Data Mining

  1. Discussion of “Analyzing Behavioral Big Data: Methodological, practical, ethical and moral issues”,Roger W. Hoerl,2017,Quality Engineering
  2. Big data analytics and firm performance: Effects of dynamic capabilities,Samuel Fosso Wamba, Angappa Gunasekaran,Shahriar Akter, Steven Ji-fan Ren, Rameshwar Dubey, Stephen J. Childe,2017,Journal of Business Research
  3. A model for unpacking big data analytics in high-frequency trading,onathan J.J.M. Seddon, Wendy L. Currie,2017,Journal of Business Research
  4. 使用語意模型分析線上部落格文件,陳林志、陳大仁、葉國暉、吳忠澄,2015,中華民國資訊管理學報
  5. 基於關聯度指標之網路文件語意分析與文句摘要,周智勳,2013,Journal of Information Technology and Applications


Network Analysis

  1. Network Filtering for Big Data: Triangulated Maximally Filtered Graph,Guido Previde Massara,T. Di Matteo,Tomaso Aste,2016,Journal of Complex Networks Advance Access
  2. Analyzing Entrepreneurial Social Networks with Big Data,Feng Wang, Elizabeth A. Mack & Ross Maciewjewski,2017,Annals of the American Association of Geographers
  3. Network Science: Complexity in Nature and Technology,Ernesto Estrado, Maria Fox, Desmond J. Higham, Gian-Luca Oppo,2015,Springer
  4. A network approach to portfolio selection,Gustavo Peraltaa , Abalfazl Zareeib,2016,Journal of Empirical Finance
  5. Stock network stability in times of crisis,Raphael H. Heiberger,2014,Physica A
  6. A Network Analysis of the Greek Stock Market,Kydros Dimitriosa , Oumbailis Vasileiosa,2015,Procedia Economics and Finance
  7. Investor Networks in the Stock Market,Han Ozsoylev, Johan Walden, M. Deniz Yavuz, Recep Bildik,2014,Review of Financial Studies
  8. Prestigious Stock Exchanges: A Network Analysis of International Financial Centers,Nicola Cetorelli , Stavros Peristiani,2013,Journal of Banking & Finance
  9. A theory of pyramidal ownership and family business groups,Almeida, H., Wolfenzon, D,2006,Journal of FInance
  10. Network topology of the interbank market,Boss, M., Elsinger, H., Summer, M., Thurner, S,2004,Quant. Finance
  11. New York Stock Exchange performance: evidence from the forest of multidimensional minimum spanning trees,Siew Lee Gan and Maman Abdurachman Djauhari,2015,Journal of Statistical Mechanics Theory and Experiment


Machine learning

  1. Forecasting of Indian Stock Market Index S&P CNX Nifty 50 Using Artificial Intelligence,Rajashree Dash, Dr.Jay Desai,2011,SSRN
  2. A hybrid stock trading framework integrating technical analysis with machine learning techniques,Rajashree Dash, Pradipta Kishore Dash,2016,The Journal of Finance and Data Science 2
  3. Deep learning for stock prediction using numerical and textual information,Ryo Akita, Akira Yoshihara, Takashi Matsubara,2016,Computer and Information Science (ICIS)
  4. Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm,TJ Hsieh, HF Hsiao, WC Yeh,2011,Applied soft computing
  5. Investigation Into The Effectiveness Of Long Short Term Memory Networks For Stock Price Prediction,Hengjian Jia,2016,SSRN
  6. Deep learning for stock prediction using numerical and textual information,Ryo Akita, Akira Yoshihara, Takashi Matsubara,2016,Computer and Information Science (ICIS)
  7. LSTM Neural Networks for Language Modeling,Martin Sundermeyer, Ralf Schluter, and Hermann Ney,2012,Interspeech
  8. Hybrid speech recognition with deep bidirectional LSTM,Alex Graves, Navdeep Jaitly, Abdel-rahman Mohamed,2014,Automatic Speech Recognition and Understanding (ASRU)
  9. TTS synthesis with bidirectional LSTM based recurrent neural networks,Y Fan, Y Qian, FL Xie,2014,Interspeech
  10. Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm,TJ Hsieh, HF Hsiao, WC Yeh,2011,Applied soft computing
  11. Recurrent neural network and a hybrid model for prediction of stock returns,AM Rather, A Agarwal, VN Sastry,2015,Expert Systems with Applications
  12. Accuracy driven artificial neural networks in stock market prediction,S Simon, A Raoot,2012,International journal on soft computing
  13. Predicting stock market trends by recurrent deep neural networks,A Yoshihara, K Fujikawa, K Seki, K Uehara,2014,Pacific Rim International
  14. Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques,J Patel, S Shah, P Thakkar, K Kotecha,2015,Expert Systems with Applications
  15. A hybrid stock trading framework integrating technical analysis with machine learning techniques,Rajashree Dash, Pradipta Kishore Dash,2016,The Journal of Finance and Data Science 2


