Paper with Finacial Event Prediction

• Sample Financial Events:
  • Bankrupt
  • Initial Public Offering (IPO)
  • Mergers and Acquisitions (M&A)

Bankrupt

Reference	Paper	Data Source	Model	Evaluation Metric(s)	Time Period	Contributions	Venue
Geng et al. (2015)	Prediction of financial distress: An empirical study of listed Chinese companies using data mining	China, CSMAR	NN, DT, SVM, MV	Accuracy, Recall, Precision	2001–2008	phenomenon of financial distress for 107 Chinese companies that received the label‘special treatment’ from 2001 to 2008 by the Shanghai Stock Exchange and the Shenzhen Stock Exchange	Accounting
Liang et al. (2016)	Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study	Taiwan Economic Journal (TEJ)	SVM, KNN, NB, CART, MLP	ROC, Accuracy	1999–2009	assess the prediction performance obtained by combining seven different categories of FRs and five different categories of CGIs	Accounting, market, corporate governance
Olson et al. (2012)	Comparative analysis of data mining methods for bankruptcy prediction	USA, Compustat	DT, logit, MLP, RBFN, SVM	MSE	2005–2009	Research bankruptcy data and predict bankruptcy through information	Accounting
Ioannidis et al. (2010)	Assessing bank soundness with classification techniques	Bankscope, World Bank	UTADIS, MLP, CART, KNN, Ordered logit, stacked models	Accuracy	2007–2008	Use stack model to build bank warning model	Accounting, country-level variables
Boyacioglu et al. (2009)	Predicting bank financial failures using neural networks, support vector machines and multivariate statistical methods: A comparative analysis in the sample of savings deposit insurance fund (SDIF) transferred banks in Turkey	Turkey, Banks Association of Turkey	NN, SVM, MDA, K-means cluster analysis, logit	Using PCA, initial Eigenvalues	1997–2004	Use financial ratio as a predictor variable to establish a regression prediction model to predict bank failure probability	Accounting
Cecchini et al. (2010)	Making words work: Using financial text as a predictor of financial events	USA, Compustat, CRSP	SVM	Using defined Concept score	1994–1999	Develop a methodology for automatically analyzing text to aid in discriminating firms that encounter catastrophic financial events	MD&A, Altman variables
Kim et al. (2010)	Ensemble with neural networks for bankruptcy prediction	Korea	MLP + bagging, MLP + boosting	Predictive Accuracy, Predictive error rate	2002–2005	An ensemble with neural network for improving the performance of traditional neural networks on bankruptcy prediction tasks	Accounting
Mai et al. (2018)	Deep learning models for bankruptcy prediction using textual disclosures	USA, CRSP	CNN	AUC	1994-2014	Deep learning models for corporate bankruptcy forecasting using textual disclosures	Accounting
Snow et al. (2020)	Investigating Accounting Patterns for Bankruptcy and Filing Outcome Prediction using Machine Learning Models	USA, UCLA BRD	XGBClassifier	ROC, AUC	1977-2016	A modern gradient boosting machine (GBM), XGBoost, to predict litigated bankruptcies and filing outcomes	Accounting
Snow et al. (2020)	Predicting Global Restaurant Facility Closures	USA, Yelp	LightGBM	ROC	2006-2017	Through text mining and sentiment analysis, make survival predictions for restaurants	Accounting
Mohammad et al. (2020)	The Automated Venture Capitalist: Data and Methods to Predict the Fate of Startup Ventures	2015 Massachusetts Institute of Technology $100K Launch competition (open sourced)	NN	AUC	/	Investigate how the composition of early-stage start-up teams, and the properties of their ventures, predict their nomination to a premier entrepreneurship competition, and their continued operation two years following	Accounting
Martin et al. (2013)	Bankruptcy prediction for small- and medium-sized companies using severely imbalanced datasets	/	SVM, IF	Accuerary	2010-2016	Unbalanced data sources	Accounting

