Consider the corporate bankruptcy prediction problem, and the list of variables in Appendix A$.$ These variables are currently used to predict the probability of corporate failure for a firm, using annual financial and market data. Recommend additional variables, which are likely to be associated with the prediction of corporate bankruptcy and hence likely to improve the predictive power of the machine learning models. You should outline one key new variable that can be created from the existing variables $($such as financial ratios$),$ as well as one key new variable from external data sources that you can collect from different Big Data sources. Justify why you believe all these two new variables would be appropriate explanatory variables.

Appendix A: Covariates included in models

$\backslash$table$[[$#$,$Variable Name,Variable Type,Description$],[1,$act,Numeric,Current Assets $-$ Total$],[2,$am$,$Numeric,Amortixation of Intangibles$],[3,$ap$,$Numeric,Accounts Payable $-$ Trade$],[4,$at$,$Numeric,Total Assets$],[5,$bkvlps$,$Numeric,Book value per share$],[6,$capx,Numeric,Capital Expenditures$],[7,$ceq,Numeric,Common$/$Ordinary Equity$],[8,$ch$,$Numeric,Cash$],[9,$che,Numeric,Cash and short$-$term investments$],[10,$chech,Numeric,Cash and cash equivalents Increase$/$Decrease$],[11,$csho,Numeric,Common shares outstanding$],[12,$dlc$,$Numeric,Debt in current liabilities$],[13,$dltt$,$Numeric,Long Term Debt $-$ Total$],[14,$dt$,$Numeric,Total Debt including current$],[15,$dvc$,$Numeric,Dividends Common$/$Ordinary$],[16,$dvt$,$Numeric,Dividends $-$ Total$],[17,$ebit,Numeric,Earnings Before Interest and Taxes$],[18,$ebitda,Numeric,Earnings Before Interest and Taxes, Depreciation and amortization$],[19,$fincf,Numeric,Financing activities net cash flow$],[20,$gdwlam,Numeric,Goodwill amortization$],[21,$ivncf,Numeric,Investing activities net cash flow$],[22,$lct$,$Numeric,Current liabilities $-$ total$],[23,$lt$,$Numeric,Liabilities $-$ total$],[24,$mkvalt,Numeric,Market value $-$ total$],[25,ni,$Numeric,Net Income $($Loss$)],[26,$oancf,Numeric,Operating Activities Net Cash Flow$],[27,$optvol,Numeric,Volatility $-$ Assumption $(\%)],[28,$prcc$\_$f$,$Numeric,Price Close $-$ Annual $-$ Fiscal$],[29,$prch$\_$f$,$Numeric,Price High $-$ Annual $-$ Fiscal$],[30,$prcl$\_$f$,$Numeric,Price Low $-$ Annual $-$ Fiscal$],[31,$revt,Numeric,Revenue $-$ Total$],[32,$sale,Numeric,Sales$/$Turnover $($Net$)],[33,$spce,Numeric,S&P Core Earnings$],[34,$spcsrc$,$Categorical,S&P Quality Ranking $-$ Current$],[35,$teq,Numeric,Stockholders Equity $-$ Total$],[36,$tfva,Numeric,Total fair value assets $($TFVA$)],[37,$tfvl$,$Numeric,Total fair value liabilities $($TFVL$)],[38,txp,$Numeric,Income taxes payable$],[39,$wcap,Numeric,Working capital $($balance sheet$)],[40,$xint,Numeric,Interest and Related Expense $-$ Total$],[41,$xintd,Numeric,Interest Expense $-$ Long$-$term Debt$],[42,$xrd$,$Numeric,Research and Development Expense$],[43,$xsga,Numeric,Selling, General and Administrative Expense$]]$