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Report NEP-CMP-2022-09-05
This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-CMP
The following items were announced in this report:
- Giovanni Cerulli, 2022, "Machine learning using Stata/Python," Italian Stata Users' Group Meetings 2022, Stata Users Group, number 02, Jul.
- Leonardo Kanashiro Felizardo & Elia Matsumoto & Emilio Del-Moral-Hernandez, 2022, "Solving the optimal stopping problem with reinforcement learning: an application in financial option exercise," Papers, arXiv.org, number 2208.00765, Jul.
- Baier, Scott & Regmi, Narendra, 2021, "Using Machine Learning to Capture Heterogeneity in Trade Agreements," Working Papers, George Mason University, Mercatus Center, number 11027, Mar.
- Qin, Fei & Wu, Steven Y., 2022, "Estimating Consumer Segments and Choices from Limited Information: The Application of Machine Learning Methods," 2022 Annual Meeting, July 31-August 2, Anaheim, California, Agricultural and Applied Economics Association, number 322473, Aug, DOI: 10.22004/ag.econ.322473.
- Gustavo Silva Araujo & Wagner Piazza Gaglianone, 2022, "Machine Learning Methods for Inflation Forecasting in Brazil: new contenders versus classical models," Working Papers Series, Central Bank of Brazil, Research Department, number 561, Jul.
- Askery Canabarro & Taysa M. Mendonc{c}a & Ranieri Nery & George Moreno & Anton S. Albino & Gleydson F. de Jesus & Rafael Chaves, 2022, "Quantum Finance: a tutorial on quantum computing applied to the financial market," Papers, arXiv.org, number 2208.04382, Aug, revised Aug 2022.
- Mostafa Shabani & Dat Thanh Tran & Juho Kanniainen & Alexandros Iosifidis, 2022, "Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification," Papers, arXiv.org, number 2207.11577, Jul.
- José Manuel Carbó & Sergio Gorjón, 2022, "Application of machine learning models and interpretability techniques to identify the determinants of the price of bitcoin," Working Papers, Banco de España, number 2215, Apr.
- Tianchen Zhao & Chuhao Sun & Asaf Cohen & James Stokes & Shravan Veerapaneni, 2022, "Quantum-inspired variational algorithms for partial differential equations: Application to financial derivative pricing," Papers, arXiv.org, number 2207.10838, Jul.
- Daniel Goller & Andrea Diem & Stefan C. Wolter, 2022, "Sitting Next to a Dropout - Academic Success of Students with More Educated Peers," CESifo Working Paper Series, CESifo, number 9812.
- Buhlmann, Florian & Hebsaker, Michael & Kreuz, Tobias & Schmidhäuser, Jakob & Siegloch, Sebastian & Stichnoth, Holger, 2022, "ZEW-EviSTA: A microsimulation model of the German tax and transfer system," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 22-026.
- Jherek Healy, 2022, "Accurate and consistent calculation of the mean and variance in Monte-Carlo simulations," Papers, arXiv.org, number 2206.10662, Jun, revised Sep 2022.
- Xi-Ning Zhuang & Zhao-Yun Chen & Yu-Chun Wu & Guo-Ping Guo, 2021, "Quantum Quantitative Trading: High-Frequency Statistical Arbitrage Algorithm," Papers, arXiv.org, number 2104.14214, Apr.
- Bora, Siddhartha S. & Katchova, Ani, 2022, "Multi-horizon Forecasts of Agricultural Commodity Prices using Deep Learning," 2022 Annual Meeting, July 31-August 2, Anaheim, California, Agricultural and Applied Economics Association, number 322557, Aug, DOI: 10.22004/ag.econ.322557.
- Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2022, "Long Story Short: Omitted Variable Bias in Causal Machine Learning," NBER Working Papers, National Bureau of Economic Research, Inc, number 30302, Jul.
- Item repec:tiu:tiutis:d656c4b4-c3ea-4700-8c93-0e7ac7e96fd4 is not listed on IDEAS anymore
- Shaswat Mohanty & Anirudh Vijay & Nandagopan Gopakumar, 2022, "StockBot: Using LSTMs to Predict Stock Prices," Papers, arXiv.org, number 2207.06605, Jul, revised Jul 2022.