Report NEP-BIG-2019-10-07

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-BIG

The following items were announced in this report:

• Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asuman Ozdaglar, 2019, "Too Much Data: Prices and Inefficiencies in Data Markets," NBER Working Papers, National Bureau of Economic Research, Inc, number 26296, Sep.
• Norbert Pfeifer, 2019, "Text-Based Rental Rate Predictions of Airbnb Listings," ERES, European Real Estate Society (ERES), number eres2019_329, Jan.
• Marcelo Cajias, 2019, "Can a machine understand real estate pricing? – Evaluating machine learning approaches with big data," ERES, European Real Estate Society (ERES), number eres2019_232, Jan.
• Kei Nakagawa & Masaya Abe & Junpei Komiyama, 2019, "A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy," Papers, arXiv.org, number 1910.01491, Oct.
• Peter Carr & Liuren Wu & Zhibai Zhang, 2019, "Using Machine Learning to Predict Realized Variance," Papers, arXiv.org, number 1909.10035, Sep.
• Qi Deng, 2019, "Artificial Intelligence BlockCloud (AIBC) Technical Whitepaper," Papers, arXiv.org, number 1909.12063, Sep.
• Sarah Perrin & Thierry Roncalli, 2019, "Machine Learning Optimization Algorithms & Portfolio Allocation," Papers, arXiv.org, number 1909.10233, Sep.
• Daiki Matsunaga & Toyotaro Suzumura & Toshihiro Takahashi, 2019, "Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis," Papers, arXiv.org, number 1909.10660, Sep, revised Nov 2019.
• Toyotaro Suzumura & Yi Zhou & Natahalie Baracaldo & Guangnan Ye & Keith Houck & Ryo Kawahara & Ali Anwar & Lucia Larise Stavarache & Yuji Watanabe & Pablo Loyola & Daniel Klyashtorny & Heiko Ludwig & , 2019, "Towards Federated Graph Learning for Collaborative Financial Crimes Detection," Papers, arXiv.org, number 1909.12946, Sep, revised Oct 2019.
• Marcelo Cajias, 2019, "New Technology and Data in Real Estate," ERES, European Real Estate Society (ERES), number eres2019_155, Jan.
• Martin Huber, 2019, "An introduction to flexible methods for policy evaluation," Papers, arXiv.org, number 1910.00641, Oct.
• Yang Qu & Ming-Xi Wang, 2019, "The option pricing model based on time values: an application of the universal approximation theory on unbounded domains," Papers, arXiv.org, number 1910.01490, Oct, revised Apr 2021.
• Martijn Droes & Martin Hoesli & Steven C. Bourassa, 2019, "Heterogeneous Households and Market Segmentation in a Hedonic Framework," ERES, European Real Estate Society (ERES), number eres2019_218, Jan.
• Marcelo Cajias & Jonas Willwersch & Felix Lorenz, 2019, "I know where you will invest in the next year – Forecasting real estate investments with machine learning methods," ERES, European Real Estate Society (ERES), number eres2019_171, Jan.
• Giovanni Mariani & Yada Zhu & Jianbo Li & Florian Scheidegger & Roxana Istrate & Costas Bekas & A. Cristiano I. Malossi, 2019, "PAGAN: Portfolio Analysis with Generative Adversarial Networks," Papers, arXiv.org, number 1909.10578, Sep.
• Claudio Vitari & Elisabetta Raguseo, 2019, "Big data analytics business value and firm performance: Linking with environmental context," Post-Print, HAL, number hal-02293765, Sep, DOI: 10.1080/00207543.2019.1660822.
• Arthur Charpentier, 2019, "Big Data, GAFA et Assurance," Working Papers, HAL, number hal-02294899, Sep.
• Andreas Kindt, 2019, "A Framework for the optimal Development and Application of Automated Valuation Models (AVMs)," ERES, European Real Estate Society (ERES), number eres2019_240, Jan.
• Draca, Mirko & Schwarz, Carlo, 2019, "How Polarized are Citizens? Measuring Ideology from the Ground-Up," CAGE Online Working Paper Series, Competitive Advantage in the Global Economy (CAGE), number 432.
• Helene Dernis & Petros Gkotsis & Nicola Grassano & Shohei Nakazato & Mariagrazia Squicciarini & Brigitte van Beuzekom & Antonio Vezzani, 2019, "World Corporate Top R&D investors: Shaping the Future of Technologies and of AI," JRC Research Reports, Joint Research Centre, number JRC117068, Sep.
• Bénédicte Apouey, 2019, "Intérêt des adhérents d'une mutuelle pour des services utilisant leurs données personnelles dans le cadre de la médecine personnalisée," PSE Working Papers, HAL, number halshs-02295392, Sep.
• Jau-er Chen & Chien-Hsun Huang & Jia-Jyun Tien, 2019, "Debiased/Double Machine Learning for Instrumental Variable Quantile Regressions," Papers, arXiv.org, number 1909.12592, Sep, revised Feb 2021.
• Michael Poli & Jinkyoo Park & Ilija Ilievski, 2019, "WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series," Papers, arXiv.org, number 1909.10801, Sep.
• Yangang Chen & Justin W. L. Wan, 2019, "Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimensions," Papers, arXiv.org, number 1909.11532, Sep.
• Item repec:ulb:ulbeco:2013/283916 is not listed on IDEAS anymore

• Item repec:imf:imfdep:19/16 is not listed on IDEAS anymore

Report NEP-BIG-2019-10-07

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-BIG

The following items were announced in this report: