We develop a framework to simultaneously compute the unobservable parameters underlying structural-parametric models for bankruptcy prediction. More specifically, we such as, asset value and volatility, through learning by embedding in structural neural network that maps network’s input space (e.g. companies’ observable financial market data) parameter space. Within ‘neuro-structural’ framework...

The U.S. personal bankruptcy system functions as a bankruptcy system for small businesses as well as consumers, because debts of noncorporate firms are personal liabilities of the firms’ owners. If the firm fails, the owner has an incentive to file for bankruptcy, since both business debts and the owner’s personal debts will be discharged. In bankruptcy, the owner must give up assets above a fi...

Research background: Managers of the companies intentionally manipulate business earnings to achieve required status company. Earnings management is a legal and widely preferred phenomenon finance that financial managers use maintain improve company´s competitiveness. The consequence these activities provide positive view for owners, encourage profitability creditor investors as well demonstrat...

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto.fi Author Qi Yu Name of the doctoral dissertation Machine Learning for Corporate Bankruptcy Prediction Publisher School of Science Unit Information and Computer Science Department Series Aalto University publication series DOCTORAL DISSERTATIONS 90/2013 Field of research Information and Computer Science Manuscript submitted 10 March 201...