IPO

Reference	Paper	Data Source	Model	Evaluation Metric(s)	Time Period	Contributions	Venue
Cristóbal et al. (2012)	Predicting IPO Underpricing with Genetic Algorithms	USA, AMEX, NASDAQ and NYSE IPOs	Genetic algorithms	RMSE, Precision	1999-2010	A rule system to predict first-day returns of initial public offerings based on the structure of the offerings	Accounting
Zhe et al. (2019)	NLP Driven Large Scale Financial Data Analysis	USA, Intrinio, The Reuters dataset	HAN	Accuracy	2006-2013	Explores the influence of various factors on the performance of utilizing NLP knowledge to predict stock trend of a company	Accounting
Jie et al. (2015)	Text Mining for Studying Management’s Confidence in IPO Prospectuses and IPO Valuations	USA, US SEC’s EDGA, CRSP	FOCAS-IE	Confusion Metrics, Accuracy	2003-2013	By analyzing MD&A, build an analysis framework FOCAS-IE, extract emotions, and use the information extracted by FOCAS-IE to build a predictive model	Accounting
David et al. (2015)	Fuzzy Techniques for IPO Underpricing Prediction	USA, National Association Of Securities Dealers	Rule-based	RMSE	1999-2010	Rule-based classification	Accounting

Mergers and Acquisitions

Reference	Paper	Data Source	Model	Evaluation Metric(s)	Time Period	Contributions	Venue
Adesoji et al. (1999)	Predicting Mergers and Acquisitions in the Food Industry	USA, SDC Platinum	Logit Models	Accuracy of 74.5%	1985–1995	Explain merger and acquisition (M&A) activities in US food manufacturing using firm level data for public firms	Food industry
Liu et al. (2007)	Financial Characteristics and Prediction on Targets of M&A Based on SOM-Hopfield Neural Network	China, Securities Journals, Web	Hopfield Network	STD. Error Mean	2004-2006	Apply self-organized mapping (SOM) and Hopfield neural network to cluster and predict the target of mergers and acquisitions	Accounting
Chin-Sheng et al. (2014)	Exploiting Technological Indicators for Effective Technology Merger and Acquisition (M&A) Predictions	USA, SDC Platinum	Ensemble	Accuracy, AUC, Recall, Precision, F1	1997–2008	Propose a technology M&A prediction technology that takes technical indicators as independent variables and considers the technical profile of bidders and candidate target companies	Accounting
B.Shao et al. (2018)	Categorization of Mergers and Acquisitions in Japan Using Corporate Databases: A Fundamental Research for Prediction	Tokyo, UZABASE	Clustering	t-SNE visualization, Accuracy	2003-2016	Use M&A data, financial data and company data for M&A analysis	Accounting
Ye et al. (2011)	Board connections and M&A transactions	USA, SDC Platinum	Logit Models	ACAR, TCAR, PCAR	1996–2008	We examine M&A transactions between firms with current board connections and find that acquirers obtain higher announcement returns in transactions with a first-degree connection where the acquirer and the target share a common director	Accounting
Ryan et al. (2019)	Deal or No Deal: Predicting Mergers and Acquisitions at Scale	USA, EDGAR	Clustering	ROC, AUC, LDA	1994-2018	We utilize natural language processing (NLP) techniques to vectorize each filing’s textual data. Next, we cluster firms by industry and identify keywords suggestive of upcoming M&A activity. We then train a classifier to predict acquirers and targets, which we use to forecast the most likely M&As of 2019. Lastly, we deploy an application which enables users to query our forecasts and visualize our data	Accounting
Yang et al. (2020)	Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification	U.S. Listed Companies	Transformers (BERT, RoBERTa), Adversarial Training, Counterfactual Explanations	MSE	2007-2019	Predict the results of a possible M&A deadls. Explain the prediction results by generating the plausible counterfactual explanations.	CoLING-20
Philip et al. (2018)	Predictive Power? Textual Analysis in Mergers & Acquisitions	/	Linear Regression	Accuracy	2002-2014	M&A prediction using sentiment analysis	Accounting