Stock Price Forecasting

Stock price forecasting aims to predict future stock price movements, assisting investment decisions and risk management. Current research heavily emphasizes the use of advanced machine learning models, including Long Short-Term Memory (LSTM) networks, transformers, and ensemble methods that combine different algorithms (e.g., LSTM with XGBoost), often incorporating external data sources like news sentiment and social media analysis. These efforts aim to improve prediction accuracy and interpretability, ultimately impacting portfolio optimization, algorithmic trading strategies, and a deeper understanding of market dynamics.

Papers

April 17, 2023

Optimum Output Long Short-Term Memory Cell for High-Frequency Trading Forecasting
Adamantios Ntakaris, Moncef Gabbouj, Juho Kanniainen
Long Short Term Memory High Frequency Stock Price Forecasting LSTM Cell

March 24, 2023

The Battle of Information Representations: Comparing Sentiment and Semantic Features for Forecasting Market Trends
Andrei Zaichenko, Aleksei Kazakov, Elizaveta Kovtun, Semen Budennyy
Implicit Sentiment Semantic Feature Stock Price Prediction Sentiment Feature Price Prediction Stock Price Forecasting Informative Representation Twitter Sentiment Social Entity Embeddings

March 13, 2023

TM-vector: A Novel Forecasting Approach for Market stock movement with a Rich Representation of Twitter and Market data
Faraz Sasani, Ramin Mousa, Ali Karkehabadi, Samin Dehbashi, Ali Mohammadi
Recurrent Neural Network Twitter Resource X Vector Market Data Stock Price Forecasting Stock Trend Stock Price Movement Novel Forecasting

October 31, 2022

Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty
Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo, Kentaro Minami
Predictive Performance Stock Price Forecasting Predictive Power Interpretable Prediction Uncertainty Awareness

May 1, 2022

A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Predictions
Yong Xie, Dakuo Wang, Pin-Yu Chen, Jinjun Xiong, Sijia Liu, Sanmi Koyejo
Adversarial Attack Real Text Word Adversarial Setting Stock Price Forecasting Adversarial Generation Victim Model

March 10, 2022

HiSA-SMFM: Historical and Sentiment Analysis based Stock Market Forecasting Model
Ishu Gupta, Tarun Kumar Madan, Sukhman Singh, Ashutosh Kumar Singh
Sentiment Analysis LSTM Network Predictive Model Historical Text Stock Price Forecasting Sentiment Data

January 17, 2022

A Stock Trading System for a Medium Volatile Asset using Multi Layer Perceptron
Ivan Letteri, Giuseppe Della Penna, Giovanni De Gasperis, Abeer Dyoub
Neural Network Multi Layer Stock Market Financial Market Stock Price Forecasting Trading System

November 15, 2021

A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting
Faizal Hafiz, Jan Broekaert, Davide La Torre, Akshya Swain
Neural Architecture Search Multi Criterion Multi Objective Neural Architecture Search Stock Price Forecasting Parsimonious Machine Learning Agent Swarm

Stock Price Forecasting

Papers

Optimum Output Long Short-Term Memory Cell for High-Frequency Trading Forecasting

The Battle of Information Representations: Comparing Sentiment and Semantic Features for Forecasting Market Trends

TM-vector: A Novel Forecasting Approach for Market stock movement with a Rich Representation of Twitter and Market data

Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty

A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Predictions

HiSA-SMFM: Historical and Sentiment Analysis based Stock Market Forecasting Model

A Stock Trading System for a Medium Volatile Asset using Multi Layer Perceptron

A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting