
Options

Add ISE dataset

parent bdde022c
Showing with 51 additions and 0 deletions
Istanbul Stock Exchange/README.md 0 → 100644
Data Science Dojo <br/>
Copyright (c) 2016 - 2019
---
**Level:** Intermediate <br/>
**Recommended Use:** Regression/Classification Models<br/>
**Domain:** Business/Finance<br/>
## Istanbul Stock Exchange Data Set
### Relate returns of Istanbul Stock Exchange with other international indices
---
![](9.jpg)
---
This *intermediate* level data set has 536 rows and 9 columns.
The data sets includes returns of Istanbul Stock Exchange with seven other international index; SP, DAX, FTSE, NIKKEI, BOVESPA, MSCE_EU, MSCI_EM from Jun 5, 2009 to Feb 22, 2011 and is organized with regard to working days in Istanbul Stock Exchange.
It can be used to find a predictive relationship between the Istanbul Stock Exchange National 100 Index (ISE100) and seven other international stock market indices.
This data set is recommended for learning and practicing your skills in **exploratory data analysis**, **data visualization**, **regression** and **classification** modelling techniques.
Feel free to explore the data set with multiple **supervised** and **unsupervised** learning techniques. The Following data dictionary gives more details on this data set:
---
### Data Dictionary
| Column Position | Atrribute Name | Definition | Data Type | Example | % Null Ratios |
|------------------- |---------------- |---------------------------------------------- |-------------- |--------------------------------- |--------------- |
| 1 | Date | Date | Quantitative | 13-Jan-09, 23-Jan-09, 30-Jan-09 | 0 |
| 2 | ISE | Stock Exchange Returns | Quantitative | 0.025426, -0.022692, 0.046831 | 0 |
| 3 | ISE.1 | Istanbul Stock Exchange - National 100 Index | Quantitative | 0.031813, -0.044349, 0.061708 | 0 |
| 4 | SP | Standard & Poor's 500 Return Index | Quantitative | 0.007787, -0.054262, 0.005538 | 0 |
| 5 | DAX | Stock Market Return Index of Germany | Quantitative | 0.008455, -0.01155, 0.034787 | 0 |
| 6 | FTSE | Stock Market Return Index Of UK | Quantitative | 0.012866, -0.009351, 0.037891 | 0 |
| 7 | NIKKEI | Stock Market Return Index Of Japan | Quantitative | 0.004162, 0.003239, -0.008182 | 0 |
| 8 | BOVESPA | Stock Market Return Index Of Brazil | Quantitative | 0.01892, -0.013151, 0.009838 | 0 |
| 9 | EU | MSCI European Index | Quantitative | 0.011341, -0.012045, 0.0328 | 0 |
| 10 | EM | MSCI Emerging Markets Index | Quantitative | 0.008773, -0.004029, 0.01032 | 0 |
---
### Acknowledgement
This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Istanbul Stock Exchange Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/ISTANBUL+STOCK+EXCHANGE).
The UCI page mentions the following paper as the original source of the data set:
*Akbilgic, O., Bozdogan, H., Balaban, M.E., (2013) A novel Hybrid RBF Neural Networks model as a forecaster, Statistics and Computing. DOI 10.1007/s11222-013-9375-7*
\ No newline at end of file
  • Eric @ericmenk33 commented

    The dataset update discussed in the thread highlights how structured financial data is essential for analyzing real-world business performance and pricing models. When working with such datasets, using a reliable tax calculator helps accurately convert net and gross values, making VAT implications clearer in financial analysis. This practical link between data handling and VAT calculation improves decision-making for business, retail, and economic research scenarios.

Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment
Explore Help Data Science Dojo