SZodixStudyAcademic Library
DashboardShelvesOpen accessMy libraryInboxNotesWriteLearnAlerts
More
Ask your libraryNotificationsQuick citeReview
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Hybrid neural network-based metaheuristics for prediction of financial markets: a case study on global gold market
16 references·1 citing·53 second hop
Hybrid neural network-based metaheuristics for prediction of financial markets: a case study on global gold market (2023)Hybrid neural network-based metaheuristic…Supply chain disruption during the COVID-19 pandemic: Recognizing potential disruption management strategies (2022)Supply chain disruption durin…Convolutional neural network for stock trading using technical indicators (2022)Convolutional neural network …The impact of COVID-19 pandemic on the volatility connectedness network of global stock market (2021)The impact of COVID-19 pandem…Forecasting stock market prices using mixed ARIMA model: a case study of Indian pharmaceutical companies (2021)Forecasting stock market pric…Deep learning for credit scoring: Do or don’t? (2021)Deep learning for credit scor…A novel particle swarm optimization-based grey model for the prediction of warehouse performance (2021)A novel particle swarm optimi…The role of investor attention in predicting stock prices: The long short-term memory networks perspective (2020)The role of investor attentio…An improved deep learning model for predicting stock market price time series (2020)An improved deep learning mod…Cybernetics and Systems (2018)Cybernetics and SystemsFinancial Time Series Forecasting – A Deep Learning Approach (2017)Financial Time Series Forecas…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…A Hybrid Artificial Neural Network with Metaheuristic Algorithms for Predicting Stock Price (2017)A Hybrid Artificial Neural Ne…A comprehensive cluster and classification mining procedure for daily stock market return forecasting (2017)A comprehensive cluster and c…Revisiting the Performance of MACD and RSI Oscillators (2014)Revisiting the Performance of…Time Series Momentum (2011)Time Series MomentumTechnical analysis of the financial markets: a comprehensive guide to trading methods and applications (1999)Technical analysis of the fin…Sustainable supply chain decision-making in the automotive industry: A data-driven approach (2024)Sustainable supply chain deci…Efficient Capital Markets: A Review of Theory and Empirical Work (1970)Simple Technical Trading Rules and the Stochastic Properties of Stock Returns (1992)International Momentum Strategies (1998)Portfolio management system in equity market neutral using reinforcement learning (2021)Deep Reinforcement Learning Approach for Trading Automation in the Stock Market (2022)A novel Deep Reinforcement Learning based automated stock trading system using cascaded LSTM networks (2023)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)On Persistence in Mutual Fund Performance (1997)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test (1988)Forecasting with artificial neural networks: (1998)Time series forecasting using a hybrid ARIMA and neural network model (2003)A fuzzy decision system for money investment in stock markets based on fuzzy candlesticks pattern recognition (2019)Performance of Deep Learning in Prediction of Stock Market Volatility (2019)Stock Market Prediction Using Machine Learning (2021)Deep learning for event-driven stock prediction (2015)Financial time series forecasting with deep learning : A systematic literature review: 2005–2019 (2020)Harnessing LLMs for Temporal Data - A Study on Explainable Financial Time Series Forecasting (2023)Machine learning in business and finance: a literature review and research opportunities (2024)Macroeconomics and Reality (1980)Generalized autoregressive conditional heteroskedasticity (1986)Stock market prediction with deep learning: The case of China (2021)Implementation of Long Short-Term Memory and Gated Recurrent Units on grouped time-series data to predict stock prices accurately (2022)Deep Learning and Technical Analysis in Cryptocurrency Market (2023)Oil prices, US stock return, and the dependence between their quantiles (2015)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Predicting the direction of stock market prices using tree-based classifiers (2018)Multivariate CNN‐LSTM Model for Multiple Parallel Financial Time‐Series Prediction (2021)Hybridization of hybrid structures for time series forecasting: a review (2022)Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022 (2023)Judgment under Uncertainty: Heuristics and Biases (1974)Judgment under Uncertainty: Heuristics and Biases (1975)Common risk factors in the returns on stocks and bonds (1993)Forecasting the Equity Risk Premium: The Role of Technical Indicators (2014)Investor Sentiment Aligned: A Powerful Predictor of Stock Returns (2014)Does Academic Research Destroy Stock Return Predictability? (2015)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Scientific method: Statistical errors (2014)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Credit default prediction from user-generated text in peer-to-peer lending using deep learning (2021)Deep reinforcement learning with the confusion-matrix-based dynamic reward function for customer credit scoring (2022)Operational Research and Artificial Intelligence Methods in Banking (2022)CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature (2005)The bibliometric analysis of scholarly production: How great is the impact? (2015)Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case (2020)Deep neural networks with L1 and L2 regularization for high dimensional corporate credit risk prediction (2022)Identifying resilience strategies for disruption management in the healthcare supply chain during COVID-19 by digital innovations: A systematic literature review (2023)Semiconductor supply chain resilience and disruption: insights, mitigation, and future directions (2024)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

  • 2017Deep learning with long short-term memory networks for financial market predictions2,827 cited
  • 2011Time Series Momentum1,470 cited
  • 1999Technical analysis of the financial markets: a comprehensive guide to trading methods and applications771 cited
  • 2022Supply chain disruption during the COVID-19 pandemic: Recognizing potential disruption management strategies456 cited
  • 2021Deep learning for credit scoring: Do or don’t?241 cited
  • 2020An improved deep learning model for predicting stock market price time series173 cited
  • 2017Financial Time Series Forecasting – A Deep Learning Approach114 cited
  • 2014Revisiting the Performance of MACD and RSI Oscillators94 cited
  • 2020The role of investor attention in predicting stock prices: The long short-term memory networks perspective94 cited
  • 2017A comprehensive cluster and classification mining procedure for daily stock market return forecasting91 cited
  • 2017A Hybrid Artificial Neural Network with Metaheuristic Algorithms for Predicting Stock Price88 cited
  • 2021A novel particle swarm optimization-based grey model for the prediction of warehouse performance81 cited
  • 2021The impact of COVID-19 pandemic on the volatility connectedness network of global stock market75 cited
  • 2022Convolutional neural network for stock trading using technical indicators

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

67 cited
  • 2018Cybernetics and Systems65 cited
  • 2021Forecasting stock market prices using mixed ARIMA model: a case study of Indian pharmaceutical companies64 cited
  • Cited by

    • 2024Sustainable supply chain decision-making in the automotive industry: A data-driven approach43 cited