Predicting Daily Probability Distributions of S&P500 Returns
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[1] Biing-Hwang Juang,et al. Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.
[2] Ashok N. Srivastava,et al. Nonlinear gated experts for time series: discovering regimes and avoiding overfitting , 1995, Int. J. Neural Syst..
[3] James D. Hamilton. Analysis of time series subject to changes in regime , 1990 .
[4] K. Pearson. Contributions to the Mathematical Theory of Evolution , 1894 .
[5] A. B. Poritz,et al. Linear predictive hidden Markov models and the speech signal , 1982, ICASSP.
[6] B.-H. Juang,et al. On the hidden Markov model and dynamic time warping for speech recognition — A unified view , 1984, AT&T Bell Laboratories Technical Journal.
[7] Jens Timmer,et al. Modeling Volatility Using State Space Models , 1997, Int. J. Neural Syst..
[8] Geoffrey E. Hinton,et al. Adaptive Mixtures of Local Experts , 1991, Neural Computation.
[9] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[10] Louis A. Liporace,et al. Maximum likelihood estimation for multivariate observations of Markov sources , 1982, IEEE Trans. Inf. Theory.
[11] A. H. Murphy,et al. Screening probability forecasts: contrasts between choosing and combining , 1995 .
[12] David Haussler,et al. How to use expert advice , 1993, STOC.
[13] Anthony S. Tay,et al. Evaluating Density Forecasts , 1997 .
[14] Andrew J. Filardo. Business-Cycle Phases and Their Transitional Dynamics , 1994 .
[15] A. H. Murphy,et al. Diagnostic verification of probability forecasts , 1992 .
[16] Andreas S. Weigend,et al. Time Series Prediction: Forecasting the Future and Understanding the Past , 1994 .
[17] Biing-Hwang Juang,et al. Hidden Markov Models for Speech Recognition , 1991 .
[18] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[19] L. Baum,et al. A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .
[20] James D. Hamilton,et al. Long Swings in the Dollar: Are They in the Data and Do Markets Know It? The American Economic Review , 1990 .
[21] J. M. Bates,et al. The Combination of Forecasts , 1969 .
[22] Andrew Harvey,et al. Forecasting, Structural Time Series Models and the Kalman Filter , 1990 .
[23] L. Baum,et al. An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process , 1972 .
[24] A. Poritz,et al. Hidden Markov models: a guided tour , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.
[25] Thomas H. McCurdy,et al. Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth , 1994 .
[26] M. Rosenblatt. Remarks on a Multivariate Transformation , 1952 .
[27] James D. Hamilton,et al. Autoregressive conditional heteroskedasticity and changes in regime , 1994 .
[28] S. Shi,et al. Markov gated experts for time series analysis: beyond regression , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).
[29] Bruce E. Hansen,et al. Erratum: The likelihood ratio test under nonstandard conditions: Testing the Markov switching model of GNP , 1996 .
[30] L. Baum,et al. An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology , 1967 .
[31] Andreas S. Weigend,et al. Nonlinear Trading Models Through Sharpe Ratio Maximization , 1997, Int. J. Neural Syst..
[32] Andrew D. Back,et al. A First Application of Independent Component Analysis to Extracting Structure from Stock Returns , 1997, Int. J. Neural Syst..
[33] C. S. Wallace,et al. An Information Measure for Classification , 1968, Comput. J..
[34] Robert A. Jacobs,et al. Hierarchical Mixtures of Experts and the EM Algorithm , 1993, Neural Computation.
[35] Kajal Lahiri,et al. Predicting cyclical turning points with leading index in a markov switching model , 1994 .
[36] Jonathan D. Cryer,et al. Time Series Analysis , 1986, Encyclopedia of Big Data.
[37] Stephen Gray. Modeling the Conditional Distribution of Interest Rates as a Regime-Switching Process , 1996 .
[38] James D. Hamilton. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle , 1989 .
[39] Michael I. Jordan,et al. Hierarchical Mixtures of Experts and the EM Algorithm , 1994, Neural Computation.
[40] Chris Chatfield,et al. Calculating Interval Forecasts , 1993 .