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Time series modeling and forecasting based on a Markov chain with changing transition matrices
5 references·1 citing·28 second hop
Time series modeling and forecasting based on a Markov chain with changing transition matrices (2019)Time series modeling and forecasting base…Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Deep learning networks for st…Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Predicting stock and stock pr…A Markov regime switching approach for hedging stock indices (2004)A Markov regime switching app…Technical analysis of the financial markets: a comprehensive guide to trading methods and applications (1999)Technical analysis of the fin…Are Stock Returns Predictable? A Test Using Markov Chains (1991)Are Stock Returns Predictable…Can Deep Learning Improve Technical Analysis of Forex Data to Predict Future Price Movements? (2021)Can Deep Learning Improve Tec…EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Financial time series forecasting using support vector machines (2003)Forecasting stock market movement direction with support vector machine (2004)Evaluating multiple classifiers for stock price direction prediction (2015)Sentiment analysis on social media for stock movement prediction (2015)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)Nonlinearity and intraday efficiency tests on energy futures markets (2009)Nonlinearity, data-snooping, and stock index ETF return predictability (2009)Stock price prediction based on LSTM and LightGBM hybrid model (2022)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Testing for a Unit Root in Time Series Regression (1988)A bivariate Markov regime switching GARCH approach to estimate time varying minimum variance hedge ratios (2007)Effectiveness of Minimum-Variance Hedging (2007)Optimal hedging with a regime‐switching time‐varying correlation GARCH model (2007)Does the Stock Market Overreact? (1985)Hierarchical structure in financial markets (1999)Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average? (2007)A systematic review of fundamental and technical analysis of stock market predictions (2019)Applications of deep learning in stock market prediction: Recent progress (2021)Beating the Foreign Exchange Market (1986)Forecasting of Forex Time Series Data Based on Deep Learning (2019)Mixture of Activation Functions With Extended Min-Max Normalization for Forex Market Prediction (2019)Combining multiple feature selection methods for stock prediction: Union, intersection, and multi-intersection approaches (2010)Deep Direct Reinforcement Learning for Financial Signal Representation and Trading (2016)Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis (2020)
this work references cited by second hop

References

  • 2014Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques1,139 cited
  • 2017Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies833 cited
  • 1999Technical analysis of the financial markets: a comprehensive guide to trading methods and applications771 cited
  • 1991Are Stock Returns Predictable? A Test Using Markov Chains117 cited
  • 2004A Markov regime switching approach for hedging stock indices115 cited

Cited by

  • 2021Can Deep Learning Improve Technical Analysis of Forex Data to Predict Future Price Movements?38 cited

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