Stock Prediction
26 papers with code • 0 benchmarks • 4 datasets
Benchmarks
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StockNet
Latest papers with no code
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Meme Stock Prediction
More and more investors and machine learning models rely on social media (e. g., Twitter and Reddit) to gather information and predict certain stocks' prices (meme stock).
Selective transfer learning with adversarial training for stock movement prediction
To validate our method, we perform the back-testing on the historical data of two public datasets and a newly constructed dataset.
Stock Index Prediction using Cointegration test and Quantile Loss
Moreover, its performance can depend on which loss is used to train the model.
Accurate Prediction Using Triangular Type-2 Fuzzy Linear Regression
The current survey proposes a triangular type-2 fuzzy regression (TT2FR) model to ameliorate the efficiency of the model by handling the uncertainty in the data.
Quantitative Day Trading from Natural Language using Reinforcement Learning
It is challenging to design profitable and practical trading strategies, as stock price movements are highly stochastic, and the market is heavily influenced by chaotic data across sources like news and social media.
AlphaEvolve: A Learning Framework to Discover Novel Alphas in Quantitative Investment
In this paper, we introduce a new class of alphas to model scalar, vector, and matrix features which possess the strengths of these two existing classes.
Forecasting with Deep Learning: S&P 500 index
Stock price prediction has been the focus of a large amount of research but an acceptable solution has so far escaped academics.
News-Driven Stock Prediction Using Noisy Equity State Representation
News-driven stock prediction investigates the correlation between news events and stock price movements.
A Stock Prediction Model Based on DCNN
The prediction of a stock price has always been a challenging issue, as its volatility can be affected by many factors such as national policies, company financial reports, industry performance, and investor sentiment etc..
Share Price Prediction of Aerospace Relevant Companies with Recurrent Neural Networks based on PCA
To improve the prediction of share price for aerospace industry sector and well understand the impact of various indicators on stock prices, we provided a hybrid prediction model by the combination of Principal Component Analysis (PCA) and Recurrent Neural Networks.
