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Time Series Impact Through Topic Modeling
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Time Series Impact Through Topic Modeling (2022)Time Series Impact Through Topic ModelingA stock price prediction method based on deep learning technology (2021)A stock price prediction meth…News-driven inflation expectations and information rigidities (2020)News-driven inflation expecta…Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong (2020)Incorporating stock prices an…The value of news for economic developments (2018)The value of news for economi…Stock Market Prediction via Multi-Source Multiple Instance Learning (2018)Stock Market Prediction via M…Financial news predicts stock market volatility better than close price (2018)Financial news predicts stock…Natural language based financial forecasting: a survey (2017)Natural language based financ…Practical Bayesian Optimization of Machine Learning Algorithms (2012)Practical Bayesian Optimizati…Predicting risk from financial reports with regression (2009)Predicting risk from financia…EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law (2012)Beyond LDA: Exploring Supervised Topic Modeling for Depression-Related Language in Twitter (2015)Movie Reviews and Revenues: An Experiment in Text Regression (2018)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks (2011)Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos (2018)Technical analysis and sentiment embeddings for market trend prediction (2019)Stock market movement forecast: A Systematic review (2020)PORTFOLIO SELECTION* (1952)Twitter mood predicts the stock market (2011)“Options, Futures, and Other Derivatives” (2016)Forecasting stock market movements using Google Trend searches (2019)Explainable Machine Learning Exploiting News and Domain-Specific Lexicon for Stock Market Forecasting (2021)Novel hybrid model based on echo state neural network applied to the prediction of stock price return volatility (2021)The Behavior of Stock-Market Prices (1965)Deep learning for event-driven stock prediction (2015)A novel multi-source information-fusion predictive framework based on deep neural networks for accuracy enhancement in stock market prediction (2021)Forecasting Stock Market Indices Using Padding-Based Fourier Transform Denoising and Time Series Deep Learning Models (2021)Stock market prediction based on statistical data using machine learning algorithms (2022)The General Theory of Employment, Interest and Money. (1936)The Impact of Uncertainty Shocks (2009)Measuring Economic Policy Uncertainty* (2016)Making Text Count: Economic Forecasting Using Newspaper Text (2020)How has Science Education changed over the last 100 years? An analysis using natural language processing (2021)Words speak as loudly as actions: Central bank communication and the response of equity prices to macroeconomic announcements (2021)On the Impossibility of Informationally Efficient Markets (1980)On the Impossibility of Informationally Efficient Markets (1980)Implications of rational inattention (2003)Sectoral Media Focus and Aggregate Fluctuations (2019)News media versus FRED‐MD for macroeconomic forecasting (2021)News and uncertainty about COVID-19: Survey evidence and short-run economic impact (2022)Noise Trader Risk in Financial Markets (1990)The Limits of Arbitrage (1995)Machine learning models predicting returns: why most popular performance metrics are misleading and proposal for an efficient metric (2021)A Multi Parameter Forecasting for Stock Time Series Data Using LSTM and Deep Learning Model (2023)Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022 (2023)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)A Tutorial on Bayesian Optimization (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Stock Market Forecasting Using Deep Learning and Technical Analysis: A Systematic Review (2020)Stock Price Forecasting with Deep Learning: A Comparative Study (2020)Transformer-based attention network for stock movement prediction (2022)
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References

  • 2012Practical Bayesian Optimization of Machine Learning Algorithms6,690 cited
  • 2017Natural language based financial forecasting: a survey399 cited
  • 2020Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong370 cited
  • 2009Predicting risk from financial reports with regression271 cited
  • 2021A stock price prediction method based on deep learning technology175 cited
  • 2018Financial news predicts stock market volatility better than close price166 cited
  • 2018Stock Market Prediction via Multi-Source Multiple Instance Learning152 cited
  • 2018The value of news for economic developments147 cited
  • 2020News-driven inflation expectations and information rigidities133 cited

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