Asset Pricing

  1. You have free access to this contentAsset Pricing without Garbage, TIM A. KROENCKE, 2017,The Journal of Finance
  2. Local Risk, Local Factors, and Asset Prices, SELALE TUZEL,MIAO BEN ZHANG, 2017, The Journal of Finance
  3. Asset Pricing with Countercyclical Household Consumption Risk, GEORGE M. CONSTANTINIDES,ANISHA GHOSH, 2017, The Journal of Finance
  4. Asset Pricing in the Dark: The Cross-Section of OTC Stocks, Andrew Ang, Assaf A. Shtauber, Paul C. Tetlock, 2013, Review of Financial Studies
  5. More Than Words: Quantifying Language to Measure Firms' Fundamentals, PAUL C. TETLOCK, MAYTAL SAAR-TSECHANSKY, SOFUS MACSKASSY, 2008, The Journal of Finance 
  6. Long-Horizon Returns, Eugene F. Fama, Kenneth R. French, 2017, SSRN


Corporate Finance

  1. Corporate Governance and Blockchains, David Yermack, 2017, Review of Finance
  2. CEO facial width predicts firm financial policies, J Mills, 2014, SSRN - Financial Economics
  3. Big Data: New Opportunities for M&A, Kurt Fanning, Emily Drogt, 2013, Journal of Corporate Accounting & Finance
  4. Big Data: Implications for Financial Managers, Kurt Fanning, Rita Grant, 2013, Journal of Corporate Accounting & Finance
  5. CEO Facial Structure and Corporate Risk  Taking, S Keck, W Tang, 2013, SSRN - Business Administration and Business Economics; Marketing; Accounting
  6. A Face Only an Investor Could Love CEOs’Facial Structure Predicts Their Firms’ Financial Performance, Elaine M. Wong,Margaret E. Ormiston, Michael P. Haselhuhn, 2011, Psychological Science


