Select Language

AI社区

公开数据集

波兰公司破产数据集

波兰公司破产数据集

8.4M
602 浏览
0 喜欢
2 次下载
0 条讨论
Business Classification

Data Set Information:The dataset is about bankruptcy prediction of Polish companies. The data was collected from Emergin......

数据结构 ? 8.4M

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Data Set Information:

    The dataset is about bankruptcy prediction of Polish companies. The data was collected from Emerging Markets Information Service (EMIS, [Web link]), which is a database containing information on emerging markets around the world. The bankrupt companies were analyzed in the period 2000-2012, while the still operating companies were evaluated from 2007 to 2013.
    Basing on the collected data five classification cases were distinguished, that depends on the forecasting period:
    - 1stYear a€“ the data contains financial rates from 1st year of the forecasting period and corresponding class label that indicates bankruptcy status after 5 years. The data contains 7027 instances (financial statements), 271 represents bankrupted companies, 6756 firms that did not bankrupt in the forecasting period.
    - 2ndYear a€“ the data contains financial rates from 2nd year of the forecasting period and corresponding class label that indicates bankruptcy status after 4 years. The data contains 10173 instances (financial statements), 400 represents bankrupted companies, 9773 firms that did not bankrupt in the forecasting period.
    - 3rdYear a€“ the data contains financial rates from 3rd year of the forecasting period and corresponding class label that indicates bankruptcy status after 3 years. The data contains 10503 instances (financial statements), 495 represents bankrupted companies, 10008 firms that did not bankrupt in the forecasting period.
    - 4thYear a€“ the data contains financial rates from 4th year of the forecasting period and corresponding class label that indicates bankruptcy status after 2 years. The data contains 9792 instances (financial statements), 515 represents bankrupted companies, 9277 firms that did not bankrupt in the forecasting period.
    - 5thYear a€“ the data contains financial rates from 5th year of the forecasting period and corresponding class label that indicates bankruptcy status after 1 year. The data contains 5910 instances (financial statements), 410 represents bankrupted companies, 5500 firms that did not bankrupt in the forecasting period.


    Attribute Information:

    X1 net profit / total assets
    X2 total liabilities / total assets
    X3 working capital / total assets
    X4 current assets / short-term liabilities
    X5 [(cash + short-term securities + receivables - short-term liabilities) / (operating expenses - depreciation)] * 365
    X6 retained earnings / total assets
    X7 EBIT / total assets
    X8 book value of equity / total liabilities
    X9 sales / total assets
    X10 equity / total assets
    X11 (gross profit + extraordinary items + financial expenses) / total assets
    X12 gross profit / short-term liabilities
    X13 (gross profit + depreciation) / sales
    X14 (gross profit + interest) / total assets
    X15 (total liabilities * 365) / (gross profit + depreciation)
    X16 (gross profit + depreciation) / total liabilities
    X17 total assets / total liabilities
    X18 gross profit / total assets
    X19 gross profit / sales
    X20 (inventory * 365) / sales
    X21 sales (n) / sales (n-1)
    X22 profit on operating activities / total assets
    X23 net profit / sales
    X24 gross profit (in 3 years) / total assets
    X25 (equity - share capital) / total assets
    X26 (net profit + depreciation) / total liabilities
    X27 profit on operating activities / financial expenses
    X28 working capital / fixed assets
    X29 logarithm of total assets
    X30 (total liabilities - cash) / sales
    X31 (gross profit + interest) / sales
    X32 (current liabilities * 365) / cost of products sold
    X33 operating expenses / short-term liabilities
    X34 operating expenses / total liabilities
    X35 profit on sales / total assets
    X36 total sales / total assets
    X37 (current assets - inventories) / long-term liabilities
    X38 constant capital / total assets
    X39 profit on sales / sales
    X40 (current assets - inventory - receivables) / short-term liabilities
    X41 total liabilities / ((profit on operating activities + depreciation) * (12/365))
    X42 profit on operating activities / sales
    X43 rotation receivables + inventory turnover in days
    X44 (receivables * 365) / sales
    X45 net profit / inventory
    X46 (current assets - inventory) / short-term liabilities
    X47 (inventory * 365) / cost of products sold
    X48 EBITDA (profit on operating activities - depreciation) / total assets
    X49 EBITDA (profit on operating activities - depreciation) / sales
    X50 current assets / total liabilities
    X51 short-term liabilities / total assets
    X52 (short-term liabilities * 365) / cost of products sold)
    X53 equity / fixed assets
    X54 constant capital / fixed assets
    X55 working capital
    X56 (sales - cost of products sold) / sales
    X57 (current assets - inventory - short-term liabilities) / (sales - gross profit - depreciation)
    X58 total costs /total sales
    X59 long-term liabilities / equity
    X60 sales / inventory
    X61 sales / receivables
    X62 (short-term liabilities *365) / sales
    X63 sales / short-term liabilities
    X64 sales / fixed assets


    Relevant Papers:

    Zieba, M., Tomczak, S. K., & Tomczak, J. M. (2016). Ensemble Boosted Trees with Synthetic Features Generation in Application to Bankruptcy Prediction. Expert Systems with Applications. [Web link]



    Citation Request:

    Zieba, M., Tomczak, S. K., & Tomczak, J. M. (2016). Ensemble Boosted Trees with Synthetic Features Generation in Application to Bankruptcy Prediction. Expert Systems with Applications. [Web link]

    BibTeX:
    @article{zikeba2016ensemble,
     title={Ensemble Boosted Trees with Synthetic Features Generation in Application to Bankruptcy Prediction},
     author={Zi{k{e}}ba, Maciej and Tomczak, Sebastian K and Tomczak, Jakub M},
     journal={Expert Systems with Applications},
     year={2016},
     publisher={Elsevier}
    }


    Creator: Sebastian Tomczak
    -- Department of Operations Research, Wroc??aw University of Science and Technology, wybrze??e Wyspia??skiego 27, 50-370, Wroc??aw, Poland

    Donor: Sebastian Tomczak (sebastian.tomczak '@' pwr.edu.pl), Maciej Zieba (maciej.zieba '@' pwr.edu.pl), Jakub M. Tomczak (jakub.tomczak '@' pwr.edu.pl), Tel. (+48) 71 320 44 53

    ×

    帕依提提提温馨提示

    该数据集正在整理中,为您准备了其他渠道,请您使用

    注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。
    暂无相关内容。
    暂无相关内容。
    • 分享你的想法
    去分享你的想法~~

    全部内容

      欢迎交流分享
      开始分享您的观点和意见,和大家一起交流分享.
    所需积分:15 去赚积分?
    • 602浏览
    • 2下载
    • 0点赞
    • 收藏
    • 分享