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The M6 forecasting competition, the sixth in the Makridakis' competition sequence, is focused on financial forecasting.
The Intelligent Investor: The Definitive Book on Value Investing
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Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
Engle, R. F. (1982) · 1982
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The accuracy of extrapolation (time series) methods: Results of a forecasting competition
Makridakis, S., Andersen, A., Carbone, R., Fildes, R., Hibon, M., Lewandowski, R., Newton, J., Parzen, E., & Winkler, R. (1982) · 1982
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Generalized autoregressive conditional heteroskedasticity
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Global portfolio optimization
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Modelling agent forecast distributions
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Modelling probabilistic agent opinion
West, M., & Crosse, J. (1992) · 1992
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The m2-competition: A real-time judgmentally based forecasting study
Makridakis, S., Chatfield, C., Hibon, M., Lawrence, M., Mills, T., Ord, K., & Simmons, L. F. (1993) · 1993
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Multivariate simultaneous generalized arch
Engle, R. F., & Kroner, K. F. (1995) · 1995
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Garch for groups
Engle, R., & Mezrich, J. (1996) · 1996
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Active Portfolio Management (PB)
Grinold, R. C., & Kahn, R. N. (1999) · 1999
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The M3-Competition: results, conclusions and implications
Makridakis, S., & Hibon, M. (2000) · 2000
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Out-of-sample tests of forecasting accuracy: an analysis and review
Tashman, L. J. (2000) · 2000
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Drift-independent volatility estimation based on high, low, open, and close prices
Yang, D., & Zhang, Q. (2000) · 2000
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The distribution of realized stock return volatility
Andersen, T. G., Bollerslev, T., Diebold, F. X., & Ebens, H. (2001) · 2001
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Principal component models for generating large garch covariance matrices
Alexander, C. (2002) · 2002
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Dynamic conditional correlation - a simple class of multivariate garch models
Engle, R. (2002) · 2002
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A forecast comparison of volatility models: does anything beat a GARCH(1,1)?
Hansen, P. R., & Lunde, A. (2005) · 2005
Buffett’s alpha
Frazzini, A., Kabiller, D., & Pedersen, L. H. (2018) · 2018
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Big data analytics in economics: what have we learned so far, and where should we go from here?
Swanson, N. R., & Xiong, W. (2018) · 2018
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The three types of factor models: A comparison of their explanatory power
Connor, G. (2019) · 2019
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The M4 Competition: 100,000 time series and 61 forecasting methods
Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2020) · 2020
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FFORMA: Feature-based forecast model averaging
Montero-Manso, P., Athanasopoulos, G., Hyndman, R. J., & Talagala, T. S. (2020) · 2020
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A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting
Smyl, S. (2020) · 2020
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The Wisdom of Crowds
Surowiecki, J. (2005) · 2005
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Midas regressions: further results and new directions
Ghysels, E., Sinko, A., & Valkanov, R. (2007) · 2007
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Bayes Linear Statistics: Theory and Methods
Goldstein, M., & Wooff, D. (2007) · 2007
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Financial Modeling Under Non-Gaussian Distributions
Jondeau, E., Poon, S.-H., & Rockinger, M. (2007) · 2007
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Glossary to ARCH (GARCH), in T. Bollerslev, T., Russel, J., Watson, M., Volatility and Time Series Econometrics: Essays in Honor of Robert F. Engle. Oxford University Press, London
Bollerslev, T. (2009) · 2009
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Wisdom of crowds before the 2007–2009 global financial crisis
Chau, M., Lin, C.-Y., & Lin, T.-C. (2020) · 2009
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Forecasting volatility using double shrinkage methods
Cheng, M., Swanson, N. R., & Yang, X. (2021) · 2021
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The wisdom of the crowd and prediction markets
Dai, M., Jia, Y., & Kou, S. (2021) · 2021
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The future of forecasting competitions: Design attributes and principles
Makridakis, S., Fry, C., Petropoulos, F., & Spiliotis, E. (2021) · 2021
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Time Series: Modeling, Computation, and Inference, Second Edition
Prado, R., Ferreira, M. A. R., & West, M. (2021) · 2021
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Bayesian Inference of State Space Models: Kalman Filtering and Beyond
Triantafyllopoulos, K. (2021) · 2021
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Beyond error measures to the utility and cost of the forecasts
Yardley, E., & Petropoulos, F. (2021) · 2021
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Letter 2022 to berkshire shareholders
Buffett, W. E. (2023) · 2022
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Maximizing the out-of-sample sharpe ratio
Lassance, N. (2022) · 2022
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The M5 competition: Background, organization, and implementation
Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2022) · 2022
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Forecasting: theory and practice
Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babai, M. Z., Barrow, D. K., Ben Taieb, S., Bergmeir, C., Bessa, R. J., Bijak, J., Boylan, J. E., Browell, J., Carnevale, C., Castle, J. L., Cirillo, P., Clements, M. P., Cordeiro, C., Cyrino Oliveira, F. L., De Baets, S., Dokumentov, A., Ellison, J., Fiszeder, P., Franses, P. H., Frazier, D. T., Gilliland, M., Gönül, M. S., Goodwin, P., Grossi, L., Grushka-Cockayne, Y., Guidolin, M., Guidolin, M., Gunter, U., Guo, X., Guseo, R., Harvey, N., Hendry, D. F., Hollyman, R., Januschowski, T., Jeon, J., Jose, V. R. R., Kang, Y., Koehler, A. B., Kolassa, S., Kourentzes, N., Leva, S., Li, F., Litsiou, K., Makridakis, S., Martin, G. M., Martinez, A. B., Meeran, S., Modis, T., Nikolopoulos, K., Önkal, D., Paccagnini, A., Panagiotelis, A., Panapakidis, I., Pavía, J. M., Pedio, M., Pedregal, D. J., Pinson, P., Ramos, P., Rapach, D. E., Reade, J. J., Rostami-Tabar, B., Rubaszek, M., Sermpinis, G., Shang, H. L., Spiliotis, E., Syntetos, A. A., Talagala, P. D., Talagala, T. S., Tashman, L., Thomakos, D., Thorarinsdottir, T., Todini, E., Trapero Arenas, J. R., Wang, X., Winkler, R. L., Yusupova, A., & Ziel, F. (2022) · 2022
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Active funds continue to fall short of their passive peers
Armour, B. (2023) · 2023
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Top 5 positions in warren buffett’s portfolio
Best, R. (2023) · 2023
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Kenneth R. French Data Library
French, K. R. (2023) · 2023
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