Stock Market Prediction
41 papers with code • 3 benchmarks • 4 datasets
Libraries
Use these libraries to find Stock Market Prediction models and implementations
StockNet
Most implemented papers
HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction
dmis-lab/hats
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Methods that use relational data for stock market prediction have been recently proposed, but they are still in their infancy.
Forecasting directional movements of stock prices for intraday trading using LSTM and random forests
pushpendughosh/Stock-market-forecasting
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Hence we outperform the single-feature setting in Fischer & Krauss (2018) and Krauss et al. (2017) consisting only of the daily returns with respect to the closing prices, having corresponding daily returns of 0. 41% and of 0. 39% with respect to LSTM and random forests, respectively.
Artificial Counselor System for Stock Investment
This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment.
Qlib: An AI-oriented Quantitative Investment Platform
microsoft/qlib
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Quantitative investment aims to maximize the return and minimize the risk in a sequential trading period over a set of financial instruments.
Sentiment Predictability for Stocks
In this work, we present our findings and experiments for stock-market prediction using various textual sentiment analysis tools, such as mood analysis and event extraction, as well as prediction models, such as LSTMs and specific convolutional architectures.
Discovering Bayesian Market Views for Intelligent Asset Allocation
Along with the advance of opinion mining techniques, public mood has been found to be a key element for stock market prediction.
Stock Movement Prediction from Tweets and Historical Prices
Stock movement prediction is a challenging problem: the market is highly stochastic, and we make temporally-dependent predictions from chaotic data.
Learning Target-Specific Representations of Financial News Documents For Cumulative Abnormal Return Prediction
sudy/coling2018
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COLING 2018
The model uses a target-sensitive representation of the news abstract to weigh sentences in the news content, so as to select and combine the most informative sentences for market modeling.
Leveraging Financial News for Stock Trend Prediction with Attention-Based Recurrent Neural Network
Stock market prediction is one of the most attractive research topic since the successful prediction on the market's future movement leads to significant profit.
Predicting the Effects of News Sentiments on the Stock Market
nicklamonica/stock-sentiment-analysis
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Stock market forecasting is very important in the planning of business activities.