High Frequency Trading

  1. The Flash Crash: High Frequency Trading in an Electronic Market,ANDREI KIRILENKO,ALBERT S. KYLE,MEHRDAD SAMADI,TUGKAN TUZUN, 2017, The Journal of Finance
  2. Do Prices Reveal the Presence of Informed Trading?, PIERRE COLLIN-DUFRESNE,VYACHESLAV FOS, 2015, The Journal of Finance
  3. News Trading and Speed, THIERRY FOUCAULT,JOHAN HOMBERT,IOANID ROŞU, 2016, The Journal of Finance
  4. The Beauty Contest and Short-Term Trading, GIOVANNI CESPA,XAVIER VIVES, 2015, The Journal of Finance
  5. High-Frequency Trading and Extreme Price Movements, Jonathan Brogaard, Al Carrion, Thibaut Moyaert, Ryan Riordan, Andriy Shkilko, Konstantin Sokolov, 2015, Working Paper
  6. High-frequency quoting, trading, and the efficiency of prices, Jennifer Conrada, Sunil Wahalb, Jin Xiang, 2015, Journal of Financial Economics
  7. News releases and stock market volatility: Intraday evidence from Borsa Istanbul, MN Solakoglu, 2015, Handbook of HFT
  8. High-Frequency News Flow and States of Asset Volatility, Kin-Yip Ho, Yanlin Shi, and Zhaoyong Zhang, 2015, Handbook of HFT
  9. High-Frequency Trading and Price Discovery, Jonathan Brogaard, Terrence Hendershott, Ryan Riordan, 2014, Review of Financial Studies
  10. OPTIMIZATION AND STATISTICAL METHODS FOR HIGH FREQUENCY FINANCE , Marc Hoffmann, Mauricio Labadie, Charles-Albert Lehalle, Gilles Page`s , Huyeˆn Pham, Mathieu Rosenbaum, 2014, Working Paper
  11. Hawkes model for price and trades high-frequency dynamics, Emmanuel Bacrya, Jean-François Muzy, 2014, Quantitative Finance
  12. Simulating the Synchronizing Behavior of High-Frequency Trading in Multiple Markets, Benjamin Myers, Austin Gerig, 2014, Financial Econometrics and Empirical Market Microstructure
  13. Clustering of Trade Prices by High-Frequency and Non–High-Frequency Trading Firms, Ryan L. Davis, Bonnie F. Van Ness, Robert A. Van Ness, 2014, The Financial Review
  14. Impact of the introduction of call auction on price discovery: Evidence from the Indian stock market using high-frequency data, Sobhesh Kumar Agarwalla, Joshy Jacob, Ajay Pandey, 2014, International Review of Financial Analysis
  15. "Machine News and Volatility: The Dow Jones Industrial Average
  16. and the TRNA Real-Time High-Frequency Sentiment Series, David E Allena, Michael McAleerb, Abhay K Singhc, 2014, Handbook of HFT"
  17. Can High-Frequency Trading Drive the Stock Market Off a Cliff?, Wei Pan, Alex Sandy Pentland, Ren Cheng, Lisa Emsbo-Mattingly, 2013, MIT Sloan Management Review
  18. When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions, Axel Groß-Klußmann, Nikolaus Hautsch, 2011, Journal of Empirical Finance
  19. Quantifying high-frequency market reactions to real-time news sentiment announcements, Groß-Klußmann, Axel Hautsch, Nikolaus, 2009, working paper


