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Interval Forecasting of Financial Time Series by Accelerated Particle Swarm-Optimized Multi-Output Machine Learning System
15 references·0 citing·50 second hop
Interval Forecasting of Financial Time Series by Accelerated Particle Swarm-Optimized Multi-Output Machine Learning System (2020)Interval Forecasting of Financial Time Se…A New Approach to Multiple Time Series Prediction Using MIMO Fuzzy Aggregation Models with Modular Neural Networks (2019)A New Approach to Multiple Ti…Replicating a Trading Strategy by Means of LSTM for Financial Industry Applications (2018)Replicating a Trading Strateg…Forward Forecast of Stock Price Using Sliding-Window Metaheuristic-Optimized Machine-Learning Regression (2018)Forward Forecast of Stock Pri…A multiple support vector machine approach to stock index forecasting with mixed frequency sampling (2017)A multiple support vector mac…Interval-valued time series forecasting using a novel hybrid HoltI and MSVR model (2016)Interval-valued time series f…Maximum and minimum stock price forecasting of Brazilian power distribution companies based on artificial neural networks (2015)Maximum and minimum stock pri…Integrating metaheuristics and Artificial Neural Networks for improved stock price prediction (2015)Integrating metaheuristics an…A fuzzy logic model for forecasting exchange rates (2014)A fuzzy logic model for forec…Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting (2013)Multiple-output support vecto…Fuzzy Refinement Domain Adaptation for Long Term Prediction in Banking Ecosystem (2013)Fuzzy Refinement Domain Adapt…Empirical mode decomposition–based least squares support vector regression for foreign exchange rate forecasting (2012)Empirical mode decomposition–…Different Approaches to Forecast Interval Time Series: A Comparison in Finance (2010)Different Approaches to Forec…A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)A novel hybridization of arti…Forecasting models for interval-valued time series (2008)Forecasting models for interv…Marketing models of consumer heterogeneity (1998)Marketing models of consumer …Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Using artificial neural network models in stock market index prediction (2011)Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction (2014)Listening to Chaotic Whispers (2018)Predicting short-term stock prices using ensemble methods and online data sources (2018)A novel deep learning framework: Prediction and analysis of financial time series using CEEMD and LSTM (2020)A Probabilistic Choice Model for Market Segmentation and Elasticity Structure (1989)The Value of Purchase History Data in Target Marketing (1996)Discrete Choice Methods with Simulation (2001)A Customer Relationship Management Roadmap: What is Known, Potential Pitfalls, and Where to Go (2005)Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force (2016)Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)Time series forecasting using a hybrid ARIMA and neural network model (2003)A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data (2014)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)An optimized model using LSTM network for demand forecasting (2020)Time Series Analysis Forecasting and Control. (1971)Another look at measures of forecast accuracy (2006)A Fuzzy Interval Time-Series Energy and Financial Forecasting Model Using Network-Based Multiple Time-Frequency Spaces and the Induced-Ordered Weighted Averaging Aggregation Operation (2020)Adaptive fuzzy modeling of interval-valued stream data and application in cryptocurrencies prediction (2021)Forecasting with artificial neural networks: (1998)Application of support vector machines in financial time series forecasting (2001)Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)Short-term forecasting of air passenger by using hybrid seasonal decomposition and least squares support vector regression approaches (2014)A multiscale analysis for carbon price drivers (2018)Soft computing hybrids for FOREX rate prediction: A comprehensive review (2018)Forecasting stock market movement direction with support vector machine (2004)Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances (2011)Support vector regression with chaos-based firefly algorithm for stock market price forecasting (2012)Seasonal forecasting of agricultural commodity price using a hybrid STL and ELM method: Evidence from the vegetable market in China (2017)Interval decomposition ensemble approach for crude oil price forecasting (2018)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)A combination method for interval forecasting of agricultural commodity futures prices (2015)Financial time series forecasting using independent component analysis and support vector regression (2009)Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting (2010)Stock price forecast based on combined model of ARI-MA-LS-SVM (2020)Forecasting stock price using integrated artificial neural network and metaheuristic algorithms compared to time series models (2021)Multi-Step Crude Oil Price Prediction Based on LSTM Approach Tuned by Salp Swarm Algorithm with Disputation Operator (2022)A LSTM-based method for stock returns prediction: A case study of China stock market (2015)Deep Learning for Finance: Deep Portfolios (2016)Classification-based financial markets prediction using deep neural networks (2017)Financial market prediction under deep learning framework using auto encoder and kernel extreme learning machine (2020)A Novel Ensemble Learning Approach for Stock Market Prediction Based on Sentiment Analysis and the Sliding Window Method (2022)Implementation of Long Short-Term Memory and Gated Recurrent Units on grouped time-series data to predict stock prices accurately (2022)Time Series Analysis: Forecasting and Control. (1978)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Wavelet Neural Network Prediction Method of Stock Price Trend Based on Rough Set Attribute Reduction (2017)Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis (2018)Advantages of direct input-to-output connections in neural networks: The Elman network for stock index forecasting (2020)
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References

  • 2010A novel hybridization of artificial neural networks and ARIMA models for time series forecasting825 cited
  • 1998Marketing models of consumer heterogeneity790 cited
  • 2015Integrating metaheuristics and Artificial Neural Networks for improved stock price prediction324 cited
  • 2018Forward Forecast of Stock Price Using Sliding-Window Metaheuristic-Optimized Machine-Learning Regression198 cited
  • 2013Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting197 cited
  • 2008Forecasting models for interval-valued time series165 cited
  • 2015Maximum and minimum stock price forecasting of Brazilian power distribution companies based on artificial neural networks165 cited
  • 2012Empirical mode decomposition–based least squares support vector regression for foreign exchange rate forecasting152 cited
  • 2010Different Approaches to Forecast Interval Time Series: A Comparison in Finance103 cited
  • 2018Replicating a Trading Strategy by Means of LSTM for Financial Industry Applications91 cited
  • 2016Interval-valued time series forecasting using a novel hybrid HoltI and MSVR model78 cited
  • 2017A multiple support vector machine approach to stock index forecasting with mixed frequency sampling78 cited
  • 2019A New Approach to Multiple Time Series Prediction Using MIMO Fuzzy Aggregation Models with Modular Neural Networks73 cited

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  • 2013Fuzzy Refinement Domain Adaptation for Long Term Prediction in Banking Ecosystem60 cited
  • 2014A fuzzy logic model for forecasting exchange rates46 cited
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