Report NEP-CMP-2019-10-07

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan Miles issued this report. It is usually issued weekly.

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Other reports in NEP-CMP

The following items were announced in this report:

• 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 1909.11532, arXiv.org.
• Sarah Perrin & Thierry Roncalli, 2019. "Machine Learning Optimization Algorithms & Portfolio Allocation," Papers 1909.10233, arXiv.org.
• Marcelo Cajias, 2019. "Can a machine understand real estate pricing? – Evaluating machine learning approaches with big data," ERES eres2019_232, European Real Estate Society (ERES).
• Peter Carr & Liuren Wu & Zhibai Zhang, 2019. "Using Machine Learning to Predict Realized Variance," Papers 1909.10035, arXiv.org.
• Norbert Pfeifer, 2019. "Text-Based Rental Rate Predictions of Airbnb Listings," ERES eres2019_329, European Real Estate Society (ERES).
• David Byrd, 2019. "Explaining Agent-Based Financial Market Simulation," Papers 1909.11650, arXiv.org.
• Daiki Matsunaga & Toyotaro Suzumura & Toshihiro Takahashi, 2019. "Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis," Papers 1909.10660, arXiv.org, revised Nov 2019.
• Jang, Jiwook & Dassios, Angelos & Zhao, Hongbiao, 2018. "Moments of renewal shot-noise processes and their applications," LSE Research Online Documents on Economics 87428, London School of Economics and Political Science, LSE Library.
• Qi Deng, 2019. "Artificial Intelligence BlockCloud (AIBC) Technical Whitepaper," Papers 1909.12063, arXiv.org.
• Kei Nakagawa & Masaya Abe & Junpei Komiyama, 2019. "A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy," Papers 1910.01491, arXiv.org.
• Naoki Awaya & Yasuhiro Omori, 2019. "Particle Rolling MCMC," CIRJE F-Series CIRJE-F-1126, CIRJE, Faculty of Economics, University of Tokyo.
• 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 1909.10578, arXiv.org.
• 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 eres2019_171, European Real Estate Society (ERES).
• Jakob J. Kolb & Finn Muller-Hansen & Jurgen Kurths & Jobst Heitzig, 2019. "Macroscopic approximation methods for the analysis of adaptive networked agent-based models: The example of a two-sector investment model," Papers 1909.13758, arXiv.org, revised Aug 2020.
• Samudra Dasgupta & Arnab Banerjee, 2019. "Quantum Annealing Algorithm for Expected Shortfall based Dynamic Asset Allocation," Papers 1909.12904, arXiv.org, revised Sep 2020.
• Riza Demirer & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Risk Aversion and the Predictability of Crude Oil Market Volatility: A Forecasting Experiment with Random Forests," Working Papers 201972, University of Pretoria, Department of Economics.