Stock Prediction

20 papers with code • 0 benchmarks • 2 datasets

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Most implemented papers

DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News

Xinyi6/DP-LSTM-Differential-Privacy-inspired-LSTM-for-Stock-Prediction-Using-Financial-News 20 Dec 2019

In this paper, we propose a novel deep neural network DP-LSTM for stock price prediction, which incorporates the news articles as hidden information and integrates difference news sources through the differential privacy mechanism.

HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction

dmis-lab/hats 7 Aug 2019

Methods that use relational data for stock market prediction have been recently proposed, but they are still in their infancy.

Stock trend prediction using news sentiment analysis

nicklamonica/stock-sentiment-analysis 7 Jul 2016

The accuracy of the prediction model is more than 80% and in comparison with news random labeling with 50% of accuracy; the model has increased the accuracy by 30%.

Temporal Relational Ranking for Stock Prediction

hennande/Temporal_Relational_Stock_Ranking 25 Sep 2018

Our RSR method advances existing solutions in two major aspects: 1) tailoring the deep learning models for stock ranking, and 2) capturing the stock relations in a time-sensitive manner.

Artificial Counselor System for Stock Investment

bghojogh/Fuzzy-Investment-Counselor Proceedings of the AAAI Conference on Artificial Intelligence 2019

This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment.

Enhancing Stock Movement Prediction with Adversarial Training

yuxiangalvin/Stock-Move-Prediction-with-Adversarial-Training-Replicate 13 Oct 2018

The key novelty is that we propose to employ adversarial training to improve the generalization of a neural network prediction model.

Improving S&P stock prediction with time series stock similarity

liorsidi/StockSimilarity 8 Feb 2020

Stock market prediction with forecasting algorithms is a popular topic these days where most of the forecasting algorithms train only on data collected on a particular stock.

Multi-Graph Convolutional Network for Relationship-Driven Stock Movement Prediction

start2020/Multi-GCGRU 11 May 2020

However, it is well known that an individual stock price is correlated with prices of other stocks in complex ways.

Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading

Zhihan1996/TradeTheEvent Findings (ACL) 2021

In this paper, we introduce an event-driven trading strategy that predicts stock movements by detecting corporate events from news articles.

Price graphs: Utilizing the structural information of financial time series for stock prediction

BUAA-WJR/PriceGraph 4 Jun 2021

Then, structural information, referring to associations among temporal points and the node weights, is extracted from the mapped graphs to resolve the problems regarding long-range dependencies and the chaotic property.