Investor Behavior

  1. Is News Sentiment More than Just Noise?, Simon Jonas Alfano, Stefan Feuerriegel, Dirk Neumann, 2015, SSRN- Financial Econimics
  2. Investor Sentiment in News and the Calendar Anomaly -- New Evidence from a Large Textual Data, Katsuhiko Okada, Takahiro Yamasaki , 2014, SSRN- Financial Econimics
  3. Quantifying the Semantics of Search Behavior Before Stock Market Moves, Chester Curme, Tobias Preis, H. Eugene Stanley, Helen Susannah Moat, 2014, National Acad Sciences
  4. Analysis on Stock Market Volatility with Collective Human Behaviors in Online Message Board, Yun Jung Lee, Hwan Gue Cho, Gyun Woo, 2014, Working Paper
  5. Jumps in Option Prices and Their Determinants: Real-Time Evidence from the E-Mini S&P 500 Option Market, George Kapetanios, Michael Neumann, George S. Skiadopoulos, 2014, SSRN - Financial Economics
  6. Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media, Hailiang Chen, Prabuddha De, Yu (Jeffrey) Hu, Byoung-Hyoun Hwang, 2014, Review of Financial Studies
  7. Anticipating Stock Market Movements with Google and Wikipedia, Helen Susannah Moat, Chester Curme, H. Eugene Stanley, Tobias Preis, 2014, Nonlinear Phenomena in Complex Systems: From Nano to Macro Scale
  8. Using big data to predict collective behavior in the real world, Helen Susannah Moat, Tobias Preis, ChristopherY. Olivola, Chengwei Liu, Nick Chater, 2014, Behavioral and Brain Sciences 
  9. Impact of News Articles on Stock Prices An Analysis using Machine Learning, Khadija Vakeel, Shubhamoy Dey, 2014, Proceedings of the 6th IBM Collaborative Academia Research Exchange Conference (I-CARE) on I-CARE 2014
  10. Quantifying Trading Behavior in Financial Markets Using Google Trends, Tobias Preis , Helen Susannah Moat , H. Eugene Stanley , 2013, Scientific Reports
  11. Quantifying Wikipedia Usage Patterns Before Stock Market Moves, Helen Susannah Moat, Chester Curme, Adam Avakian, Dror Y. Kenett, H. Eugene Stanley, Tobias Preis, 2013, Scientific Reports
  12. Quantifying the Relationship between Financial News and the Stock Market, Merve Alanyali, Helen Susannah Moat, Tobias Preis, 2013, Scientific Reports
  13. Efficient global portfolios: Big data and investment universes, JB Guerard, ST Rachev, BP Shao, 2013, IBM Journal of Research and Development
  14. Global Stock Selection Modeling and Efficient Portfolio Construction and Management, John B. Guerard, Jr., Harry Markowitz, Ganlin Xu, 2013, Working Paper
  15. News Sentiment And States of Stock Return Volatility: Evidence from Long Memory and Discrete Choice Models, Y. Shi, K.Y-. Ho, 2013, 20th International Congress on Modelling and Simulation
  16. How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches, Kin-Yip Hoa, Yanlin Shia, Zhaoyong Zhang, 2013, The North American Journal of Economics and Finance
  17. Web Search Queries Can Predict Stock Market Volumes, Ilaria Bordino, Stefano Battiston, Guido Caldarelli, Matthieu Cristelli , Antti Ukkonen, Ingmar Weber, 2012, PLOS One
  18. Mining the Web for the Voice of the Herd to Track Stock Market Bubbles, Aaron Gerow , Mark T.Keane, 2012, Proceedings of the Twenty-Second international joint conference on Artificial Intelligence
  19. Everyone's an Influencer Quantifying Influence on Twitter, Eytan Bakshy, Jake M.Hofman, Winter A.Mason , Duncan J.Watts, 2011, Proceedings of the fourth ACM international conference on Web search and data mining
  20. The determinants of international investment and attention allocation: Using internet search query data, Jordi Mondriay, Thomas Wu, Yi Zhang, 2010, Journal of International Economics
  21. Complex dynamics of our economic life on different scales: insights from search engine query data, Tobias Preis, Daniel Reith, H. Eugene Stanley, 2010, The Royal Society
  22. Does Public Financial News Resolve Asymmetric Information?, Paul C. Tetlock, 2010, Does Public Financial News Resolve Asymmetric Information?
  23. Giving Content to Investor Sentiment: The Role of Media in the Stock Market, PAUL C. TETLOCK, 2007, The Journal of Finance
  24. Using big data in finance: Example of sentiment-extraction from news articles, Nitish Sinha, 2014, Working Paper


Market Microstructure

  1. Assessing Measures of Order Flow Toxicity and Early Warning Signals for Market Turbulence, Torben G. Andersen, Oleg Bondarenko, 2015, Review of Finance
  2. A big data approach to analyzing market volatility, Kesheng Wua, E. Wes Bethela, Ming Gub, David Leinwebera, and Oliver Rübela, 2013, Algorithmic Finance
  3. Testing VPIN on Big Data – Response to 'Reflecting on the VPIN Dispute', Kesheng Wu, E. Wes Bethel, Ming Gu, David Leinweber, and Oliver Ruebel, 2013, SSRN
  4. Comments on'Testing VPIN on Big Data-Response to Reflecting on the VPIN Dispute', Torben G. Andersen, Oleg Bondarenko, 2013, SSRN - Financial Economics
  5. A Big Data Study of Microstructural Volatility in Futures Markets, Kesheng Wu, E. Wes Bethel, Ming Gu, David Leinweber, Oliver Ru ̈bel, 2013, SSRN - Financial Economics
  6. Flow Toxicity and Liquidity in a High Frequency World, David Easley, Marcos Lopez de Prado, Maureen O'Hara, 2012, Review of Financial Studies


Market Prediction

  1. A hybrid model for high-frequency stock market forecasting, Ricardo de A. Araújoa, Adriano L.I. Oliveirab, Silvio Meira, 2015, Expert Systems with Applications
  2. Mining microblogging data to model and forecast stock market behavior, Oliveira, Nuno Miguel da Rocha, 2015,
  3. An Automatic Leading Indicator, Variable Reduction and Variable Selection Methods Using Small and Large Datasets: Forecasting the Industrial Production Growth for Euro Area Economies, Gonzalo Camba-Mendez, George Kapetanios, Fotis Papailias, Martin R. Weale, 2014, Quantf research Working Paper
  4. Coupling news sentiment with web browsing data predicts intra-day stock prices, Gabriele Ranco, Ilaria Bordino, Giacomo Bormetti, Guido Caldarelli, Fabrizio Lillo, Michele Treccani, 2014, Working Paper
  5. The face says it all: CEOs, gender, and predicting corporate performance, Julianna Pillemer, Elizabeth R. Grahama, Deborah M. Burke, 2014, The Leadership Quarterly
  6. Should Macroeconomic Forecasters Use Daily Financial Data and How?, Elena Andreoua, Eric Ghyselsbc, Andros Kourtellos, 2013, Journal of Business & Economic Statistics
  7. A novel text mining approach to financial time series forecasting, B Wang, H Huang, X Wang, 2012, Neurocomputing
  8. Data Mining in Social Media for Stock Market Prediction, Feifei Xu, 2012,
  9. A Preprocessing Method of Internet Search Data for Prediction Improvement:Application to Chinese Stock Market, Ying Liu, Benfu Lv, Geng Peng, Qingyu Yuan, 2012, Proceedings of the Data Mining and Intelligent Knowledge Management Workshop
  10. Internet Search Behavior as an Economic Forecasting Tool: The Case of Inflation Expectations, Giselle Guzman, 2011, The Journal of Economic and Social Measurement
  11. News—Good or Bad—and Its Impact on Volatility Predictions over Multiple Horizons, Xilong Chen, Eric Ghysels, 2011, Review of Financial Studies
  12. Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data, Huina Mao, Scott Counts, Johan Bollen, 2011, Working Paper
  13. Can Facebook Predict Stock Market Activity, Yigitcan Karabulut, 2011, Working Paper
  14. Twitter mood predicts the stock market, Johan Bollen, Huina Mao, Xiao-Jun Zeng, 2010, Journal of Computational Science
  15. 運用文字探勘於日內股價漲跌趨勢預測, 鍾任明, 李維平, 吳澤民, 2007, 中華管理評論
  16. Application of Machine Learning to Short-Term Equity Return Prediction, Robert Yan, John Nuttall, Charles X. Ling, 2006, SSRN
  17. The use of data mining and neural networks for forecasting stock market returns, David Enke , Suraphan Thawornwong, 2005, Expert Systems wuth Applications
  18. Forecasting Intraday stock price trends with text mining techniques, MA Mittermayer, 2004, System Sciences
  19. Stock prediction Integrating text mining approach using real-time news, GPC Fung, JX Yu, W Lam, 2003, Computational Intelligence for Financial Engineering


Risk Management

  1. Managerial Ability, Investment Efficiency and Stock Price Crash Risk, Ahsan Habib and Mostafa Monzur Hasan , 2016,SSRN
  2. Product Market Threats and Stock Crash Risk , Si Li and Xintong Zhan, 2016,SSRN
  3. Stock Liquidity and Default Risk , Jonathan Brogaard, Dan Li and Ying Xia, 2015, Journal of Financial Economics
  4. Risk and Risk Management in the Credit Card Industry, Florentin Butaru, Qingqing Chen, Brian Clark, Sanmay Das, Andrew W. Lo, Akhtar R. Siddique, 2015, SSRN - Financial Economics
  5. Risk Classification's Big Data (R)evolution, Rick Swedloff, 2014, Connecticut Insurance Law Journal
  6. Financial big data analysis for the estimation of systemic risks, Paola Cerchiello, Paolo Giudici, 2014, Working Paper
  7. Can Google Trends search queries contribute to risk diversification?, Ladislav Kristoufek, 2013, Scientific Reports
  8. Constructing credit auditing and control & management model with data mining technique, SC Chen, MY Huang, 2011, Expert Systems with Applications
  9. Detection of financial statment fraud and feature selection using data mining techniques, P,Ravisankar , V.Ravi , G.Raghava Rao , I,Bose, 2011, Decision Support Systems
  10. Credit scoring with a data mining approach based on support vector machines, CL Huang, MC Chen, CJ Wang, 2007, Expert systems with applications